Grid soil sampling technology is one of the most important information technologies in agriculture. Application of these technologies is a way to understand the extent of needed nutrient elements of soil. The purpose of this research is to investigate the attitude and intention to the extension of grid soil sampling technologies among agricultural specialists in Iran. A survey was used to collect data from 249 specialists. The results using Structural Equation Modeling (SEM) showed that attitude to use is the most important determinant of intention to extension. Attitude of confidence, observability and triability positively affect intention to extension of these technologies. Perceived ease of use indirectly influences the intention to extension through attitude to use.
Article Citation:
Kurosh. Rezaei-Moghaddam, Saeid. Salehi, Abdol-azim. Ajili.
Extension of grid soil sampling technology: application of extended Technology Acceptance Model (TAM).
Journal of Research in Agriculture (2012) 1(1): 078-087.
Full Text:
http://www.jagri.info/documents/AG0013.pdf
Jianqiang Ren_Simulation of regional winter wheat yield by EPIC model.pptgrssieee
The document describes a study that used a crop growth model combined with remotely sensed leaf area index (LAI) data to simulate regional winter wheat yield in northern China. The study area covered 11 counties. Researchers used the EPIC crop growth model optimized with the SCE-UA algorithm. Remotely sensed MODIS LAI data were input to the model. The model was able to accurately simulate winter wheat sowing dates, plant density, fertilizer application rates, and yields compared to field investigation data, demonstrating the potential of the approach for crop monitoring and yield forecasting.
This document provides an introduction and overview of the CERES-Wheat simulation model, which was developed over 10 years through collaboration between various researchers and organizations. The model aims to predict wheat yields based on cultivar, soil, climate, and management inputs in a user-friendly package. It describes the model's development history and objectives to simulate crop growth processes related to development, biomass accumulation, soil water and nitrogen balance. The document outlines the model's intended uses, system boundaries, philosophy of balancing detail across processes, and overview of model operations through interconnected subroutines.
Pros and cons of VRT in Indian Agriculture as compared to Developed countries PragyaNaithani
Variable-rate technology (VRT) allows fertilizer,
chemicals, lime, gypsum, irrigation water and other farm
inputs to be applied at different rates across a field,
without manually changing rate settings on equipment
or having to make multiple passes over an area.
Variable-rate application (VRA) can range from the
simple control of flow rate to the more complex
management of rate, chemical mix and application
pattern. VRA can match changes in crop yield potential
with specific input rates resulting in a more efficient
system and minimising potential environmental impacts.
VRT can be used to deal with spatial variability between
paddocks or between management zones/classes. There
are two types of VRT:
1. Map-based control: a map of application rates is
produced for the field prior to the operation.
2. Real-time control: decisions about what rates
to apply in different locations are made using
information gathered during the operation. This
requires sensors to detect necessary information
‘on-the-go’ and is usually designed for a specific
job such as herbicide application.
This paper is the continuation of the paper published by the authors Arun Balaji and Baskaran [2].
Multiple linear regression (MLR) equations were developed between the years of rice cultivation and Feed
Forward Back Propagation Neural Network (FFBPNN) method of predicted area of rice cultivation / rice
production for different districts pertaining to Kuruvai, Samba and Kodai seasons in Tamilnadu. The
average r2 value in area of cultivation is 0.40 in Kuruvai season, 0.42 in Samba season and 0.46 in Kodai
season, where as the r2 value in rice production is 0.31 in Kuruvai season, 0.23 in Samba season and
0.42 in Kodai season. The Rice Data Simulator (RDS) predicted the area of rice cultivation and rice
production using the MLR equations developed in this research. The range of average predicted area for
Kuruvai, Samba and Kodai seasons varies from 12052.52 ha to 13595.32 ha, 48998.96 ha to 53324.54 ha
and 4241.23 ha to 6449.88 ha respectively whereas the range of average predicted rice production varies
from 45132.88 tonnes to 46074.48 tonnes in Kuruvai, 128619 tonnes to 139693.29 tonnes in Samba and
15446.07 to 20573.50 tonnes in Kodai seasons. The mean absolute relative error (ARE) between the
FFBPNN and multiple regression methods of prediction of area of rice cultivation was found to be 15.58%,
8.04% and 26.34% for the Kuruvai, Samba and the Kodai seasons respectively. The ARE for the rice
production was found to be 17%, 11.80% and 24.60% for the Kuruvai, Samba and the Kodai seasons
respectively. The paired t test between the FFBPNN and MLR methods of predicted area of cultivation in
Kuruvai shows that there is no significant difference between the two types of prediction for certain
districts.
1) The document discusses predicting soil fertility using machine learning techniques such as decision trees, artificial neural networks, support vector machines, and k-nearest neighbors.
2) It analyzes soil data from Haryana, India to determine the most important properties for defining soil fertility and properties that are highly correlated. Conductivity, water holding capacity, and potassium were found to be most important based on a decision tree analysis.
3) Support vector machines using a radial basis kernel performed best with 80% accuracy compared to 63% for decision trees, 55% for artificial neural networks, and 70% for k-nearest neighbors.
The document discusses sample size requirements for assessing statistical moments (measures of central tendency like mean and measures of dispersion like standard deviation) of simulated crop yield distributions from crop growth models.
- A minimum sample size of 15 years of simulated crop yields is sufficient to estimate average crop yields with less than 10% relative error at 95% confidence.
- For symmetric yield distributions, sample sizes of 200 and 1,500 yield observations are needed to estimate the standard deviation and skewness, respectively. More asymmetric distributions require larger sample sizes for standard deviation but smaller sizes for skewness.
- The study provides guidance on minimum sample sizes required to accurately analyze statistics from simulated crop yield data under different climate and soil conditions using crop
Precision agriculture in relation to nutrient management by Dr. Tarik MitranDr. Tarik Mitran
Precision agriculture techniques can help optimize nutrient management by accounting for spatial variability within fields. Soil sampling is done on a grid to produce fertility maps showing nutrient levels in different areas. GPS and GIS combine to map yield and collect data that identifies low-yielding zones. Remote sensing uses imagery to detect differences such as no-till fields. Yield monitors coupled with GPS measure harvest yields in various locations. Variable rate technology then applies nutrients precisely based on need. This precision nutrient management improves efficiency and protects the environment.
Agriculture is the backbone of the country. A lot of factors such as climate change, population growth, food security concerns have driven the sector to seek more innovative/emerging technology/ approaches like AI and IoT's to improve crop yields and to get better farming results.
Jianqiang Ren_Simulation of regional winter wheat yield by EPIC model.pptgrssieee
The document describes a study that used a crop growth model combined with remotely sensed leaf area index (LAI) data to simulate regional winter wheat yield in northern China. The study area covered 11 counties. Researchers used the EPIC crop growth model optimized with the SCE-UA algorithm. Remotely sensed MODIS LAI data were input to the model. The model was able to accurately simulate winter wheat sowing dates, plant density, fertilizer application rates, and yields compared to field investigation data, demonstrating the potential of the approach for crop monitoring and yield forecasting.
This document provides an introduction and overview of the CERES-Wheat simulation model, which was developed over 10 years through collaboration between various researchers and organizations. The model aims to predict wheat yields based on cultivar, soil, climate, and management inputs in a user-friendly package. It describes the model's development history and objectives to simulate crop growth processes related to development, biomass accumulation, soil water and nitrogen balance. The document outlines the model's intended uses, system boundaries, philosophy of balancing detail across processes, and overview of model operations through interconnected subroutines.
Pros and cons of VRT in Indian Agriculture as compared to Developed countries PragyaNaithani
Variable-rate technology (VRT) allows fertilizer,
chemicals, lime, gypsum, irrigation water and other farm
inputs to be applied at different rates across a field,
without manually changing rate settings on equipment
or having to make multiple passes over an area.
Variable-rate application (VRA) can range from the
simple control of flow rate to the more complex
management of rate, chemical mix and application
pattern. VRA can match changes in crop yield potential
with specific input rates resulting in a more efficient
system and minimising potential environmental impacts.
VRT can be used to deal with spatial variability between
paddocks or between management zones/classes. There
are two types of VRT:
1. Map-based control: a map of application rates is
produced for the field prior to the operation.
2. Real-time control: decisions about what rates
to apply in different locations are made using
information gathered during the operation. This
requires sensors to detect necessary information
‘on-the-go’ and is usually designed for a specific
job such as herbicide application.
This paper is the continuation of the paper published by the authors Arun Balaji and Baskaran [2].
Multiple linear regression (MLR) equations were developed between the years of rice cultivation and Feed
Forward Back Propagation Neural Network (FFBPNN) method of predicted area of rice cultivation / rice
production for different districts pertaining to Kuruvai, Samba and Kodai seasons in Tamilnadu. The
average r2 value in area of cultivation is 0.40 in Kuruvai season, 0.42 in Samba season and 0.46 in Kodai
season, where as the r2 value in rice production is 0.31 in Kuruvai season, 0.23 in Samba season and
0.42 in Kodai season. The Rice Data Simulator (RDS) predicted the area of rice cultivation and rice
production using the MLR equations developed in this research. The range of average predicted area for
Kuruvai, Samba and Kodai seasons varies from 12052.52 ha to 13595.32 ha, 48998.96 ha to 53324.54 ha
and 4241.23 ha to 6449.88 ha respectively whereas the range of average predicted rice production varies
from 45132.88 tonnes to 46074.48 tonnes in Kuruvai, 128619 tonnes to 139693.29 tonnes in Samba and
15446.07 to 20573.50 tonnes in Kodai seasons. The mean absolute relative error (ARE) between the
FFBPNN and multiple regression methods of prediction of area of rice cultivation was found to be 15.58%,
8.04% and 26.34% for the Kuruvai, Samba and the Kodai seasons respectively. The ARE for the rice
production was found to be 17%, 11.80% and 24.60% for the Kuruvai, Samba and the Kodai seasons
respectively. The paired t test between the FFBPNN and MLR methods of predicted area of cultivation in
Kuruvai shows that there is no significant difference between the two types of prediction for certain
districts.
1) The document discusses predicting soil fertility using machine learning techniques such as decision trees, artificial neural networks, support vector machines, and k-nearest neighbors.
2) It analyzes soil data from Haryana, India to determine the most important properties for defining soil fertility and properties that are highly correlated. Conductivity, water holding capacity, and potassium were found to be most important based on a decision tree analysis.
3) Support vector machines using a radial basis kernel performed best with 80% accuracy compared to 63% for decision trees, 55% for artificial neural networks, and 70% for k-nearest neighbors.
The document discusses sample size requirements for assessing statistical moments (measures of central tendency like mean and measures of dispersion like standard deviation) of simulated crop yield distributions from crop growth models.
- A minimum sample size of 15 years of simulated crop yields is sufficient to estimate average crop yields with less than 10% relative error at 95% confidence.
- For symmetric yield distributions, sample sizes of 200 and 1,500 yield observations are needed to estimate the standard deviation and skewness, respectively. More asymmetric distributions require larger sample sizes for standard deviation but smaller sizes for skewness.
- The study provides guidance on minimum sample sizes required to accurately analyze statistics from simulated crop yield data under different climate and soil conditions using crop
Precision agriculture in relation to nutrient management by Dr. Tarik MitranDr. Tarik Mitran
Precision agriculture techniques can help optimize nutrient management by accounting for spatial variability within fields. Soil sampling is done on a grid to produce fertility maps showing nutrient levels in different areas. GPS and GIS combine to map yield and collect data that identifies low-yielding zones. Remote sensing uses imagery to detect differences such as no-till fields. Yield monitors coupled with GPS measure harvest yields in various locations. Variable rate technology then applies nutrients precisely based on need. This precision nutrient management improves efficiency and protects the environment.
Agriculture is the backbone of the country. A lot of factors such as climate change, population growth, food security concerns have driven the sector to seek more innovative/emerging technology/ approaches like AI and IoT's to improve crop yields and to get better farming results.
Dr. B. L. Sinha discusses the history and definition of precision agriculture. Precision agriculture has been practiced for hundreds of years through adaptations like the transition from horse-drawn plows to tractors. In recent decades, technology like GPS, GIS systems, and remote sensing has allowed for more precise data collection and analysis at subfield levels. This enables variable applications tailored to spatial and temporal variability in fields. By improving efficiency and reducing waste, precision agriculture benefits farmers through increased profits and more sustainable practices.
Crop Identification Using Unsuperviesd ISODATA and K-Means from Multispectral...IJERA Editor
This document summarizes an article that examines unsupervised classification methods for identifying crops from multispectral remote sensing imagery. It discusses ISODATA and K-means clustering algorithms for classifying imagery without training data. The author applies these methods to an image using ENVI software and compares the results. ISODATA identified five classes - water body, crops, hilly area, and barren land. K-means identified the same classes but with different class distributions between methods. The author concludes unsupervised classification can successfully identify crop types from remote sensing images without prior knowledge of land cover types.
This document discusses precision agriculture and provides an overview of key concepts:
1. Precision agriculture aims to optimize field management to match crop needs, protect the environment, and boost farm economics through efficient practices.
2. It involves characterizing field variability, making decisions based on soil maps and sensor data, and implementing variable-rate technology.
3. Current trends include high-accuracy GPS, input management like variable-rate fertilizer application, and information management tools to aid decision-making.
4. The document describes technologies like guidance systems, drones, wireless sensors, and yield mapping that are part of precision agriculture approaches.
IRJET - Analysis of Land Degraded in Maitha Block of Kanpur Dehat District us...IRJET Journal
This document analyzes land degradation in Maitha Block of Kanpur Dehat district in Uttar Pradesh, India using remote sensing and GIS techniques. Satellite images from 2013 and 2016 were classified to map sodic (saline) land and waterlogged areas. The analysis found that sodic land decreased from 20.96 km2 to 16.32 km2 from 2013 to 2016, while waterlogged areas decreased from 2.9 km2 to 1.2 km2 over the same period. Overall, the total degraded land in the block increased from 25.96 km2 (8.6% of the area) in 2013 to 28.02 km2 (9.52% of the area) in 2016,
Application of GIS & Remote Sensing Technologies: Precision AgricultureTariq Javid
This document discusses the application of geographic information systems (GIS) and remote sensing technologies for precision agriculture. It explains that precision agriculture uses sensors and computer-based GIS tools to respond to intra-field variations observed through remote sensing. The document outlines how vegetation indices like NDVI and EVI generated from remote sensing data can be used to identify healthy and stressed crop growth and monitor changes over time. It argues that precision agriculture's careful utilization of natural resources through updated maps and timely treatments could improve crop quality and yields in Pakistan, lowering market prices and benefiting the economy.
IRJET- Smart Crop-Field Monitoring and Automation Irrigation System using...IRJET Journal
This document describes a proposed smart crop field monitoring and automated irrigation system using IoT technologies. The system uses sensors to monitor soil moisture levels and temperature in crop fields. A Raspberry Pi device collects data from the sensors via an IoT network. The system aims to automate irrigation by turning pumps on and off based on the sensor data, allowing for more precise watering that reduces water usage while maximizing crop yields. It also aims to allow remote monitoring of crop fields using the sensor data collected on the cloud. The system is meant to help modernize agriculture and make it more efficient through precision farming techniques enabled by IoT.
Precision Farming helps findout nutrient and micro nutrient deficiency in minute areas of soils and enables application of nutrients/micro nutrients in the soil where deficiency exists. This saves money and helps soil improvement.
IRJET- Crop Prediction and Disease DetectionIRJET Journal
This document discusses a proposed system for crop prediction and disease detection using data mining techniques and image processing. The system would use algorithms like Apriori and C4.5 to predict crop yields based on past climate data like temperature and rainfall. It would also allow farmers to upload images of crop diseases to identify the disease and recommended treatments. The goal is to help farmers make better decisions around crop selection and disease management given expected climate conditions.
IRJET- Iot Based Intelligent Management for Agricultural Process using Ra...IRJET Journal
This document describes a proposed IoT-based system for intelligent agricultural management using Raspberry Pi. The system would combine wireless sensors with a Raspberry Pi and web server to automate irrigation and fertilizer spraying based on sensor readings. Sensors would monitor soil conditions like moisture and send data to a Raspberry Pi, which would control irrigation and spraying. Farmers could check sensor readings on a web server to know the field status and make informed decisions about watering and fertilizing without overdoing it, improving crop quality and resource efficiency. The system aims to reduce water waste and allow more accurate agricultural management than traditional practices.
IoT Based Intelligent Management System for Agricultural Applicationijtsrd
The growth of technology in any sector is not there in agriculture and this is a problem for India. The government has struggled to do anything for the farming sector which is in an exceptionally deplorable state. The pause in decision making also has led to Indias high rate of unemployment owing to the quality of the economy. The applications in well developed countries involve robotics, aircraft, and artificial intelligence, but they can raise the cost of running and sustain. Currently, operating drones such as these is difficult. In India, only a few farmers can afford to employ such high tech machinery to farm owing to financial constraints. The project is aimed at developing an affordable quad copter for farmers to use on their crops, with the goal of growing their output. We are developing core a framework with support of Raspberry Pi and OpenCV that can help predict crops yield with the help of inputs from numerous different sensor packages. Venkat. P. Patil | Umakant B. Gohatre | Anushka Mhaskar | Akash Jadhav | Prajwal Shetty | Yash Jadhav "IoT Based Intelligent Management System for Agricultural Application" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38578.pdf Paper Url: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/38578/iot-based-intelligent-management-system-for-agricultural-application/venkat-p-patil
Precision Agriculture: a concise introduction Joseph Dwumoh
The presentation supplies a brief introduction to what precision agriculture is, what drives its adoption, and what challenges the acceptance of the technologies involved.
Remote sensing and GIS techniques can provide timely and accurate information for agricultural monitoring over large areas. Remote sensing uses sensors aboard satellites or drones to capture electromagnetic radiation reflected or emitted from crops and soil. GIS allows integration of spatial data for analysis. Applications include crop identification and acreage estimation, growth monitoring, soil moisture and fertility assessment, pest and disease detection, and yield estimation. Various sensors such as multispectral, thermal, LIDAR and hyperspectral are used to analyze vegetation, soil properties, and assess crop health. Drones equipped with different sensors can assist with crop scouting, inventory management and precision agriculture.
precise weed management is very useful under large land holdings which reduces cost of cultivation to a greater extent. remote sensing plays a major role in site specific weed management
The document describes the design and preliminary field testing of a mechanical intra-row weeder to control weeds in organic vegetable farms. Key points:
1) A weeder with rotating rubber-coated rollers was designed to uproot weeds between crop rows using hydraulic power from a tractor. An ultrasonic sensor was added to detect weed height and allow the rollers to move around crops.
2) An initial field test found that the weeder successfully uprooted weeds ranging from 10-18 cm tall and collected them with a vacuum.
3) Further testing is still needed to evaluate the performance of the weeding mechanism and sensor system as well as potential crop damage from the weeder.
The document discusses the application of geospatial technologies in agriculture. It provides examples of how remote sensing, GIS, and GPS technologies can be used to map soil variability, detect crop health issues, monitor pests and diseases, and enable precision farming. These tools provide spatial data and analysis that can improve decision making around irrigation, fertilizer application, pest management, and more. When integrated, geospatial technologies provide valuable information to farmers and agricultural managers.
IRJET- Unmanned Ground Vehicle for Precision FarmingIRJET Journal
1. The document describes an unmanned ground vehicle designed for precision farming using image processing. It carries an infrared camera on a robotic arm to capture plant images.
2. The vehicle uses a line following mechanism to navigate predefined paths autonomously. Images are processed using open source software like OpenCV to calculate the NDVI index and detect plant diseases.
3. NDVI values indicate plant health and are used to identify diseased or stressed plants early before crop damage. This allows farmers to take preventative measures and increase yields with reduced inputs.
results of FieldFact project (EU FP6) concerning relevant EGNOS precision based applications for European agriculture. Three applications show how EGNOS and precision agriculture are critical instruments in transforming agriculture into a sustainable sector.
Berdasarkan analisis data seismik dan sumur, dilakukan pemetaan distribusi probabilitas hidrokarbon di area studi menggunakan metode AVO Fuzzy Inversion. Hasilnya menunjukkan peta probabilitas hidrokarbon berkisar antara 0,5-0,7, gas 0,1-0,5, dan minyak 0,2-0,4. Namun, proses trend analysis dan kalibrasi menunjukkan hasil yang kurang optimal karena pemisahan cluster yang kurang jelas dan ketidakc
Diversity and distribution of butterflies in the open and close canopy forest...Innspub Net
Butterflies were sampled in Cadaclan, San Fernando La Union Botanical Garden (LUBG) of North Luzon to provide information on species-level diversity trend and distribution of butterflies on the open and close canopy portion of the dipterocarp forest from 2012-2014 using field transect method Species accumulation curve shows that additional sampling is needed for the possible turnover of species. Butterfly abundance was higher in open canopy forest with a mean individual of 8.14 per 10 meters out of the 814 total individuals. The close canopy forest had only 4.57 mean individuals for the total of 457. Species level diversity was higher in open canopy forest (H’ = 1.957) compared with the closed canopy forest (H’ = 1.933). These results suggest that butterflies prefer open canopy forest or clearing for their plights. Butterfly spatial distribution was uneven in the dipterocarp forest of LUBG with only 6 species of aggregate assemblages and 98 species with random distribution. Get more articles at: http://www.innspub.net/volume-6-number-1-january-2015-jbes/
This document contains data from an emissions measurement test including:
1. Measurements of gas velocity, temperature, pressure and volumes from a stack and gas meter.
2. Average values are reported for velocity, temperatures, pressures and volumes.
3. Data on the side stream measurement including average flowrate and volume are also presented.
Blind-Spectrum Non-uniform Sampling and its Application in Wideband Spectrum ...mravendi
This document proposes a method for blind-spectrum non-uniform sampling and its application in wideband spectrum sensing. It introduces a blind spectrum signal model and discusses parameters for the sampling method including the number of active bands (N), maximum frequency (fmax), and sampling parameters like the number of samples (L) and sampling pattern (C). It then describes two approaches for spectral recovery from the non-uniform samples using subspace and nonlinear least squares methods. Simulation results demonstrate the method's ability to sense and reconstruct multi-band signals from a reduced set of samples. The document proposes applying this sampling approach to wideband spectrum sensing to lower the sampling rate requirement compared to traditional methods.
Dr. B. L. Sinha discusses the history and definition of precision agriculture. Precision agriculture has been practiced for hundreds of years through adaptations like the transition from horse-drawn plows to tractors. In recent decades, technology like GPS, GIS systems, and remote sensing has allowed for more precise data collection and analysis at subfield levels. This enables variable applications tailored to spatial and temporal variability in fields. By improving efficiency and reducing waste, precision agriculture benefits farmers through increased profits and more sustainable practices.
Crop Identification Using Unsuperviesd ISODATA and K-Means from Multispectral...IJERA Editor
This document summarizes an article that examines unsupervised classification methods for identifying crops from multispectral remote sensing imagery. It discusses ISODATA and K-means clustering algorithms for classifying imagery without training data. The author applies these methods to an image using ENVI software and compares the results. ISODATA identified five classes - water body, crops, hilly area, and barren land. K-means identified the same classes but with different class distributions between methods. The author concludes unsupervised classification can successfully identify crop types from remote sensing images without prior knowledge of land cover types.
This document discusses precision agriculture and provides an overview of key concepts:
1. Precision agriculture aims to optimize field management to match crop needs, protect the environment, and boost farm economics through efficient practices.
2. It involves characterizing field variability, making decisions based on soil maps and sensor data, and implementing variable-rate technology.
3. Current trends include high-accuracy GPS, input management like variable-rate fertilizer application, and information management tools to aid decision-making.
4. The document describes technologies like guidance systems, drones, wireless sensors, and yield mapping that are part of precision agriculture approaches.
IRJET - Analysis of Land Degraded in Maitha Block of Kanpur Dehat District us...IRJET Journal
This document analyzes land degradation in Maitha Block of Kanpur Dehat district in Uttar Pradesh, India using remote sensing and GIS techniques. Satellite images from 2013 and 2016 were classified to map sodic (saline) land and waterlogged areas. The analysis found that sodic land decreased from 20.96 km2 to 16.32 km2 from 2013 to 2016, while waterlogged areas decreased from 2.9 km2 to 1.2 km2 over the same period. Overall, the total degraded land in the block increased from 25.96 km2 (8.6% of the area) in 2013 to 28.02 km2 (9.52% of the area) in 2016,
Application of GIS & Remote Sensing Technologies: Precision AgricultureTariq Javid
This document discusses the application of geographic information systems (GIS) and remote sensing technologies for precision agriculture. It explains that precision agriculture uses sensors and computer-based GIS tools to respond to intra-field variations observed through remote sensing. The document outlines how vegetation indices like NDVI and EVI generated from remote sensing data can be used to identify healthy and stressed crop growth and monitor changes over time. It argues that precision agriculture's careful utilization of natural resources through updated maps and timely treatments could improve crop quality and yields in Pakistan, lowering market prices and benefiting the economy.
IRJET- Smart Crop-Field Monitoring and Automation Irrigation System using...IRJET Journal
This document describes a proposed smart crop field monitoring and automated irrigation system using IoT technologies. The system uses sensors to monitor soil moisture levels and temperature in crop fields. A Raspberry Pi device collects data from the sensors via an IoT network. The system aims to automate irrigation by turning pumps on and off based on the sensor data, allowing for more precise watering that reduces water usage while maximizing crop yields. It also aims to allow remote monitoring of crop fields using the sensor data collected on the cloud. The system is meant to help modernize agriculture and make it more efficient through precision farming techniques enabled by IoT.
Precision Farming helps findout nutrient and micro nutrient deficiency in minute areas of soils and enables application of nutrients/micro nutrients in the soil where deficiency exists. This saves money and helps soil improvement.
IRJET- Crop Prediction and Disease DetectionIRJET Journal
This document discusses a proposed system for crop prediction and disease detection using data mining techniques and image processing. The system would use algorithms like Apriori and C4.5 to predict crop yields based on past climate data like temperature and rainfall. It would also allow farmers to upload images of crop diseases to identify the disease and recommended treatments. The goal is to help farmers make better decisions around crop selection and disease management given expected climate conditions.
IRJET- Iot Based Intelligent Management for Agricultural Process using Ra...IRJET Journal
This document describes a proposed IoT-based system for intelligent agricultural management using Raspberry Pi. The system would combine wireless sensors with a Raspberry Pi and web server to automate irrigation and fertilizer spraying based on sensor readings. Sensors would monitor soil conditions like moisture and send data to a Raspberry Pi, which would control irrigation and spraying. Farmers could check sensor readings on a web server to know the field status and make informed decisions about watering and fertilizing without overdoing it, improving crop quality and resource efficiency. The system aims to reduce water waste and allow more accurate agricultural management than traditional practices.
IoT Based Intelligent Management System for Agricultural Applicationijtsrd
The growth of technology in any sector is not there in agriculture and this is a problem for India. The government has struggled to do anything for the farming sector which is in an exceptionally deplorable state. The pause in decision making also has led to Indias high rate of unemployment owing to the quality of the economy. The applications in well developed countries involve robotics, aircraft, and artificial intelligence, but they can raise the cost of running and sustain. Currently, operating drones such as these is difficult. In India, only a few farmers can afford to employ such high tech machinery to farm owing to financial constraints. The project is aimed at developing an affordable quad copter for farmers to use on their crops, with the goal of growing their output. We are developing core a framework with support of Raspberry Pi and OpenCV that can help predict crops yield with the help of inputs from numerous different sensor packages. Venkat. P. Patil | Umakant B. Gohatre | Anushka Mhaskar | Akash Jadhav | Prajwal Shetty | Yash Jadhav "IoT Based Intelligent Management System for Agricultural Application" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38578.pdf Paper Url: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/38578/iot-based-intelligent-management-system-for-agricultural-application/venkat-p-patil
Precision Agriculture: a concise introduction Joseph Dwumoh
The presentation supplies a brief introduction to what precision agriculture is, what drives its adoption, and what challenges the acceptance of the technologies involved.
Remote sensing and GIS techniques can provide timely and accurate information for agricultural monitoring over large areas. Remote sensing uses sensors aboard satellites or drones to capture electromagnetic radiation reflected or emitted from crops and soil. GIS allows integration of spatial data for analysis. Applications include crop identification and acreage estimation, growth monitoring, soil moisture and fertility assessment, pest and disease detection, and yield estimation. Various sensors such as multispectral, thermal, LIDAR and hyperspectral are used to analyze vegetation, soil properties, and assess crop health. Drones equipped with different sensors can assist with crop scouting, inventory management and precision agriculture.
precise weed management is very useful under large land holdings which reduces cost of cultivation to a greater extent. remote sensing plays a major role in site specific weed management
The document describes the design and preliminary field testing of a mechanical intra-row weeder to control weeds in organic vegetable farms. Key points:
1) A weeder with rotating rubber-coated rollers was designed to uproot weeds between crop rows using hydraulic power from a tractor. An ultrasonic sensor was added to detect weed height and allow the rollers to move around crops.
2) An initial field test found that the weeder successfully uprooted weeds ranging from 10-18 cm tall and collected them with a vacuum.
3) Further testing is still needed to evaluate the performance of the weeding mechanism and sensor system as well as potential crop damage from the weeder.
The document discusses the application of geospatial technologies in agriculture. It provides examples of how remote sensing, GIS, and GPS technologies can be used to map soil variability, detect crop health issues, monitor pests and diseases, and enable precision farming. These tools provide spatial data and analysis that can improve decision making around irrigation, fertilizer application, pest management, and more. When integrated, geospatial technologies provide valuable information to farmers and agricultural managers.
IRJET- Unmanned Ground Vehicle for Precision FarmingIRJET Journal
1. The document describes an unmanned ground vehicle designed for precision farming using image processing. It carries an infrared camera on a robotic arm to capture plant images.
2. The vehicle uses a line following mechanism to navigate predefined paths autonomously. Images are processed using open source software like OpenCV to calculate the NDVI index and detect plant diseases.
3. NDVI values indicate plant health and are used to identify diseased or stressed plants early before crop damage. This allows farmers to take preventative measures and increase yields with reduced inputs.
results of FieldFact project (EU FP6) concerning relevant EGNOS precision based applications for European agriculture. Three applications show how EGNOS and precision agriculture are critical instruments in transforming agriculture into a sustainable sector.
Berdasarkan analisis data seismik dan sumur, dilakukan pemetaan distribusi probabilitas hidrokarbon di area studi menggunakan metode AVO Fuzzy Inversion. Hasilnya menunjukkan peta probabilitas hidrokarbon berkisar antara 0,5-0,7, gas 0,1-0,5, dan minyak 0,2-0,4. Namun, proses trend analysis dan kalibrasi menunjukkan hasil yang kurang optimal karena pemisahan cluster yang kurang jelas dan ketidakc
Diversity and distribution of butterflies in the open and close canopy forest...Innspub Net
Butterflies were sampled in Cadaclan, San Fernando La Union Botanical Garden (LUBG) of North Luzon to provide information on species-level diversity trend and distribution of butterflies on the open and close canopy portion of the dipterocarp forest from 2012-2014 using field transect method Species accumulation curve shows that additional sampling is needed for the possible turnover of species. Butterfly abundance was higher in open canopy forest with a mean individual of 8.14 per 10 meters out of the 814 total individuals. The close canopy forest had only 4.57 mean individuals for the total of 457. Species level diversity was higher in open canopy forest (H’ = 1.957) compared with the closed canopy forest (H’ = 1.933). These results suggest that butterflies prefer open canopy forest or clearing for their plights. Butterfly spatial distribution was uneven in the dipterocarp forest of LUBG with only 6 species of aggregate assemblages and 98 species with random distribution. Get more articles at: http://www.innspub.net/volume-6-number-1-january-2015-jbes/
This document contains data from an emissions measurement test including:
1. Measurements of gas velocity, temperature, pressure and volumes from a stack and gas meter.
2. Average values are reported for velocity, temperatures, pressures and volumes.
3. Data on the side stream measurement including average flowrate and volume are also presented.
Blind-Spectrum Non-uniform Sampling and its Application in Wideband Spectrum ...mravendi
This document proposes a method for blind-spectrum non-uniform sampling and its application in wideband spectrum sensing. It introduces a blind spectrum signal model and discusses parameters for the sampling method including the number of active bands (N), maximum frequency (fmax), and sampling parameters like the number of samples (L) and sampling pattern (C). It then describes two approaches for spectral recovery from the non-uniform samples using subspace and nonlinear least squares methods. Simulation results demonstrate the method's ability to sense and reconstruct multi-band signals from a reduced set of samples. The document proposes applying this sampling approach to wideband spectrum sensing to lower the sampling rate requirement compared to traditional methods.
Tiga kalimat ringkasan dokumen tersebut adalah:
Algoritma baru dikembangkan untuk pengambilan sampel acak (random sampling) dengan menggunakan pendekatan generator variabel acak terbalik berbasis distribusi geometri. Metode ini diujicobakan untuk menghasilkan sampel dari populasi besar dengan jumlah yang tidak pasti menggunakan Microsoft Excel. Hasilnya menunjukkan metode ini mampu menghasilkan sampel yang lebih merata dibandingkan metode
Tracking and camera stations were used to document fisher (Martes pennanti) behavior in Vermont forests over two months. Fifty-eight photos showed 12 visits by fishers, with more activity in March during breeding season. Photos revealed behaviors like scent marking on logs and sticks. Non-invasive tracking and cameras allowed observation without disturbing fishers and provided information about their presence and behaviors.
ARIF RAHMAN, (2012), Pendekatan Antrian M/M/c Dalam Perencanaan Kebutuhan Tenaga Kerja Dengan Teknik Shojinka Pada Sistem Layanan Bersifat Stokastik, Prosiding Seminar Nasional Teknoin, Yogyakarta, pp. B.27-B.32
Audit sampling involves applying audit procedures to less than 100% of transactions or account balances to evaluate characteristics and form conclusions. It is used when reviewing 100% is not efficient. There are three key features - reviewing less than all items, all items having a chance of selection, and evaluating characteristics. Samples can be representative or non-representative due to non-sampling or sampling risks. Statistical and non-statistical sampling differ in how risks are quantified. Attribute sampling classifies items as having or not having attributes, while variable sampling assesses amounts. Audit sampling involves designing the sample, selecting items, and evaluating results to form conclusions.
ARIF RAHMAN, (2013), Pengacakan Random Sampling Dengan Pendekatan Inverse-Transform Random Variate Generator Berbasis Distribusi Hipergeometrik, Prosiding Seminar Nasional Teknoin, Yogyakarta, pp. E.106-E.111
A workshop on Sampling & Types of Sampling delivered by me Zulfiqar Behan.
Date: 27th Jan 2016
workshop titled introduction to research methodology facilitators 1.Kiran Hashmi 2. Zulfiqar Behan
Title: Sampling in research
SLOs
At the end of session participants will be
able to Know types of sampling
Application of sampling
Venue:
JamiaMillia College of Education
Date: January 27, 2016
Time: 11:00 am to 12:00 pm
Facilitator:
Zulfiqar Behan
zulfiqarbehan@yahoo.com
It was a wonderful workshop for M.Ed class and teaching faculty of Jamia Milia College of Education Malir Karachi.
workshop were hand and mind oriented participants took active interest.
Audit sampling is a technique used to test accounts and transactions. It involves examining less than 100% of the items in an account or class. There are two main types: attributes sampling tests for a characteristic like control deviations, while variables sampling estimates monetary amounts like account balances. Sample sizes and risks are determined statistically or judgmentally. Results are projected to the whole population.
This document discusses concepts related to calculus including functions, limits, continuity, and derivatives. The objective is for students to be able to evaluate limits and determine derivatives of algebraic functions. It defines functions and function notation. It discusses limits, continuity, and the definition of the derivative. It provides examples of evaluating limits using theorems and the squeeze principle. It also defines types of discontinuities and conditions for continuity.
Uptake and translocation of copper by mycorrhized seedlings Sterculia setige...researchagriculture
Pot culture experiments were established to determine the effects of
arbuscular mycorrhizal fungus (AMF) (
Glomus fasciculatum
) on tropical gum tree
(
Sterculia setigera
Del.) grown in Copper contaminated soils. AMF and non
-
AMF
inoculated plants were grown in sterilized substrates and subjected to different
copper level (0, 200, 400,600, 800 mg kg
-
1
) concentrations. Root and shoot biomasses
of inoculated plants were significantly higher than those of non
-
inoculated. Copper
concentrations in roots were significantly higher than those in shoots in both the
inoculated and non
-
inoculated plants, indicating this heavy metal mostly accumulated
in the roots of plants. Copper translocation efficiency from root to shoot was lower in
mycorrhizal plants than in nonmycorrhizal ones at any Copper addition levels.
However, at high soil Copper concentrations, shoot Copper concentration of
inoculated plant were significantly reduced by about 50% compared to non
-
inoculated plants. These results indicated that AMF could promote tropical gum tree
growth and decrease the uptake of Cu at higher soil concentrations, thus protecting
their hosts from the toxicity of Copper contaminated soils.
The document discusses how the author used The Evening Chronicle newspaper as a style model for their page 2 article. Some key points:
- The author mimicked the layout, measurements, and features of The Evening Chronicle pages, including the header, contents bar, placement of images, and number/style of columns for articles.
- Both headers included social media links, page number, newspaper name and issue date to attract younger readers and encourage sharing.
- The contents bar listed newspaper departments and used two shades of the same color, like the style model.
- The article placement, sizing of accompanying image, and focus on a celebrity's prime matched the style of The Evening Chronicle article discussed.
Produced e-magazine highlight entrepreneurs and entrepreneurship program, intended for online viewing. Assembled content, managed freelance writers, and executed design and layout.
Agricultural research has strengthened the optimized
economical profit, internationally and is very vast and
important field to gain more benefits.
In future agriculture is the only scope for all the people. But
today number of people having land, but they don’t know how
to yield the crops.
So many of people are doing useless agriculture by
cultivating the crop on improper soil. To implement the
application to identify the types of soil,water source of that
land whether that land is based on rain or bore water. And
suggest what of crop is suitable for that soil. So through this
application provide application for the people to know about
the agriculture. There is no any application to know about the
cultivation. However, it can be enhanced by the use of different
technological resources, tool, and procedures. Predict the type
of crop which one is suitable for that particular soil, weather
condition, temperature and so on. So for, using machine
learning with the set of data set are identified the crop for the
corresponding soil.
Crop Recommendation System to Maximize Crop Yield using Machine Learning Tech...IRJET Journal
This document describes a crop recommendation system that uses machine learning techniques to maximize crop yields. The system collects soil data from testing labs and combines the data with crop information from experts. It then uses an ensemble model with majority voting to recommend crops for specific soil parameters. The ensemble uses support vector machine and artificial neural network learners to make recommendations with high accuracy. The goal is to help farmers choose crops best suited to their soil needs and increase productivity.
Digital Soil Mapping using Machine LearningIRJET Journal
This document describes a study that uses machine learning techniques to predict suitable crops and soil fertility based on analyzing soil nutrients. The researchers collected soil sample data and removed unnecessary attributes before training decision tree, KNN, and random forest models. The random forest model achieved the highest accuracy of 93.6% for predicting crops compatible with the soil's nutrient content and properties. The study aims to help farmers select optimal crops and improve agricultural yield through automated, real-time soil analysis and recommendations.
IRJET - Agrotech: Soil Analysis and Crop PredictionIRJET Journal
This document presents a system for soil analysis and crop prediction using data mining techniques. The system measures soil parameters like pH, nitrogen, phosphorus and potassium using sensors. It then uses a decision tree algorithm to classify the soil and predict suitable crops. The pH value is used to estimate other nutrient values. The nutrient values and soil type are sent over WiFi to a server, which uses machine learning to predict crops and provide fertilizer recommendations to the farmer. The proposed system automates the soil testing process and aims to help farmers select optimal crops and increase agricultural yields.
A Review on Associative Classification Data Mining Approach in Agricultural S...Editor IJMTER
Data mining in agriculture is a very recent research topic. It consists in the
application of data mining techniques to agriculture. Recent technologies are nowadays able to
provide a lot of information on agricultural-related activities, which can then be analyzed in
order to find important information. A related, but not equivalent term is precision agriculture.
This research aimed to assess the various classification techniques of data mining and apply
them to a soil science database to establish if meaningful relationships can be found. A large
data set of soil database is extracted from the Soil Science & Agricultural department, Bhopal
M.P and National Informatics Centre, The application of data mining techniques has never
been conducted for Bhopal soil data sets. The research compares the different classifiers and
the outcome of this research could improve the management and systems of soil uses
throughout a large number of fields that include agriculture, horticulture, environmental and
land use management.
A decision support system (DSS) was developed in Visual Basic 6.0 programming language to match tractor power and implement size. The proper selection and matching of tractor and implements is becoming very important and difficult in Sudan because of the availability of variety of tractor models and powers ranging from 20 to > 100 kW and variety of implement sizes. The program options permit the user to select the type of operation and the types of implements available in his/her farm. The system enables the user to insert the inputs data through file system, and obtain the output easily. The developed system was tested with a case study using data from The Arab Investment Corporation-Um Doom Farm. It was found that the power used in the farm can match the implement available. In addition, it was tested by making comparison between the power required for zero tillage and for conventional tillage. The sensitivity analyses showed that changing in some parameters such as speed, width and soil factor affected the power required for the farm. According to the results, the decision support system worked well in matching tractor power and implements sizes for proper performance. Developing other computer programs to assist farm machinery manager in decision–making to solve the problems will face them in this system can be used to help the managers in the decision-making for calculating the power required and matching power available and implement required for economical machinery use.
This document describes a web application called Agro-Farm Care that aims to help farmers by predicting crops, fertilizers, and detecting diseases from images using machine learning models. The application takes in soil parameters and recommends suitable crops. It also takes in soil and crop details to recommend fertilizers. Additionally, it can detect diseases by analyzing leaf images. The system was developed using tools like Flask, Python, HTML, CSS and aims to benefit farmers by providing crop, fertilizer and disease predictions and recommendations.
Intelligent Chemical Fertilizer Recommendation System for Rice Fields IIJSRJournal
In this paper, a recommendation system for supplementary chemical fertilizers of rice fields is proposed using data mining methods. Traditionally, an expert determines the necessary amount of chemical fertilizer for each field after testing the amount of existing organic materials in the soil. The recommendation provided by the expert is a combination of agricultural science and region-specific conditions. In this paper, thru recognizing the existing pattern in recommendations proposed by two groups of experts for the agricultural lands in Mazandaran Province in recent years, a predictive model is proposed. Different artificial intelligence techniques are compared with each other and the best one among them is introduced
Precision agriculture in maize-based cropping systemsCIMMYT
Precision agriculture aims to ensure crops and soil receive exactly what they need through information technology. It can benefit the environment and farm profits by better using resources like nutrients, water, and pesticides in a spatially and temporally targeted way. Key technologies enabling precision agriculture include GPS, earth observation satellites, drones, proximal sensors, and ICT. These allow for remote sensing, variable rate application, and decision support. Precision agriculture adapted for smallholders in developing countries must address intra-farm variability and be implemented through affordable, appropriate technologies delivered via mobile apps or other ICT to optimize resource use at multiple scales.
This document summarizes research on the development and testing of a dual-purpose disc applicator for applying granular fertilizer and liquid pesticides to field crops. Testing assessed the uniformity of fertilizer distribution patterns at different application rates and disc speeds, finding the best pattern was achieved at medium application rates and 550 rpm. Droplet size distributions of liquid applications were also evaluated, with the best uniformity coefficient obtained at 5000 rpm and 90 L/ha. The dual-purpose applicator was found to improve upon manual application methods and help address labor shortages in crop production and application safety concerns.
Soil Characterization and Classification: A Hybrid Approach of Computer Visio...IJECEIAES
This paper presents soil characterization and classification using computer vision & sensor network approach. Gravity Analog Soil Moisture Sensor with arduino-uno and image processing is considered for classification and characterization of soils. For the data sets, Amhara regions and Addis Ababa city of Ethiopia are considered for this study. In this research paper the total of 6 group of soil and each having 90 images are used. That is, form these 540 images were captured. Once the dataset is collected, pre-processing and noise filtering steps are performed to achieve the goal of the study through MATLAB, 2013. Classification and characterization is performed through BPNN (Back-propagation neural network), the neural network consists of 7 inputs feature vectors and 6 neurons in its output layer to classify soils. 89.7% accuracy is achieved when back-propagation neural network (BPNN) is used.
IRJET- IoT based ANN for Prediction of Soil using Cloud and AIIRJET Journal
This document describes a proposed IoT-based artificial neural network system to analyze soil and environmental elements. Multiple IoT nodes would be deployed to collect data on soil composition, which would be sent to a server for processing and storage in the cloud. The system aims to use the collected data and AI algorithms to predict crop yields and categorize soils for different uses like farming, construction, and industry. It provides background on current soil testing methods and issues with analysis. The proposed system architecture and requirements are then outlined, with the goal of centralizing land information and usability analysis through cloud storage.
Analysis of crop yield prediction using data mining techniqueseSAT Journals
Abstract
Agrarian sector in India is facing rigorous problem to maximize the crop productivity. More than 60 percent of the crop still depends on monsoon rainfall. Recent developments in Information Technology for agriculture field has become an interesting research area to predict the crop yield. The problem of yield prediction is a major problem that remains to be solved based on available data. Data Mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. This paper presents a brief analysis of crop yield prediction using Multiple Linear Regression (MLR) technique and Density based clustering technique for the selected region i.e. East Godavari district of Andhra Pradesh in India.
Keywords: Agrarian Sector, Crop Production, Data Mining, Density based clustering, Information Technology, Multiple Linear Regression, Yield Prediction.
The effects of multiple layers feed-forward neural network transfer function ...IJECEIAES
In the area of machine learning performance analysis is the major task in order to get a better performance both in training and testing model. In addition, performance analysis of machine learning techniques helps to identify how the machine is performing on the given input and also to find any improvements needed to make on the learning model. Feed-forward neural network (FFNN) has different area of applications, but the epoch convergences of the network differs from the usage of transfer function. In this study, to build the model for classification and moisture prediction of soil, rectified linear units (ReLU), Sigmoid, hyperbolic tangent (Tanh) and Gaussian transfer function of feed-forward neural network had been analyzed to identify an appropriate transfer function. Color, texture, shape and brisk local feature descriptor are used as a feature vector of FFNN in the input layer and 4 hidden layers were considered in this study. In each hidden layer 26 neurons are used. From the experiment, Gaussian transfer function outperforms than ReLU, sigmoid and tanh transfer function. But the convergence rate of Gaussian transfer function took more epoch than ReLU, Sigmoid and tanh.
SOIL FERTILITY AND PLANT DISEASE ANALYZERIRJET Journal
1) The document proposes a soil fertility and plant disease analyzer system that would leverage machine learning and data analytics to analyze historical and real-time sensor data to provide accurate recommendations to farmers.
2) By detecting diseases early and considering soil quality factors, the system aims to help farmers select optimal crops and improve yields while reducing risks from diseases or soil issues.
3) The system has the potential to revolutionize how farmers make decisions and help address challenges in Indian agriculture through timely recommendations accessible on mobile and web apps.
Precision Farming and Good Agricultural Practices (1).pptxNaveen Prasath
Precision agriculture (PA), as the name implies, refers to the application of precise and correct amounts of inputs like water, fertilizers, pesticides etc. at the correct time to the crop for increasing its productivity and maximizing its yields. The use of inputs (i.e. chemical fertilizers and pesticides) based on the right quantity, at the right time and in the right place.
This type of management is commonly known as “Site-Specific management”
Strictly based on Global Positioning System (GPS) i.e. unique character is precise in time and space.
IRJET - Survey on Soil Classification using Different TechniquesIRJET Journal
The document discusses different techniques for classifying soil types, including machine learning algorithms. It provides an overview of previous research that has used support vector machines, decision trees, naive Bayes, neural networks, and convolutional neural networks to classify soils based on their properties and spectral data. The document also describes common soil classification methods used in India based on location and particle size. It evaluates the advantages and disadvantages of different soil classification techniques.
This document summarizes a global research project aimed at reducing land health risks and targeting agroforestry interventions to enhance land productivity. Key points include:
- Developing methods for evidenced-based management of land health through land health surveillance.
- Applying these methods to multi-scale targeting of sustainable land management and assessing intervention outcomes.
- Establishing a sentinel site surveillance framework using stratified random sampling to monitor soil health.
- Developing soil-plant spectral diagnostics using spectroscopy to map soil properties.
- Creating regional spatial information systems and out-scaling the work through various initiatives.
Similar to Extension of grid soil sampling technology; application of extended Technology Acceptance Model (TAM) (20)
Identification and Evaluation of Antifungal Compounds from Botanicals for th...researchagriculture
Red rot is a devastating disease in sugarcane caused by fungus,
Colletotrichum
falcatum
. In this study, eighteen different botanicals were screened for
identifying effective antifungal compound against
C.
falcatum.
Among the plants
screened, 15 per cent aqueous leaf extract of
Psoralea corylifolia
alone inhibited 100
per cent growth of both mycelium as well as spore germination under
in vitro
conditions. The extract did not exhibit any inhibitory effect to the beneficial microbes
viz.
,
Pseudomonas fluorescens
,
Bacillus megaterium
and
Gluconacetobacter
diazotrophicus
which are normally used in sugarcane. The effective plant extracts
exhibiting 100 per cent antifungal activity was subjected to TLC, HPLC and GC
-
MS
analysis to identify the bioactive antifungal compound. It revealed the
presence of
7H
-
furo [3,2
-
G] (1) benzopyran
-
7
-
one as main bioactive compound which is thought to be
the intermediate of antifungal compound, 8
–
methoxypsoralen formed during
biosynthesis.
Pesticidal efficacy of crude aqueous extracts of Tephrosia vogelii L., Alli...researchagriculture
Cabbage aphid (
Brevicoryne brassicae
L.) is one of the most problematic
pests in smallholder vegetable production, causing significant yield losses in heavy
infestations. Current control strategy focuses on use of synthetic pesticides that
consequently lead to decimation of natural enemies, development of insect
resistance and resurgence and upset biodiversity. Botanical pesticides have been used
widely in smallholder farmers but not much documented literature exists on efficacy
of these products. A field trial was done to assess the efficacy of crude aqueous
extracts of
Tephrosia vogelii
,
Allium sativum
and
Solanum incanum
in controlling
Brevicoryne brassicae
in
Brassica napus
production. The trial was laid in a randomized
complete block design (RCBD) with five treatments replicated four times. The five
treatments used in the experiment were
T
.
vogelii
,
A
.
sativum
,
S
.
incanum
,
dimethoate and control. Wingless adult female aphids were inoculated three weeks
after transplanting of seedlings. Spraying and data collection were done weekly for
four weeks. Data was collected on aphid nymph and adult counts on the third leaf
from the aerial plant part of randomly selected plants from each treatment for
24 hours after the application of treatments and total plant fresh weight per each
treatment. There were significant differences (p<0.05)><0.05) on the yield of rape. It was concluded that
T. vogelii
,
S
.
incanum
and
A
.
sativum
aqueous crude extracts have some pesticidal
effects on aphid in rape
production.
Influence of Long Term Nitrogen and Potassium Fertilization on the Biochemist...researchagriculture
As the tea plantation in hilly tracts are located in slopes, the management of
fertilizer regimes is somewhat challengeable due to leaching which in turn affect the
quality of tea soil. In light of this fact the present study was focused to determine the
quality of tea soil in terms of the evaluation of certain physical and biological
characteristics as influenced by various dosage of fertilizer applications. The impact of long
term nitrogen and potassium fertilization on biochemical characteristics and microbial
activities in tea soil has been analyzed in the present study. Different sources and rates of
nitrogen (ammonium sulphate and urea), and potassium (muriate of potash) were tested
at two soil depths (0
-
10 cm and 10
-
20 cm) and for two seasons (premonsoon and
monsoon). The acidic tea soil was further acidified with nitrogen application and the
extent of acidification varied with the fertilizer type and season. Soil respiration rates were
higher in 0
-
10 cm soils and were positively related to soil nitrogen and potassium
concentrations. Among the soil enzymes analyzed, urease activity exhibited different
trends in the two soil depths at different seasons. Urease activity tended to increase with
increasing potassium application rates, whereas higher cellulase activity was associated
with lower nitrogen application rates. This study clearly indicates that the soil quality
depends on the fertilizer application rates and season.
Anther Culture of Pepper: Morphological Charactersitics of Fruits of Androgen...researchagriculture
The presented study describes the effectiveness of induced androgenesis in
in vitro pepper anther culture. The aim of this study was the establishment of
effective technology for induction of embryogenesis in pepper anther culture;
development of the embryos into plantlets; successful adaptation and acclimatization
of plantlets from sterile to greenhouse conditions, and the breeding process of
obtained androgenetic pepper lines in the plastic tunnel conditions. From 19 pepper
genotypes under investigation, 12 possessed potential for embryo formation in
anther culture. After the acclimatization and adaptation of plantlets, seed material
from four pepper genotypes were collected: Piran, Kurtovska kapija SR, Zlaten medal
SR and Féherözön. From the collected seed material, breeding processes of
androgenetic pepper lines was set up in plastic tunnel (from April
-
October
2007
-
2010). The pepper genotypes and androgenetic lines as their products differ
among themselves in the length of phonological phases, fruit type and fruit utilization.
Detailed study for characterization of morphological and production parameters of
the fruits was established that indicate to sort out lines with positive characteristics.
Uses of Ganoderma and other Mushrooms as Medicine in Oshana and Ohangwena r...researchagriculture
Basidiomycetes fungi, including
Ganoderma lucidum
, have a variety of uses
such as providing nutrition and medical remedies. The mushroom
G. lucidum
has
been used for a long time to cure liver problems, heart condition, asthma, cancer,
high blood pressure and arthritis. Recently, it has been associated with boosting
immune systems in HIV infected persons. It is for these reasons that the mushroom
has attracted a lot of attention leading to proposals of cultivating to increase supply
to the Southern African market. This study was initiated with the objective of
determining the uses of
Ganoderma
species and other mushrooms by local
communities in Oshana and Ohangwena Regions of northern Namibia. A survey was
conducted in the 10% households of each of the two northern regions of Namibia.
A questionnaire for face
-
to
-
face interviews was designed and applied to the two
Regions. The information survey has revealed that
Ganoderma
species have a variety
of other traditional uses including veterinary applications, while other five species of
mushrooms are used as nerve calming tonics and as treatment of skin infections. The
study found out that those interviewed in Ohangwena Region use more mushrooms
for medicinal purposes than those interviewed in Oshana Region.
Farmers’ Constraints In Rice Production In South - East Nigeriaresearchagriculture
The study was carried out in South East Nigeria to evaluate the
socioeconomic attributes of rice farmers and identify the major constraints facing the
rice enterprise in the area. The study relied mainly on primary data obtained by
questionnaire and interview administered on a total of 158 farmers across four states
that constitute the South East Agro
-
ecological area. Descriptive statistics was mainly
used to analyze the data collected. Findings show that farmers in rice production were
dominated by married, literate, male farmers. Major constraints to rice production
include poor extension contact, lack of finance, high cost of agrochemical, lack of
inorganic fertilizer, lack of processing facilities/ standard measure for rice, lack of
credit, and delay in supply of improved rice varieties. It was recommended that the
government should expose farmers to skills and knowledge required to overcome the
constraints in rice production through the development of extension
training/ teaching service, development of rural infrastructure, irrigation/storage/
processing facilities and credit supply at affordable interest rates.
Biodiversity of Butterflies at Ambasamudram Taluk, Tirunelveli District, Tam...researchagriculture
The present study has been aimed to explore the existing diversity of
butterflies from Ambasamudram Taluk, Tirunelveli District, Tamil Nadu. A total of
19 genera and 23 species belonging to eight families were recorded. Out of these,
Nymphalidae were dominant with 7 species, followed by Papilionidae (5 species),
Pieridae (5 species), Danaidae (3 species), Acraeidae (1 species), Hesperiidae
(1 species), Lycaenidae (1 species), and Satyridae (1 species). Nymphalidae was found
to be the most dominant members with 30.43% followed by Papilionidae (21.74%),
Pieridae (17.39%) and Danaidae (13.04%). The minimum number of species found in
this habitat was from the families such as Acraeidae (4.35%), Hesperiidae (4.35%),
Lycaenidae (4.35%) and Satyridae (4.35%).
Technical Efficiency Differentials and Resource - Productivity Analysis amon...researchagriculture
- The study analyzed the technical efficiency and resource productivity of 96 smallholder soybean farmers in Benue State, Nigeria.
- Results from a transcendental logarithmic stochastic frontier model showed technical efficiencies varied widely from 0.254 to 0.999 with a mean of 0.718, indicating production was in stage III of irrational production.
- Land and fertilizer use was effective as confirmed by estimated coefficients between zero and one, depicting stage II production. Productivity could be enhanced by expanding farm size while maintaining labor to move from stage III to II.
Factors affecting agricultural sustainable activities among wheat producersresearchagriculture
The sustainability of agricultural activities has been emphasized in many
studies. The main objective of this study is to determine the major factors affecting
the adoption of
sustainable activities among wheat producers in Marvdasht county in
Iran. The Survey research was used and the sample consists of 178 farmers that
selected with simple random sampling technique from 10 villages. Findings showed a
positive correlation between educational level, knowledge on sustainability, attending
on educational classes, participation in extension activities, social norms and
conducting sustainable agricultural activities. The regression findings showed that
age, educational level, knowledge on sustainability, agricultural income, total land of
family, attending on educational classes, participation in extension activities, social
norms, controllability of production factors were major variables to explain variability
in adoption of sustainable activities among wheat producers. The study has provided
recommendations to improve of adoption rate in sustainable agricultural activities.
Effect of seaweed liquid fertilizer (SLF) prepared from Sargassum wightii an...researchagriculture
The effect of Seaweed Liquid Fertilizer (SLF) of
Sargassum wightii
and
Hypnea
musciformis
were evaluated on the seedling growth and biochemical parameters of
the pulse,
Cyamopsis tetragonoloba
(L). The seeds of
C. tetragonoloba
soaked in SLF
performed better when compared to the water soaked controls in terms of growth
and certain biochemical attributes. The seeds were sown in soil and SLF were added
to soil bed in four different concentrations separately (0.5%, 1%, 2% and 5% w/v).
C.
tetragonoloba
seedlings showed positive response at 0.5% concentration of aqueous
seaweed extracts in almost all the growth parameters studied. Similarly, a significant
increase in the content of photosynthetic pigments and biochemical constituents such
as soluble protein and starch was noted. The use of
Sargassum
and
Hypnea
extracts
proved to be effective.
Analysis of the effects of monetary and fiscal policy indicators on agricult...researchagriculture
This document analyzes the effects of monetary and fiscal policy indicators on agricultural output in Nigeria from 1990-2000. It specifically examines the relationship between money supply, interest rates, inflation, savings, budgetary allocation and the output of cereals like maize, millet, rice and wheat. The results of a regression analysis showed that money supply, budgetary allocation and interest rates had a significant relationship with agricultural output, while inflation and savings were not significant. The analysis also revealed that while budgetary allocations to agriculture increased dramatically over the period, agricultural output levels remained largely the same, indicating a weak relationship between fiscal policy and output.
Contamination by trace metals (ETM) assessment of the plants populating the ...researchagriculture
The proportioning of the metal element traces by ICP
-
AES (Inductively
Coupled Plasma
-
Atomic Spectrometry Emission) in the mining residues of the dumps,
and the plants which populate the mine field of Zaida (High Moulouya), allowed to
highlight an important contamination as well as residues of the plants (
Stipa
tenuifolia
,
Reseda phyteuma
and
Matthiola longipetala
).
This contamination is materialized by strong concentrations in ETM (Lead,
Zinc, Copper and Cadmium).On the level of the plants the distribution of these ETM
(Lead, Zinc, Copper and Cadmium) is variable according to the vegetative species and
their bodies.
The simultaneous presence of the various elements as well induces an
increasing toxicity on the flora as on fauna and consequently on the local population.
Effects of storage conditions on viability, germination and sugar content of ...researchagriculture
Pearl millet (
Pennisetum glaucum
) is the most widely grown type of millet in
Africa and Asia. Pearl millet is well adapted to growing in areas characterized by
drought, low soil fertility, and high temperature. It grow well in soil with high salinity
or low pH.
In northern Namibia, pearl millet grains are stored in wooden, plastic and
cement containers for future consumption and also seeds for the next planting
season. This study looked at viability, germination and sugar content of pearl millet
grains in different containers after 0
-
16 months post
-
harvest.
Germination and
viability of pearl millet grains decreased as the period of storage increased, and this
was more obvious especially in cement and wooden containers. Viability in wooden
container ranged between 64
-
50% after 8
-
16 months post
-
harvest compared to
83
-
74% in plastic container and 30
-
12% in wooden container after a similar period of
storage. Pearl millet grains were found to contain high amounts of starch and sucrose
for the first four months and it decreases as storage time increase. As the duration
time of storing the pearl millet grain increased, the amount of starch and sucrose
decreased. This happened in all storage containers but there was a rapid loss in starch
and sucrose content in cement storage than in the other storage facilities.
Biodegradation of insecticidal compounds of Clausena anisata and Plectrant...researchagriculture
Essential oils of some aromatic plants are suggested in Northern Cameroon
as alternatives to hazardous pesticides having harmful effects on the consumer and
the environment. The active compounds of these essential oils are very volatile, easily
biodegradable. To be effective, treatments should be made with short interval and
regular time. This mode of use generates the accumulation of constituents of these
essential oils on the treated food and could limit food security and safety. The present
study aimed at evaluating the variation of the constituent’s quality of
Clausena
anisata
(Rutaceae)
and
Plectranthus glandulosus
(Lamiaceae)
essential oils and their
levels on food products according to time. In this way, samples of corn grains and
flour were treated with these essential oils and stored during 150 days. During this
storage, the persistent compounds present in these samples were extracted by
hydrodistillation and analyzed by GC/FID. The obtained
results showed that, essential
oils concentration decreases on food products according to the duration of storage,
with half
-
life times (IT50) of 24.16 and 34.61 days for
C. anisata
, and 25 and 38.75
days for
P. glandulosus
, respectively on grains and flour. At 150 days after the
treatment, there is no more that six constituents of
C. anaisata
and 3 of
P.
glandulosus
on the grains, and 10 and seven constituents on the flour respectively for
these two essential oils. The rates of these persistent constituents are more than 62.5
times lower than the toxic concentration observed from the day of treatment. At
these used doses, these constituents are not toxic to consumers.
Extension of grid soil sampling technology: application of extended Technolog...researchagriculture
Grid soil sampling technology is one of the most important information
technologies in agriculture. Application of these technologies is a way to understand
the extent of needed nutrient elements of soil. The purpose of this research is to
investigate the attitude and intention to the extension of grid soil sampling
technologies among agricultural specialists in Iran. A survey was used to collect data
from 249 specialists. The results using Structural Equation Modeling (SEM) showed
that attitude to use is the most important determinant of intention to extension.
Attitude of confidence, observability and triability positively affect intention to
extension of these technologies. Perceived ease of use indirectly influences the
intention to extension through attitude to use.
Effect of elements of communication on effectiveness of poultry technology m...researchagriculture
This study was carried out to ascertain the effect of elements of
communications on effectiveness of poultry technology messages in Delta State,
Nigeria. A sample size of 180 poultry farmers and 46 extension agents were randomly
selected and used for the study. The findings showed that the poultry technology
messages communicated to farmers included climate change adaptation measures,
poultry waste management, bird flu prevention, prevention of predators and exotic
breeds of broiler and layer birds. All the elements of communication such as source
(sender), message, channel, and receiver had positive correlation with effectiveness
of poultry technology messages. There is a need to sustain the use of a combination
of channels, various elements in the communication process should be seriously
considered in message designs, its execution and extension agents. Poultry farmers
should be encouraged to improve on their role performance.
Assessment of aquaculture sediment for agricultural fertilizer supplement an...researchagriculture
Overuse of farmlands for crop production and rising cost of chemical
Overuse of farmlands for crop production and rising cost of chemical fertilizers have
grossly affected crop yield, production and food availability, and the search for
alternative use of locally available aquaculture
-
waste for fertilizer and soil
improvement can improve crop yield and food availability for the teaming population
of Nigeria and other sub
-
Saharan African countries. This research determined the pH,
Organic Matter, nitrate and phosphate qualities of 10 fishpond sediments for use as
agricultural fertilizer supplement and soil conditioner in Owerri, Nigeria. Samples
were subjected to standard physicochemical analysis. The pH ranged from 8.1
-
7.3,
organic matter from 46.6
-
61.3 g/kg, nitrate from 2.6
-
3.2 g/kg and phosphate from
0.05
-
0.1 g/kg. The higher the organic matter in the sediment samples, the higher the
recorded pH, nitrate and phosphate from the different ponds sediments. Organic
material, nitrate, phosphate and pH variation in the sediments might be due to
nutrients added to pond water from fertilizer, unconsumed feed, fish feaces and
metabolites. The nitrate and phosphate are major plant nutrients; organic matter can
be used as soil conditioner. The pH can determine the soil chemistry and availability
of the nutrients. The fish pond sediment can help to improve soil texture and soil
fertility, which may influence soil aeration, water, and nutrient
-
holding capacity and
root penetration by crops and increased crops growth and yield. It can serve as
alternative uses for fertilizer, soil conditioner, and its application as a waste
management approach in aquaculture for environmental sustainability.
Seed morphometric studies of some Kenaf ( Hibiscus canabinus ) accessions researchagriculture
Fifteen kenaf lines collected from kenaf and Jute Improvement Programme
of Institute of Agricultural Research and Training (I.A.R.& T.) were subjected to digital
imaging analysis using USB microscope with digital imaging software (Veho™ UK) and
Vernier caliper to study the seed morphometric of available kenaf accession and the
possibility of using the morphometric data to determine variations between the
accessions. Ten seeds in four replicates of each seed lot were randomly selected and
measurement of the seed length, seed width, seed angle and seed thickness were
taken. The measurements were inputted and saved into Microsoft excel from where
the mean value of each parameters were calculated for each replicates. Data were
subjected to Analysis of variance, correlation analysis, principal component analysis
and clustering analysis. Variation exit among seed of kenaf accessions though they
had similar microscopic appearance features. Seed area, which was a function of seed
length and seed width contributed largely to the variation that exist between the seed
of kenaf accessions. Accession HC
-
583
-
31
2
, clearly distinguished itself from others and
therefore can be used in parent selection during breeding programmes. The inclusion
of this seed morphometrics trait in taxonomic description of kenaf is recommended to
increase the accuracy of morphological classification of kenaf.
Analysis of adaptation and extent of adaptation to climate variability among ...researchagriculture
The performance of agriculture is influenced by many factors including
climate variability. This factor is gradually being recognized as a key element in
shaping the form, scale, size and time
-
frame of agricultural productivity. Climate
variability is expected to have significant economic, environmental and social impacts
on various sectors of the Kenyan economy. In particular, rural farmers who depend on
major crops like maize and wheat for their livelihoods are likely to bear the brunt of
adverse impacts. The extent to which these impacts are felt depends in large part on
the extent of adaptation in response to climate variability. The key question here is,
“Why are wheat farmers in Rongai district facing continued decline in wheat output
despite evidence from both national and continental perspective that farmers have
adapted to climatic variability”. This study seeks to find out whether wheat farmers in
Rongai District have adapted to climate variability, and if that is the case, to what
extent. The study used multistage sampling procedure to select 150 wheat farmers in
Rongai district informed by both primary and secondary data sources. Data analysis
was done using descriptive statistics. The results indicated that indeed, farmers in the
area were able to recognize that temperatures have increased and there has been a
reduction in the volume of rainfall as well the vegetation cover. They were also able
to note changes in disease occurrence and pest infestation. The percentage of
farmers who perceived the changes was 62% while those who did not were 38%. The
percentage of farmers who perceived changes in temperature, precipitation and
vegetation cover were all equal. This indicates that the farmers were able to relate all
the three indicators of climate variability similarly.
Rice is one of the most important cereal crops of developing countries and
the staple food of about 65% of the world’s population. The rice crops have been
greatly disturbed by the heavy metals. The present study deals with the toxic effect of
sodium arsenate on morphological and molecular variation through SDS
-
PAGE in 10
rice (
Oryza sativa
L.) varieties. Ten varieties of rice were grown under different
concentration (25 ppm, 50 ppm and 100 ppm) of sodium arsenate against control.
Morphological parameters like shoot length, root length, leaf area and biomass
showed marked differences among ten rice varieties. The proteins were separated
through SDS
-
PAGE gel electrophoresis and calculated their molecular weight. The
morphological and molecular variations induced in rice varieties by arsenic stress
provide a new insight leading to a better understanding of the heavy metal response
in plants.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...Sérgio Sacani
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
Current Ms word generated power point presentation covers major details about the micronuclei test. It's significance and assays to conduct it. It is used to detect the micronuclei formation inside the cells of nearly every multicellular organism. It's formation takes place during chromosomal sepration at metaphase.
The debris of the ‘last major merger’ is dynamically youngSérgio Sacani
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
ESPP presentation to EU Waste Water Network, 4th June 2024 “EU policies driving nutrient removal and recycling
and the revised UWWTD (Urban Waste Water Treatment Directive)”
Extension of grid soil sampling technology; application of extended Technology Acceptance Model (TAM)
1. Extension of grid soil sampling technology:
application of extended Technology Acceptance Model (TAM)
Keywords:
Grid soil sampling technology, Technology acceptance model, intention,
attitude, Iran.
ABSTRACT:
Grid soil sampling technology is one of the most important information
technologies in agriculture. Application of these technologies is a way to understand
the extent of needed nutrient elements of soil. The purpose of this research is to
investigate the attitude and intention to the extension of grid soil sampling
technologies among agricultural specialists in Iran. A survey was used to collect data
from 249 specialists. The results using Structural Equation Modeling (SEM) showed
that attitude to use is the most important determinant of intention to extension.
Attitude of confidence, observability and triability positively affect intention to
extension of these technologies. Perceived ease of use indirectly influences the
intention to extension through attitude to use.
078-087 | JRA | 2012 | Vol 2 | No 1
This article is governed by the Creative Commons Attribution License (http://creativecommons.org/
licenses/by/2.0), which gives permission for unrestricted use, non-commercial, distribution, and
reproduction in all medium, provided the original work is properly cited.
www.jagri.info
Journal of Research in
Agriculture
An International Scientific
Research Journal
Authors:
Kurosh. Rezaei-Moghaddam1
,
Saeid. Salehi2
,
Abdol-azim. Ajili3
.
Institution:
1. Assistant Professor, Dept.
of Agricultural Education
and Extension, College of
Agriculture, Shiraz
University, Fars Province,
Iran.
2. M.S in Agricultural
Education and Extension,
3. Assistant Professor,
Dept. of Agricultural
Education and Extension,
Ramin University of natural
resource and agriculture,
Ramin, Khuzestan Province,
Iran.
Corresponding author:
Kurosh. Rezaei-Moghaddam.
Email:
Salehi.saeid85@gmail.com
rezaei@shirazu.ac.ir
Web Address:
http://www.jagri.info
documents/AG0013.pdf.
Dates:
Received: 20 Dec 2011 Accepted: 16 Jan 2012 Published: 30 May 2012
Article Citation:
Kurosh. Rezaei-Moghaddam, Saeid. Salehi, Abdol-azim. Ajili.
Extension of grid soil sampling technology: application of extended Technology
Acceptance Model (TAM).
Journal of Research in Agriculture (2012) 1: 078-087
Original Research
Journal of Research in Agriculture
JournalofResearchinAgriculture An International Scientific Research Journal
2. INTRODUCTION
Application of new technologies based on
"high-input and high-output" conventional strategy has
caused fundamental changes in the process of
production. Technological advances have contributed to
increased productivity of crop production in Iran. For
example, yields of irrigated wheat and barley increased
from 1700 kg/ha and 1670 kg/ha in 1980
(Abdulhosainzadeh, 1986) to 3054 kg/ha and 2594 kg/ha
in 2000 (Iran Statistical Center, 2002). Despite these
successes, the agricultural production system has been
criticized for technical and allocative inefficiencies
(Torkamani & Hardaker, 1996). Environmental
technology is usually considered to comprise products
and services developed for purposes of environmental
improvement. Use of these technologies can decrease
demand on natural systems and increase ability to control
the environmental consequences of production
(Rezaei-Moghaddam et al., 2005). This is the goal of
precision farming that implies the maturity of wisdom-
oriented technologies and aims at "optimized input-
output solution" (Shibusawa, 2002).
The concept of precision agriculture, based on
information technology, is becoming an attractive idea
for managing natural resources and realizing modern
sustainable agricultural development (Maohua, 2001).
The main activities of precision agriculture are data
collection, processing and targeted application of inputs
(Fountas et al., 2005). The central ideas of precision
agriculture are understanding spatial variability of soil
properties, crop status and yield within a field;
identifying the reasons for yield variability; making
farming prescription and crop production management
decisions based on variability and knowledge
implementing site-specific field management operations;
evaluating the efficiency of treatment; and accumulating
spatial resource information for further management
decision making (Maohua, 2001).
Precision farming technologies have designed to
provide extensive information and data to assist farmers
when making site-specific management decisions.
By making more informed and better management
decisions, farmers can become more efficient, paying
lower production costs, and, in turn, become more
profitable (Arnholt et al., 2001).
Grid soil sampling is based on GPS technology.
This is a method of breaking a field into square grids that
generally range from 1 to 2.5 acres, and sampling soils
within those grids to determine appropriate application
rates (Grisso et al., 2002). Grid soil sampling involves
partitioning a field into grids of a specified size and
pulling soil samples from the grids. This technology
allows measurement of within-field variability of soil
fertility. Another type of soil sampling involves taking
samples from several management zones which are
identified by characteristics such as soil type or
topography. Information gathered from soil sampling, as
well as other information such as soil
electro-conductivity, may then be used to generate
variable rate lime or fertilizer recommendations for
different grids o r ma nage ment zo nes
(English et al., 2000).
Conceptual model and research hypotheses
The "Technology Acceptance Model (TAM)" of
Davis and his colleagues (1989) is perhaps most widely
applied to explain or predict application of information
technologies (Yi et al., 2006). Davis (1989) based the
TAM on the Theory of Reasoned Action (TRA)
(Fishbin & Ajzen, 1975) by defining perceived
usefulness and perceived ease of use as constructs that
predict behavior intention and usage of technologies.
This structural equation model demonstrated the
simultaneous effects of potential information system
users' perceptions of usefulness and ease of the use of
technology on both the intention to adopt technology and
the actual use of technology (Adrian et al., 2005).
079 Journal of Research in Agriculture (2012) 1: 078-087
Rezaei-Moghaddam et al.,2012
3. The innovation adoption literature showed
technology characteristics that can affect adoption.
The factors compatibility of new technologies with
current practices, triability and observability of their
results affect in the decision process of adoption
(Rogers, 1983, 1995). Also, Adrian et al., (2005) have
shown that attitude to confidence is used to measure the
confidence of a producer to learn and use precision
agriculture technologies. We extended the TAM with
new variables (Fig. 1). The purpose of this research is to
investigate the attitude and intention to extension of grid
soil sampling technologies among Iranian agricultural
specialists.
Based on Fig.1, the following hypotheses are
proposed:
H1. Attitude of confidence will affect perceived ease of
use (H1a), attitude to use (H1b), perceived usefulness
(H1c) and intention to extension (H1d) of grid soil
sampling technologies.
H2. Perceived ease of use will affect attitude to use
(H2a), perceived usefulness (H2b) and intention to
extension (H2c) of grid soil sampling technologies.
H3. Perceived usefulness will affect attitude to use (H3a)
and intention to extension (H3b) of grid soil sampling
technologies.
H4. Attitude to use will affect intention to extension of
grid soil sampling technologies.
H5. Observability will affect perceived ease of use
(H5a), perceived usefulness (H5b), attitude to use (H5c)
and intention to extension (H5d) of grid soil sampling
technologies.
H6. Triability will affect perceived ease of use (H6a),
perceived usefulness (H6b), attitude to use (H6c) and
intention to extension (H6d) of grid soil sampling
technologies.
H7. Compatibility will affect perceived ease of use
(H7a), perceived usefulness (H7b), attitude to use (H7c)
and intention to extension (H7d) of grid soil sampling
technologies.
Research method
A cross-sectional survey was used to collect
information using questionnaire. Data to test the model
was gathered among agricultural specialists in Khuzestan
and Fars, two southern provinces in Iran. A stratified
random sampling was used to gather data. The sample
consists of 249 agricultural specialists from the
population of 705. The study was conducted in two
phases. First, the questionnaire was pilot-tested with 30
randomly selected agricultural specialists from out of
sample. Based on the feedback from the pilot test, the
questionnaire was refined and a revised final
questionnaire was developed. The Cronbach’s alpha for
all variables were well above the cited minimums of 0.70
(Nunnally, 1978, Nunnally & Bernstein, 1994) and,
ranged from 0.71 to 0.91. Second, questionnaires were
distributed to agricultural specialists in Khuzestan and
Fars provinces. Data were analyzed using the LISREL
software version 8.54 and SPSS software version 11.5.
Variables Definitions
Perceived Ease of Use (PEOU)
This is defined as the belief that using a
particular technology (grid soil sampling technology in
this study) will be free of physical and mental
effort (Davis, 1989). The scale consisted of
four items (alpha = 0.72).
Journal of Research in Agriculture (2012) 1: 078-087 080
Rezaei-Moghaddam et al.,2012
Fig.1 Research model
4. Perceived Usefulness (PU)
This variable measuring the extent to which a
person believed that the grid soil sampling technology
was capable of being used advantageously and provided
expected outcomes. The scale consisted of four items
(alpha = 0.71).
Attitude to Use (ATU)
Taylor and Todd (1995) defined attitude scale
which measured whether individuals like or dislike using
the technology and how they felt using the technology.
We operationally defined attitude to use as the
prospective specialist's positive or negative feeling about
the adopting grid soil sampling technologies. The scale
consisted of three items (alpha = 0.74).
Attitude of Confidence (AOC)
This variable measures the confidence of a
producer to learn and use grid soil sampling
technologies. Adrian et al., (2005) argued that the
attitude of having the ability to learn and use precision
agriculture technologies, influence the perception of ease
of use. The scale consisted of three items (alpha = 0.79).
Intention to Extension (INE)
Behavioral intention is defined as the strength of
the prospective adopter's intention to make or to support
the adoption decision (Phillips et al., 1994). We
measured the intention to extension as specialist's
intention to extension of grid soil sampling technologies
among farmers. This variable consisted of four items
(alpha = 0.71).
081 Journal of Research in Agriculture (2012) 1: 078-087
Rezaei-Moghaddam et al.,2012
Table 1: Confirmatory factor analysis (CFA) for research model of grid soil sampling technology
Variable Item Mean
Standard
Deviation
Factor
Loading
t-value α-Cronbach (>0.7) ρc (>0.6)
AVE
(>0.5)
Intention to
Extension
0.71 0.860 0.672
INE1 3.95 0.77 0.77 16.69
INE2 3.97 0.73 0.87 45.77
INE4 3.90 0.80 0.81 19.37
Attitude to
Use
0.74 0.875 0.701
ATU1 4.31 0.69 0.80 25.28
ATU2 4.08 0.75 0.84 26.33
ATU3 3.97 0.76 0.87 50.38
Perceived
Usefulness
0.71 0.845 0.645
PU2 3.90 0.80 0.81 23.19
PU3 3.90 0.80 -0.78 15.83
PU4 3.90 0.80 0.81 23.73
Perceived Ease of Use 0.72 0.803 0.674
PEOU2 3.18 0.98 0.70 8.02
PEOU3 3.72 0.85 0.92 36.12
Compatibility 0.91 0.840 0.725
COM2 3.24 1.01 0.83 8.79
COM3 3.01 1.01 0.87 10.63
Triability 0.74 0.796 0.661
TRI1 4.01 0.78 0.78 9.90
TRI2 4.10 0.76 0.85 9.52
Observability 0.77 0.834 0.716
OBS1 4.01 0.72 0.82 16.00
OBS2 4.03 0.77 0.87 26.93
Attitude of Confidence 0.79 0.775 0.634
AOC1 2.16 0.89 -0.86 22.05
AOC2 4.15 0.71 0.72 6.42
5. Observability (OBS)
This means the extent to observe the results of an
innovation (grid soil sampling technology in this study)
for others. The scale consisted of two items
(alpha = 0.77).
Triability (TRI)
This variable is defined as probability to test an
innovation (grid soil sampling technology in this study)
in a small area (of farm). The scale consisted of three
items (alpha = 0.74).
Compatibility (COM)
It is defined as individual's interpretation of
economic advantages of grid soil sampling technology
with existing values, past experiences and future needs.
The scale consisted of three items (alpha = 0.91).
RESULTS
Measurement model
We evaluated the proposed model using
Structural Equation Modeling (SEM). The items used for
the variables are included in table 1. We tested the data
for reliability and validity using Confirmatory Factor
Analysis (CFA). We see in Table-1 that all factor items
for PEOU, PU, ATU, INE, AOC, OBS, TRI and COM
fit were all above 0.7. Factor loadings indicate the
correlation between the item and the latent variable.
When the coefficients exceed the 0.7, then the empirical
data fit the proposed model (Fornell & Larcker, 1981).
The composite reliability was estimated to
evaluate the internal consistency of the measurement
model. Table 1 shows the composite reliabilities (ρc) of
the variables in the model ranged from 0.775 to 0.875.
Then, all variables have suitable reliabilities
(Fornell & Larcker, 1981). These showed that all
measures had strong and adequate reliability and
discriminate validity. As shown in Table 1, the Average
Variance Extracted (AVE) for all measures also
exceeded 0.5. The completely standardized factor
loadings and individual item reliability for the observed
variables were presented in Table 1.
Table 2 shows the results of the goodness of fit
measures. Goodness of fit measures includes
Chi-Square/Degree of Freedom (χ2
/df),
Goodness-of-Fit (GFI), Normed Fit Index (NFI),
Comparative Fit Index (CFI), Root Mean square
Residual (RMR), Root Mean Square Error of
Approximation (RMSEA) and Adjusted Goodness of Fit
Index (AGFI). As we see the measurement model test
presented a good fit between the data and the proposed
measurement model. The χ2
/df value was 1.32, less than
J ö r e s k o g a n d S ö r b o m ( 1 9 8 3 & 1 9 9 3 ) ,
Journal of Research in Agriculture (2012) 1: 078-087 082
Rezaei-Moghaddam et al.,2012
goodness of
fit measure
Measure
recommended*
Results in
this survey
χ2
/df ≤3 1.32
p-value ≥005 0.56
NFI ≥0.90 0.98
NNFI ≥0.90 0.98
CFI ≥0.90 0.99
GFI ≥0.90 0.99
AGFI ≥0.90 0.95
RMR ≤0.05 0.026
RMSEA ≤0.10 0.039
Table 2: Model evaluation overall fit measurements
Source: Jöreskog, & Sörbom, 1983 & 1993;
Gefen et al., 2000; Markland, 2006 Fig. 2: SEM analysis for grid soil sampling technology
6. Gefen et al., (2000) and Markland (2006) suggestion
fewer than three. The GFI is 0.99. RMSEA was less than
the recommended range of acceptability (≤0.10)
suggested by Jöreskog and Sörbom (1983 & 1993),
Gefen et al., (2000) and Markland (2006). Then the
goodness of fit indices such as χ2
/df, NFI, NNFI, CFI,
GFI, AGFI, RMR and RMSEA are acceptable (Table 2).
Structural Model
Hypotheses testing
The results of inter-correlations have been shown
in Table 3. We see in this table that the variables are inter
-correlated. Also, the Fig-2 presents the standardized
coefficients for each of the paths. Attitude of confidence
has significant direct effect on perceived ease of use
(γ= 0.17, p<0.05), perceived usefulness (γ=0.15, p<0.05)
and intention to extension (γ=0.15, p<0.05) of grid soil
sampling technologies. These are consistent with
H1a, H1c and H1d. The attitude of confidence has no
significant direct effect on attitude to use. This is not
consistent with H1b. But, the attitude of confidence has a
significant indirect effect on attitude to use through
perceived ease of use.
Based on agricultural specialists' worldviews,
perceived ease of use directly affect attitude to use
(ß=0.33,p<0.01) and perceived usefulness
(γ=0.22, p<0.01), consistent with H2a and H2b. The
perceived ease of use has no significant direct effect on
the intention to extension of grid soil sampling
technologies. This is not consistent with H2c. But, fig.2
showed that perceived ease of use has a significant
indirect effect on intention to extension through attitude
to use.
The results showed that perceived usefulness has
no direct effect on attitude to use and intention to
extension (Fig.2). Consistent with H4, attitude to use has
the highest direct effect on the intention to extension
(ß=0.43,p<0.01) of grid soil sampling technologies.
Similarly, observability has direct effect on
perceived ease of use (γ=0.19, p<0.05), perceived
usefulness (γ=0.14, p<0.05), attitude to use (γ=0.28,
p<0.01) and intention to extension (γ=0.21, p<0.01) of
grid soil sampling technologies (Fig.2). These results are
consistent with H5a, H5b, H5c and H5d.
For hypothesis 6, we see in fig.2 that triability
has significant and positive effects on perceived ease of
use (γ=0.16, p<0.05) and intention to extension
(γ=0.21, p<0.01) of grid soil sampling technologies.
These results are consistent with H6a and H6d. Also,
083 Journal of Research in Agriculture (2012) 1: 078-087
Rezaei-Moghaddam et al.,2012
Table 3: Scale properties and correlations for grid soil sampling technology
*: significant in p<0.05 **: significant in p<0.01
- Parentheses are variation range of Likert scale
Mean SD INE ATU PU PEOU COM TRI OBS AOC
INE
(4-20)
15.53 2.36
ATU
(3-15)
12.36 1.84 0.54**
PU
(4-20)
13.16 1.83 0.26**
0.20**
PEOU
(4-20)
13.54 2.02 0.41**
0.37**
0.34**
COM
(4-20)
12.99 3.05 -0.09 -0.04 0.13 0.04
TRI
(3-15)
11.27 2.02 0.49**
0.25**
0.54**
0.29**
0.15**
OBS
(2-10)
8.05 1.27 0.49**
0.32**
0.16*
0.25**
-0.06 0.53**
AOC
(3-15)
9.77 1.56 0.23**
-0.11 0.21*
0.29**
0.03 0.28**
0.09
7. triability has indirect effect on intention to extension
through perceived ease of use and attitude to use. Fig.2
showed that triability has not direct effect on attitude to
use and perceived usefulness.
Compatibility has a direct effect on perceived
usefulness (ß=0.22, p<0.01), consistent with H7b.
But the effects of compatibility on perceived ease of use,
attitude to use and intention to extension are not
significant.
Fig.2 showed that the explained variance (SMC)
in perceived ease of use, perceived usefulness, attitude to
use and intention to extension are 0.15, 0.17, 0.34 and
0.51, respectively.
DISCUSSION
The results showed that attitude to use is the
most important factor to intention to extension of grid
soil sampling technologies. The role of attitude in
changing intention and behavior is emphasized (Fishbin
& Ajzen, 1975; Rezaei-Moghaddam et al., 2005). Both
perceived ease of use and perceived usefulness have no
direct effect on intention to extension of grid soil
sampling technologies. This is in accord with the results
of Adrian et al. (2005). Koufaris (2002) showed that
perceived ease of use is not a significant determinate for
intension to use. Also, the results of
Venkatesh and Davis (1996) and Venkatesh (2000)
implies that perceived ease of use has a direct and
significant effect on behavioral intention to use in the pre
-implementation test, but little influence on intentions
over a period. However, perceived ease of use has
significant positive effect on attitude to use and
indirectly influences the intention to extension of grid
soil sampling technologies. This is consistent
with the results of Hung et al., (2006) and
Schepers and Wetzels (2007). Prior studies indicated that
perceived ease of use has direct effect on perceived
usefulness (Fu et al., 2006; Davis, 1989; Schepers &
Wetzels, 2007). Our study presents a causal
relationship between these two factors.
Attitude of confidence has a significant direct
effect on intention to extension. Also, this factor
indirectly affect on intention to extension of grid soil
sampling technologies through perceived ease of use and
attitude to use. The findings are consistent with the
results of Adrian et al., (2005). In fact, an attitude of
confidence can lead to a better understanding of the
technology's usefulness, and then leading to a propensity
to adopt the technology. Producers who indicated
confidence about using and learning technologies
showed greater propensity to adopt precision agriculture
technologies (Adrian et al., 2005).
One of the exciting aspects of our study is the
influence of innovation characteristics on intention to
extension. Many researchers emphasized on the
characteristics of innovation to adoption (Rogers, 1983,
1995). The results showed that observability has
significant direct effect on all dependent variables i.e.
perceived ease of use, perceived usefulness, attitude to
use and intention to extension of grid soil sampling
technologies. Also, observability indirectly affect on
attitude to use through perceived ease of use.
This variable has an indirect effect on intention to
extension through perceived ease of use and attitude to
use. The importance of observability has been
emphasized in previous studies (Karahanna et al., 1999).
Compatibility only has significant direct effect
on perceived usefulness. The results of Wu and Wang
(2005) showed that compatibility affects positively and
has direct influences on perceived usefulness.
Chau and Hu (2002a) showed that compatibility is a
significant determinant of perceived usefulness but not
perceived ease of use.
Another characteristic is triability. Our study
showed that triability has significant direct effect on
perceived ease of use. Also, the results imply that
triability has indirect effects on both attitude to use
through perceived ease of use and intention to extension
Journal of Research in Agriculture (2012) 1: 078-087 084
Rezaei-Moghaddam et al.,2012
8. through perceived ease of use and attitude to use. Many
studies confirm that test of a technology in a small area
of farm leads to better decisions related to adoption by
farmers (Rogers, 1983).
CONCLUSION
In this research, we tried to test the extended
technology acceptance model. We integrated the attitude
of confidence, and characteristics of innovation by
Rogers (1983, 1995) i.e. observability, compatibility and
triability to it. The findings indicated that the explained
variance by this model was higher than the previous
studies related to information technologies in agriculture.
Then, careful attention should be paid to characteristics
of grid soil sampling technologies.
The results showed that the most important
determinant for intention to extension of grid soil
sampling technologies is attitude to use. The relationship
between attitude and behavioral intention has been
emphasized. This is important to develop positive
attitudes towards technology for successful adoption.
This finding has policy implications for agricultural
development policy makers so that can help extension
agents, agricultural educators and agricultural
administrators to present suitable training and services to
change attitude of clients.
Our study provides a starting point for
agricultural development decision makers in Iran to
extension and application of information system
technologies in agriculture. However, additional research
is needed to apply the extended technology acceptance
model proposed by this study to other contexts. A survey
would be useful to predict attitude and intension of
agricultural specialists in other provinces towards
information technologies. Also, further development of
the model with additional constructs such as
environmental impacts of these technologies are
proposed.
As with all empirical researches, this study has a
few limitations. The most important is that the model
was tested in only one context i.e. grid soil sampling
technologies. The research should be extend to another
precision agriculture technologies such as
VRT-technologies (irrigation, spraying, tillage …) and
Yield monitoring.
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