16 most essential nutrients of soil. These nutrients can be classified as:
1. The primary macronutrients: nitrogen (N), phosphorus (P), potassium (K)
2. The secondary macronutrients: calcium (Ca), sulfur (S), magnesium (Mg)
3. The micronutrients: boron (B), chlorine (Cl), manganese (Mn), iron (Fe), zinc (Zn), copper
(Cu),molybdenum (Mo), nickel (Ni)
These nutrients are supplied by the soil and by the addition of fertilizers such as manure, compost, and fertilizer salts.
A soil testing program can be divided into four main components:
Soil sample preparations
Measurement
Reference analysis
Calibration
Validation
Predictions
https://www.youtube.com/watch?v=Lm1UKqqUhQ8&t=42s
Introduction -Remote means – far away ; Sensing means – believing or observing or acquiring some information.
Remote sensing means acquiring information of things from a distance with sensors. (without touching the things)
Sensors are like simple cameras except that they not only use visible light but also other bands of the electromagnetic spectrum such as infrared, microwaves and ultraviolet regions.
Distance of Remote Sensing, Definition of remote sensing - Remote Sensing is:
“The art and science of obtaining information about an object without being in direct contact with the object” (Jensen 2000).
India’s National Remote Sensing Agency (NRSA) defined as : “Remote sensing is the technique of deriving information about objects on the surface of the earth without physically coming into contact with them.”
Remote Sensing Process, - (A) Energy Source or Illumination.
(B) Radiation and the Atmosphere.
(C) Interaction with the Target.
(D) Recording of Energy by the Sensor.
(E) Transmission, Reception, & Processing.
(F) Interpretation and Analysis.
(G) Application.
Remote sensing platforms , History of Remote Sensing, Applications of remote sensing - In Agriculture, In Geology, Applications of National Priority.
Introduction -Remote means – far away ; Sensing means – believing or observing or acquiring some information.
Remote sensing means acquiring information of things from a distance with sensors. (without touching the things)
Sensors are like simple cameras except that they not only use visible light but also other bands of the electromagnetic spectrum such as infrared, microwaves and ultraviolet regions.
Distance of Remote Sensing, Definition of remote sensing - Remote Sensing is:
“The art and science of obtaining information about an object without being in direct contact with the object” (Jensen 2000).
India’s National Remote Sensing Agency (NRSA) defined as : “Remote sensing is the technique of deriving information about objects on the surface of the earth without physically coming into contact with them.”
Remote Sensing Process, - (A) Energy Source or Illumination.
(B) Radiation and the Atmosphere.
(C) Interaction with the Target.
(D) Recording of Energy by the Sensor.
(E) Transmission, Reception, & Processing.
(F) Interpretation and Analysis.
(G) Application.
Remote sensing platforms , History of Remote Sensing, Applications of remote sensing - In Agriculture, In Geology, Applications of National Priority.
Remote sensing and aerial photography study notes. Including concept and history of RS, visual image interpretation, digital image interpretation, application of RS, digital imaging, application of remote sensing etc.
Remote Sensing: Normalized Difference Vegetation Index (NDVI)Kamlesh Kumar
The Normalized Difference Vegetation Index (NDVI) is a numerical indicator that uses the visible and near-infrared (NIR) bands of the electromagnetic spectrum to analyze whether the target (image) being observed contains green vegetation or not. Healthy vegetation (chlorophyll) reflects more near-infrared (NIR) and green light compared to other wavelengths. But it absorbs more red and blue light. This is why our eyes see vegetation as the colour green. If we could see near-infrared, then it would be strong for vegetation too.
It is basically measured through the use of Intensity, Hue and saturation of an image and through pixels as well.
The density of vegetation (NDVI) at a certain point on the image is equal to the difference in the intensities of reflected light in the red and infrared range divided by the sum of these intensities.
푁퐷푉퐼=((푁퐼푅−푅퐸퐷))/((푁퐼푅+푅퐸퐷))
The result of this formula generates a value between -1 and +1. If you have low reflectance (low values) in the red band and high reflectance in the NIR, this will yield a high NDVI value. And vice versa.
Remote Sensing and its Applications in AgricultureVikas Kashyap
Here is a presentation prepared by me on Remote sensing and its Applications in agriculture. This presentation created after studying many regarding websites, articles and research papers. Thank You
Remote Sensing Data Acquisition,Scanning/Imaging systemsdaniyal rustam
full of concepts about RS data acquisition scanning and imaging systems. Best for students of remote sensing. in this presentation we briefly explained the concept of scanning in remote sensing.
Standard Soil Testing Laboratory
time consuming, Laborious, use of chemical and reagents which effect human health and environment, costly, do not consider spatial variation in the field.
Electrochemical Sensing
Ion Selective Electrodes
Ion Sensitive Field Effect Transistor
Optical Spectroscopy
NIR Spectroscopy
Remote sensing and aerial photography study notes. Including concept and history of RS, visual image interpretation, digital image interpretation, application of RS, digital imaging, application of remote sensing etc.
Remote Sensing: Normalized Difference Vegetation Index (NDVI)Kamlesh Kumar
The Normalized Difference Vegetation Index (NDVI) is a numerical indicator that uses the visible and near-infrared (NIR) bands of the electromagnetic spectrum to analyze whether the target (image) being observed contains green vegetation or not. Healthy vegetation (chlorophyll) reflects more near-infrared (NIR) and green light compared to other wavelengths. But it absorbs more red and blue light. This is why our eyes see vegetation as the colour green. If we could see near-infrared, then it would be strong for vegetation too.
It is basically measured through the use of Intensity, Hue and saturation of an image and through pixels as well.
The density of vegetation (NDVI) at a certain point on the image is equal to the difference in the intensities of reflected light in the red and infrared range divided by the sum of these intensities.
푁퐷푉퐼=((푁퐼푅−푅퐸퐷))/((푁퐼푅+푅퐸퐷))
The result of this formula generates a value between -1 and +1. If you have low reflectance (low values) in the red band and high reflectance in the NIR, this will yield a high NDVI value. And vice versa.
Remote Sensing and its Applications in AgricultureVikas Kashyap
Here is a presentation prepared by me on Remote sensing and its Applications in agriculture. This presentation created after studying many regarding websites, articles and research papers. Thank You
Remote Sensing Data Acquisition,Scanning/Imaging systemsdaniyal rustam
full of concepts about RS data acquisition scanning and imaging systems. Best for students of remote sensing. in this presentation we briefly explained the concept of scanning in remote sensing.
Standard Soil Testing Laboratory
time consuming, Laborious, use of chemical and reagents which effect human health and environment, costly, do not consider spatial variation in the field.
Electrochemical Sensing
Ion Selective Electrodes
Ion Sensitive Field Effect Transistor
Optical Spectroscopy
NIR Spectroscopy
Fluorescence spectroscopy is a very advanced technology that uses the phenomena of fluorescence. This presentation covers the basic concepts, instrumentation, applications, advantages and disadvantages of the technique. It also covers the Jablonski diagram. The process that analyses and measure these types of emissions is known as Fluorescence spectroscopy.Fluorescence spectroscopy is a novel technique that is used for measuring the binding of ligands to the proteins in the presence of fluorphore that bound to the ligand .
Analytical methods and instrumentation syllabusThivya Prasad
The above ppt contains the syllabus of OBT751 -Analytical Methods and Instrumentation .The above ppt is prepared based on Anna University Syllabus R2017 For more PPT contact - +919789541354
This ppt explains the basics of mass spectrometry and in application in pharmacognosy. Hope this helps you guys. Like, comment and save. If you hav problem downloading, send your email address; i'll post it for you by mail :)
Enjoy the presentation.
Remote Sensing - A tool of plant disease managementAnand Choudhary
Definition, history , type of remote sensing, plateform used in remote sensing, type of resolution used in sensor, objective of remote sensing in plant disease management
A RESEARCH ON NON COOPERATIVE HYBRID SPECTRUM SENSING TECHNIQUEIAEME Publication
The research designed in this paper is to purpose and implement a Hybrid spectrum sensing technique. As the utilization of wireless devices has been increased, there is a great demand for the radio spectrum .Cognitive Radio is a technology which can sense the spectrum to make the efficient use of resources of spectrum. Sensing of spectrum can be done by using matched filter, energy detection, waveform based detection, cyclostationary feature. Hybrid model is implemented by taking the assumptions for the distance and the SNR value, so it does not require unnecessary time for sensing of every frequency band. Results are formulated on the bases of two parameters probability of false detection and probability of correct detection. The proposed methodology has been implemented in MATLAB and the results obtained are in the form of improvement in Throughput, Energy consumption, Accuracy and improvement in Error.
The proposed model has been found efficient when compared to the other spectrum sensing techniques. It has been proved the effective improvement in throughput is by 9.9135% .Thus the results obtained are excellent and this will definitely help researcher for the future development of Cognitive Radio.
Introduction
Properties of electromagnetic radiation
The electromagnetic spectrum & its usage for spectroscopic method
UV visible spectrometry
Principle
Device and mechanism
Applications
Mass spectrometry
Parts of mass spectrometer
Theoretical example
Creating ions
IR spectrometry
Theory
Vibrational modes
Raman spectrometry
Theory
Applications
References
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
3. 16 most essential nutrients of soil. These
nutrients can be classified as:
1. The primary macronutrients: nitrogen (N),
phosphorus (P), potassium (K)
2. The secondary macronutrients: calcium (Ca),
sulfur (S), magnesium (Mg)
3. The micronutrients: boron (B), chlorine (Cl),
manganese (Mn), iron (Fe), zinc (Zn), copper
(Cu),molybdenum (Mo), nickel (Ni)
These nutrients are supplied by the soil and by
the addition of fertilizers such as manure,
compost, and fertilizer salts.
What we want to sense?
3
Ref.
Soil Sampling and analysis
Soil Nutrients
4. 4
Soil Nutrients
nutrient Symbol Peak wavelength (nm)
Nitrogen N -
Potassium K 766.491
Calcium Ca 616.217
Magnesium Mg 518.360
Phosphorus P -
Sulfur S -
Sodium Na 568.820
Iron Fe 259.940
Boron B 249.772
Manganese Mn 257.610
Zinc Zn 213.857
Copper Cu 324.754
Between(200-800)
Ref.
Determination of available nutrients in soil using the Agilent 4200 MP-AES
5. How it can be sense?
Electrochemical sensing that uses ion-
selective electrodes which generate a
voltage or current output in response
to the activity of selected ions.(i.e. ion
selective field effect transistor )
Optical sensing that uses reflectance
spectroscopy to detect the level of
energy absorbed/reflected by soil
particles and nutrient ions.
Electro chemical sensing Spectroscopy
5
Ref.
Testing/Monitoring of Soil Chemical Level Using Wireless Sensor Network Technology
Electrochemical sensors for soil nutrient detection: opportunity and challenge
By Sensing techniques for soil nutrients
6. Ref.
Soil Analysis Using Visible and Near Infrared Spectroscopy
https://www.youtube.com/watch?v=dkARLSQWHH8
6
Why Spectroscopy over Electrochemical ??
1.This is non-destructive measurement.
2. no need to take large no of soil sample.
3. Less time consuming
4. Very small amount of sample is required.
5. Cost effective in the long run.
7. https://www.youtube.com/watch?v=dkARLSQWHH8 7
What is Spectroscopy???
Spectroscopy :it is the study of interaction of
electromagnetic radiation with matter
Spectrometer: it is a tool which is use to look
indirectly at molecule.
Spectra: A plot of the color profile
(wavelength)
8. Interaction methodologies
There are two ways in which interaction between matter and radiation can take place
8https://www.youtube.com/watch?v=dkARLSQWHH8
11. Type of Spectroscopy
Spectroscopic methods are classified according to the resign of the electromagnetic
spectrum used or produced such as
11
Ref. Optical Sensing Methods for Assessment of Soil Macronutrients and other Properties for Application in Precision
Agriculture:: A review
UV region = 200-400nm
Visible range = 400-780nm
NIR = 780-2500nm
12. Method of sensing by Spectroscopy
A soil testing program can be
divided into four main
components:
1. Soil sample preparations
2. Measurement
3. Reference analysis
4. Calibration
5. Validation
6. Predictions
12
Ref. Soil Analysis Using Visible and Near Infrared Spectroscopy
13. Detailed Methodology
13
Ref.
Soil Analysis Using Visible and Near Infrared Spectroscopy
Diagnostic Nutrient Testing
1. Soil sample preparations
• Use air or oven dried soil
• Grind soil to < 2 mm particle size
2.Measurement
•Sample preparation and handling:
1.Make sure that the sample is thoroughly mixed in the sample
container .
2. Soils are heterogeneous
3. Pack the containers the same way for all samples
4. If the same container is to be used for several samples it is
important to clean it
between samples.
•White and dark reference:
1. Depending on instrument, this may be done automatically,
however for some instruments it needs to be done manually.
14. Detailed Methodology
14
3. Pre treatment of spectra
•Average spectra of repeated vis-NIR scans on the same soil sample to
avoid using false replicates.
•Transform the measured reflectance to apparent absorption through
log(1/reflectance) to enhance the linearity.
•To enhance the more chemically related peaks and reduce effects
such as baseline shifts and overall curvature, it is often recommended
to employ some additional pre-processing transformation of the
spectra
4. Reference soil analyses
• The calibration statistics can never be better than the quality of the chemical
reference analyses. That is, errors related to the traditional chemical analysis to
which the spectra are correlated will be included in the calibration model.
• Make a statistical analysis of the soil data before using it for calibration.
15. 15
Detailed Methodology
5. Calibration and validation
There are many different algorithms that can be used to calibrate soil vis–NIR
spectra to predict soil properties. They include
multiple linear regression (MLR),
principal component regression (PCR) and
Partial least squares regression (PLS)
6. Model assessment
There are several numerical measurements describing the performance of the
predictions. We recommend the use of the root mean squared error (RMSE), bias
(or mean error) and standard deviation of the error distribution (SDE) to account
for accuracy and imprecision of the predictions, and the ratio of performance to
deviation (RPD) for assessments across units:
16. Selection of Instrument depends on
16https://www.asdi.com/products-and-services/fieldspec-spectroradiometers/handheld-2-portable-spectroradiometer
What instrument to choose is largely
dependent on the application and
basically there is a trade-off between
price and performance.
•Resolution and noise
•Spectral range
•Flexibility
17. 17
References
1. “Soil Analysis Using Visible and Near Infrared Spectroscopy”, Johanna Wetterlind, Bo Stenberg Swedish, University of
Agricultural Sciences.
2. “Testing/Monitoring of Soil Chemical Level Using Wireless Sensor Network Technology”, Purvi Mishra, Sudha Mapara
Arya Institue of Engineering and Technology, Jaipur.
3. “Optical Sensing Methods for Assessment of Soil Macronutrients and other Properties for Application in Precision
Agriculture A review” , Shakuntala Laskar, Department of Electrical and Electronics Engineering, School of Technology
Assam Don Bosco University, Guwahati.
4. “Soil Sampling and analysis”, J.L. Walworth.
5. “Nutrients Detection in the Soil: Review Paper”, Ashwini A. Chitragar, Sneha M. Vasi, Sujata Naduvinamani, Akshata
J. Katigar and Taradevi I. Hulasogi,Department of Instrumentation Technology, B V Bhoomaraddi College of
Engineering and Technology, Hubli, INDIA.
6. “Near infrared Spectroscopy technology for soil nutrients detection bsaed on LS-SVM”, Yandan Qioa,central for
popularization of agriculture machinary technlogy for shanxi provinece.
7. “Electrochemical sensors for soil nutrient detection: opportunity and challenge”, ianhan Lin, Maohua Wang , Miao
Zhang, Yane Zhang, Li ChenKey Laboratory of Modern Precision Agriculture System Integration, Ministry of Education,
Beijing, China.
8. “Diagnostic Nutrient Testing”, R.S. Mylavarapu.
9. “Determination of available nutrients in soil using the Agilent 4200 MP-AES”, Dharmendra Vummiti Agilent
Technologies, India