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The document discusses developing a generic Land Management Typology (LMT) to help bridge the gap between agricultural research and farmers. An LMT would classify farming systems based on standardized agro-climatic criteria, allowing outcomes to be modeled and compared within and between locations. Combining an LMT with vegetation and soil baseline data collected using standardized methods could facilitate adaptive management and planning.
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![Andrew N Gillison Center for Biodiversity Management Queensland, Australia email: [email_address] www.cbmglobe.org ‘ Agro-bio-climatic models: Towards a generic Land Management Typology’](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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Africalterover snapp
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- The Kellogg Biological Station LTER site experiments with different cropping systems including conventional, no-till, low-input, and organic management to study how to manage crops with biology rather than chemicals while maintaining high yields.
- The professor proposes strengthening linkages between LTER sites and long-term experiments in Africa through collaborations around methods, cross-site synthesis, student exchange, and studying sustainable intensification.
GGEBiplot analysis of genotype × environment interaction in Agropyron interme...
In order to identify genotypes of Agropyron intermedium with high forage yield and stability an experiment was carried out in the Research station of Kermanshah Iran.The 11 accessions were sown in a randomized complete block design with three replications under rainfed and irrigated conditions during 2013-21-014 cropping deasons. Combined analysis of variance indicated high significant differences for location, genotype and G × E interaction (GEI) at 1% level of probability. Mean comparisons over environments introduced G4, G3 and G5 with maximum forage yield over rainfed and irrigated conditions. Minimum forage yield was attributed to genotype G1. GGEbiplot analysis exhibited that the first two principal components (PCA) resulted from GEI and genotype effect justified 99.37% of total variance in the data set. The four environments under investigation fell into two apparent groups: irrigated and rainfed. The presence of close associations among irrigated (E1 and E3) and rainfed (E2 and E4) conditions suggests that the same information about the genotypes could be obtained from fewer test environments, and hence the potential to reduce testing cost.The which-won-where pattern of GGEbiplot introduced genotypes G3 and G4 as stable with high forage yield for rainfed condition, while G5 was stable with high yield for irrigated condition. According to the comparison of the genotypes with the Ideal genotype accessions G4, G3 and G9 were more favorable than all the other genotypes. Get more articles at: http://www.innspub.net/volume-6-number-4-april-2015-jbes/
The dssat cropping system model
The document describes the new design of the DSSAT cropping system model (CSM), which incorporates crop models as modules using a single soil model. The CSM was redesigned to facilitate incorporating new scientific advances more efficiently and allow for easier replacement and addition of modules. It has a modular structure separating components along scientific lines, including a Soil module, Crop Template module to simulate different crops, Weather module, and module for competition among soil, plants and atmosphere. The redesign was intended to provide opportunities for greater scientific cooperation and application of knowledge to solve agricultural problems.
stability for grain yield in Finger millet
The document discusses stability for grain yield in finger millet. It begins by introducing the challenges plant breeders face in developing stable cultivars across environments due to genotype by environment (GxE) interactions. It then defines stability and the agronomic and biological concepts of stability. Different statistical models for analyzing stability are described, including the Additive Main effects and Multiplicative Interaction (AMMI) model. The AMMI model uses analysis of variance and principal component analysis to evaluate GxE interactions and identify stable genotypes. Biplots are used to graphically represent GxE interactions identified through AMMI analysis. Specifically, biplots allow visualization of genotypes and environments as well as patterns of GxE interactions.
Integrated LULCC modeling and impact assessment
Presentation delivered by Christine Fürst from the University of Bonn during the LSE seminar series on 30 October 2014
Benefits Over Traditional Wired Sensing Technology
This document describes the development of a prototype pest management system using a wireless sensor network to monitor environmental parameters like temperature, humidity, and leaf wetness in apple and Kutki farms. The sensor data is transmitted wirelessly to a server to alert farmers when infection risk is high so they can take preventative measures and reduce unnecessary pesticide spraying. The system aims to improve crop growth and yield by monitoring conditions and notifying farmers to spray only when needed. The wireless sensor network allows for real-time monitoring across wide farm areas compared to traditional wired systems.
Genotype x environment interaction analysis of tef grown in southern ethiopia...
This document summarizes a study that evaluated 22 tef genotypes for grain yield performance across four locations in southern Ethiopia. Significant differences were found among genotypes and locations, and for the genotype x environment interaction. Analysis of variance and AMMI modeling were used to analyze the data. The study found that genotype DZ-Cr-255 was the most stable and high-yielding variety across locations. Areka and Hossana locations showed similar patterns of interaction and had higher average yields, indicating they may be better test environments. The first principal component axis from the AMMI analysis captured 48.7% of the genotype x environment interaction variance.
11.genotype x environment interaction analysis of tef grown in southern ethio...
This document summarizes a study on genotype x environment interaction of tef varieties grown in southern Ethiopia. Twenty-two tef genotypes were evaluated across four locations over two years. Significant differences were found among genotypes and locations, and for the genotype x environment interaction. Analysis of variance and AMMI modeling revealed that the variety DZ-Cr-255 was the most stable and high-yielding across locations. The locations of Areka and Hossana showed similar interaction patterns and may represent good testing environments. The study provides information to guide tef breeding efforts in the region.
Seed Yield Stability and Genotype x Environment Interaction of Common Bean (P...
This document evaluates 15 common bean lines and one check variety across 5 environments in Ethiopia over 2 years to analyze genotype by environment interaction and identify stable, high-yielding lines. Significant genotype by environment interaction was found, with environments explaining most variation (81.06%) followed by interaction (15.73%) and genotypes (3.21%). Combined analysis of variance and AMMI modeling partitioned the interaction into two significant principal component axes explaining 39.45% and 17.38% of variation. Biplots of the results identified lines KG-71-1, KG-71-23, and KG-71-44 as both high yielding and broadly adapted. However, specific adaptation of lines was not consistent over
2015. Patrik Schnable. Trait associated SNPs provide insights into heterosis...
1) Trait-associated SNPs provide insights into the genetic basis of heterosis or hybrid vigor in maize. GWAS identified over 1,000 associations between SNPs and seven yield-related traits.
2) Including dominance effects in models explains more of the observed heterosis and genetic variation than additive effects alone. The ratio of SNPs exhibiting positive versus negative dominance is correlated with heterosis for a given trait.
3) Field-based phenotyping using sensors on robots and UAVs can study dynamic traits influenced by environment and GxE interactions, overcoming limitations of endpoint traits in controlled conditions. This will improve predictive models for plant breeding and variety recommendations.
Predictive fertilization models for potato crops using machine learning techn...
Given the influence of several factors, including weather, soils, land management, genotypes, and the severity of pests and diseases, prescribing adequate nutrient levels is difficult. A potato’s performance can be predicted using machine learning techniques in cases when there is enough data. This study aimed to develop a highly precise model for determining the optimal levels of nitrogen, phosphorus, and potassium required to achieve both high-quality and high-yield potato crops, taking into account the impact of various environmental factors such as weather, soil type, and land management practices. We used 900 field experiments from Kaggle as part of a data set. We developed, evaluated, and compared prediction models of k-nearest neighbor (KNN), linear support vector machine (SVM), naive Bayes (NB) classifier, decision tree (DT) regressor, random forest (RF) regressor, and eXtreme gradient boosting (XGBoost). We used measures such as mean average error (MAE), mean squared error (MSE), R-Squared (RS), and R 2 Root mean squared error (RMSE) to describe the model’s mistakes and prediction capacity. It turned out that the XGBoost model has the greatest R 2 , MSE and MAE values. Overall, the XGBoost model outperforms the other machine learning models. In the end, we suggested a hardware implementation to help farmers in the field.
Prediction of soil urea content using rf spectroscopy and partial least squar...
This document summarizes a study that used radio frequency (RF) spectroscopy and partial least squares regression (PLSR) to predict soil urea content. 20 soil samples with varying concentrations of nutrients including urea were analyzed using an RF spectrometer. 16 samples were used to calibrate a PLSR model and the remaining 4 samples were used to validate the model's predictions of urea content. The PLSR model achieved an R2 value of 0.987 and prediction errors ranging from 0.49% to 2.78% for the validation samples, indicating RF spectroscopy combined with PLSR can accurately predict soil urea content. The study demonstrated the potential of this approach for analyzing soil nutrients but was limited to laboratory-
Class ProjectMapping of Cr.docx
This document describes a class project that aims to map crop residues using hyperspectral data. It will generate estimates of crop residue cover and amount in agricultural fields in Central Indiana using Landsat 7 ETM+, EO-1 ALI, and EO-1 Hyperion data from April 12, 2003. Methods will include pre-processing the hyperspectral data through de-striping and atmospheric corrections, then calculating indices like the Cellulose Absorption Index to classify crop residues and differentiate tillage systems. The results will provide information on quantifying and mapping crop residues using remote sensing techniques.
No-Till Effect On Soil Erosion In Mid-Slope Cropping Through Soil Aggregates ...
Mr. Iaaich Hamza, National Institute of Agricultural Research (INRA), Morocco. Global Symposium on Soil Erosion (GSER19), 15 - 17 May 2019 at FAO HQ.
Genotype by environment interaction and stability of extra-early maize hybrid...
Maize (Zea mays L.) is the most important cereal crop produced in Ghana. However the change in environmental conditions, the expansion of maize to new agro-ecologies coupled with inadequate maize varieties available for the different environments affects yield improvement programmes in Ghana. Hence, the study is to investigate the influence of genotype by environment interaction on the maize hybrids and to identify stable and high yielding hybrids with superior agronomic for famers use in the country. The objectives of the study was to investigate the influence of genotype by environment interaction on the maize hybrids and to identify stable and high yielding hybrids with superior agronomic performance for famers use in Ghana. Thus, fifteen extra-early maize hybrids and three locally released checks were evaluated in a randomized complete block design with three replications in two locations in Ghana. The experiment was carried out at KNUST and Akomadan which represent the forest and forest transition zones of Ghana. Nine of the hybrids out of the fifteen hybrids evaluated produce above the average yield and the effect of genotype, location and genotype by location interaction was significant for grain yield. The GGE biplot used in this study revealed that TZEEI-1 x TZEEI-21, TZEEI-6 x TZEEI-21, TZEEI-15 x TZEEI-1 and TZEEI-29 x TZEEI-21 were high yielding and stable hybrids because they were closer to the ideal. The GGE biplot also identified Akomadan as the most ideal testing environment for these hybrids under irrigation.
Gismap_AEZ_Methodology
GISMAP developed tools to apply land evaluation methods to assess food production potential. Their approach combines global agro-ecological zoning (GAEZ) and land suitability analysis (LSA) to leverage their respective strengths. For a case study in Iraq, they integrated climate, soil, topography and other data to model potential yields and suitability ratings for major crops at a high resolution. Their workflow uses matching tables to rate environmental parameters for each crop and estimate yield reductions, outputting suitability maps to inform land use planning.
Whole genome sequencing of Napier grass (C. purpureus) accessions from sub-Sa...
Presented by Abel Teshome (PhD) at the ILRI Forage Diversity Seminar Series, Addis Ababa, 2 December 2021
Functional markers2005
This document presents a proposed "systemic strategy" to more efficiently identify functional marker candidates for abiotic stress tolerance in plants. The strategy aims to strengthen interdisciplinary efforts between plant breeding, plant nutrition, and molecular biology. It involves using ecophysiological modeling and genetic analyses to identify robust physiological parameters for important agronomic traits. Target tissues and cells critical for those parameters would then be studied at the molecular level to characterize stress-induced reprogramming. Both "top-down" whole plant approaches and "bottom-up" molecular approaches would be combined to benefit functional marker-assisted breeding for quantitative traits like stress tolerance. Research on the role of root hairs in phosphate efficiency is highlighted as one area that has made progress in this
Phylogeny of Bacterial and Archaeal Genomes Using Conserved Genes: Supertrees...
Lang JM, Darling AE, Eisen JA (2013) Phylogeny of Bacterial and Archaeal Genomes Using Conserved Genes: Supertrees and Supermatrices. PLoS ONE 8(4): e62510. doi:10.1371/journal.pone.0062510
Ijet v5 i6p16
This document summarizes a research paper that proposes a system to analyze crop phenology (growth stages) using IoT to support parallel agriculture management. The system would use sensors to collect data on soil moisture, temperature, humidity and other parameters. This data would be input to a database. Then, a multiple linear regression model trained on past data would predict the optimal crop and expected yield based on the tested sensor data and parameters. This system aims to help farmers select crops and fertilization practices tailored to their specific fields' conditions.
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GGEBiplot analysis of genotype × environment interaction in Agropyron interme...
GGEBiplot analysis of genotype × environment interaction in Agropyron interme...
Benefits Over Traditional Wired Sensing Technology
Benefits Over Traditional Wired Sensing Technology
Genotype x environment interaction analysis of tef grown in southern ethiopia...
Genotype x environment interaction analysis of tef grown in southern ethiopia...
11.genotype x environment interaction analysis of tef grown in southern ethio...
11.genotype x environment interaction analysis of tef grown in southern ethio...
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Seed Yield Stability and Genotype x Environment Interaction of Common Bean (P...
2015. Patrik Schnable. Trait associated SNPs provide insights into heterosis...
2015. Patrik Schnable. Trait associated SNPs provide insights into heterosis...
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No-Till Effect On Soil Erosion In Mid-Slope Cropping Through Soil Aggregates ...
No-Till Effect On Soil Erosion In Mid-Slope Cropping Through Soil Aggregates ...
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Genotype by environment interaction and stability of extra-early maize hybrid...
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Whole genome sequencing of Napier grass (C. purpureus) accessions from sub-Sa...
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Constraints And Opportunities To Agric Development In Kenya
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The document discusses the costs of land degradation in Ethiopia. It identifies the major on-site costs as the loss of agricultural production due to soil erosion and loss of nutrients from removing crop residues. The major off-site costs are siltation of dams and reservoirs and gravel deposition downstream. It proposes using the replacement cost approach and change in productivity approach to estimate these costs, and developing a decision matrix to prioritize conservation efforts based on erosion rates and economic returns.
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This document outlines an economic analysis framework for targeting sustainable land management (SLM) interventions. It defines key terms like land degradation, outlines immediate causes of degradation like exploitative farming and deforestation, and describes approaches to estimate the costs of degradation and benefits of SLM. These economic approaches, like the change in productivity approach and replacement cost approach, could be used with Ethiopian data to prioritize SLM interventions for greatest impact.
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Brief On Sustainable Agriculture Precious Final
Sustainable agriculture aims to address issues with conventional agriculture like persistent poverty, hunger, and environmental damage. It involves practices that integrate soil, crop, and livestock production while reducing external inputs and emphasizing techniques adapted to local conditions. Studies show organic and sustainable systems in developing countries can produce higher yields than conventional farms and meet global food demand. However, adoption of sustainable practices remains low due to constraints like lack of information, biomass availability, and unsupportive policies. Recommendations include tailored approaches, market support, institutional strengthening, and research to further understanding and address myths about sustainable agriculture.
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The document discusses how markets, institutions, and policies influence smallholder investment in sustainable land management (SLM) in Africa. It argues that SLM adoption has been low due to a lack of profitable SLM options, high opportunity costs of labor, and weak property rights, markets, and institutions. Markets can promote SLM by facilitating access to new technologies and inputs, but are not sufficient on their own without well-defined property rights and coordinated policies to reduce tradeoffs from intensification and support diversification. Payment for ecosystem services and targeted subsidies may also incentivize SLM when costs are less than social benefits. Overall, the document emphasizes that improved market access, policies, and institutional arrangements are needed to encourage more small
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The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
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Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
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Gothenburg Pres Ag
- 1. UN expert group meeting on “ Sustainable land management and agricultural practices in Africa: Bridging the gap between research and farmers” April 16 – 17, 2009, University of Gothenburg, Sweden .
- 2. Andrew N Gillison Center for Biodiversity Management Queensland, Australia email: [email_address] www.cbmglobe.org ‘ Agro-bio-climatic models: Towards a generic Land Management Typology’
- 9. Farming system Dendrogram based on similarity matrix derived from the LMT grammar UNDESA, EFD Mtg Gothenburg Univ. 16-17 April 2009
- 10. Multidimensional scaling of best two axes from similarity matrix derived from LMT grammar. Shows interpretable clustering of LMTs and provides a basis for quantitative comparison within and between types. Vector 2 Vector 1
- 11. Single axis solution score (MDS) of LMT relationship with plant species diversity (richness per 200m 2 transect) UNDESA, EFD Mtg Gothenburg Univ. 16-17 April 2009
- 13. VegClass , Public domain, user-friendly software for data entry and meta-analysis; integrated with field proforma to support rapid vegetation survey
- 14. Sample page from VegClass showing PFT and species listings UNDESA, EFD Mtg Gothenburg Univ. 16-17 April 2009
- 15. Plant Functional Type ( me-pe-do-ct-ph ) Plant Functional Elements Adaptive PFTs are constructed from 36 generic PFEs according to a specific rule set. This system can be applied to all terrestrial vegetation Example of PFE combination me = me sophyll leaf size class pe = pe ndulous leaf inclination do = do rsiventral leaf ct = green c or t ex (photosynthetic stem) ph = ph anerophyte (perennial woody plant > 2m tall) Combining functional traits to describe a single plant individual (VegClass grammar)) UNDESA, EFD Mtg Gothenburg Univ. 16-17 April 2009
- 16. High (SFG8.9) Medium (SFG5.6) Low (SFG1.0) Biodiversity and vegetation structure can be readily used to estimate soil fertility in the lower Zambezi basin, Mozambique – Potential linkages here with LMT grammar Potential agric. productivity R 2 0.677 P< 0.001 Rapid baseline VegClass survey using 200m 2 transects World Bank/GEF case study 2006 UNDESA, EFD Mtg Gothenburg Univ. 16-17 April 2009
- 17. Soil fertility can be linked with biodiversity, LMT and remote sensing Fertility high Low Lower Zambezi valley Ocean Zambezi R . Chire R. Soil fertility predicted from biodiversity and coupled with remote sensing can be mapped at 30m grid resolution and readily ground-tested
- 18. Cell at 17.262S, 34.999E elevn 34m Transect # 14 (40x5m) maize, rice Information on soil fertility, plant biodiversity, remotely sensed and other site values can be extracted from spatially-referenced data layers (also LMT) UNDESA, EFD Mtg Gothenburg Univ. 16-17 April 2009 LMT: fc ha pl ar mg ud rf nl or lo gr fr fz 0.2 Litter depth (cm) 1 Basal area (m 2 ha -1 ) 5 Mean canopy height (m) 116 Plant functional complexity 16 Plant functional type richness 19 Plant species richness 8.6 Soil fertility index 93 Bare ground reflectance 266 Non-photosyn. reflectance 605 Photosynthetic reflectance Value Attribute