Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics

Xu Wang Sandesh Kumar Shrestha Philomin Juliana Suchismita Mondal Francisco Pinto Govindan Velu Leonardo Abdiel Crespo Herrera JULIO HUERTA_ESPINO Ravi Singh Jesse Poland (2023, [Artículo])

New Crop Varieties Plant Breeding Programs Yield Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA LEARNING GRAIN YIELDS WHEAT BREEDING FOOD SECURITY

Smallholder maize yield estimation using satellite data and machine learning in Ethiopia

Zhe Guo Jordan Chamberlin Liangzhi You (2023, [Artículo])

The lack of timely, high-resolution data on agricultural production is a major challenge in developing countries where such information can guide the allocation of scarce resources for food security, agricultural investment, and other objectives. While much research has suggested that remote sensing can potentially help address these gaps, few studies have indicated the immediate potential for large-scale estimations over both time and space. In this study we described a machine learning approach to estimate smallholder maize yield in Ethiopia, using well-measured and broadly distributed ground truth data and freely available spatiotemporal covariates from remote sensing. A neural networks model outperformed other algorithms in our study. Importantly, our work indicates that a model developed and calibrated on a previous year's data could be used to reasonably estimate maize yield in the subsequent year. Our study suggests the feasibility of developing national programs for the routine generation of broad-scale and high-resolution estimates of smallholder maize yield, including seasonal forecasts, on the basis of machine learning algorithms, well-measured ground control data, and currently existing time series satellite data.

Sentinel-2 Smallholder Agriculture Yield Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA INTENSIFICATION SMALLHOLDERS AGRICULTURE YIELD FORECASTING

Genetic improvement of global wheat, including progress for enhancing insect resistance

Leonardo Abdiel Crespo Herrera (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETIC IMPROVEMENT WHEAT BREEDING CLIMATE CHANGE DISEASE RESISTANCE YIELDS

Wheat yield estimation from UAV platform based on multi-modal remote sensing data fusion

Urs Schulthess Azam Lashkari (2022, [Artículo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RELIEF UNMANNED AERIAL VEHICLES WINTER WHEAT YIELDS

REMATTOOL-R: a smart tool for identifying superior maize genotypes from multi-environment yield trials

Lewis Machida Dan Makumbi (2023, [Artículo])

Maize Variety Testing Multienvironment Trial Analysis Relative Maturity REMATTOOL-R Superior Varieties Identification CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE VARIETIES MATURITY IDENTIFICATION YIELDS

Balancing quality with quantity: a case study of UK bread wheat

Nick Fradgley Keith Gardner Stéphanie M. Swarbreck Alison Bentley (2023, [Artículo])

Grain Protein Content Environmental Sustainability End-Use Quality Modern Bread Baking Methods CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GRAIN PROTEIN CONTENT HISTORY QUALITY WHEAT YIELDS

Agroecology can promote climate change adaptation outcomes without compromising yield in smallholder systems

Sieglinde Snapp Yodit Kebede Eva Wollenberg (2023, [Artículo])

A critical question is whether agroecology can promote climate change mitigation and adaptation outcomes without compromising food security. We assessed the outcomes of smallholder agricultural systems and practices in low- and middle-income countries (LMICs) against 35 mitigation, adaptation, and yield indicators by reviewing 50 articles with 77 cases of agroecological treatments relative to a baseline of conventional practices. Crop yields were higher for 63% of cases reporting yields. Crop diversity, income diversity, net income, reduced income variability, nutrient regulation, and reduced pest infestation, indicators of adaptative capacity, were associated with 70% or more of cases. Limited information on climate change mitigation, such as greenhouse gas emissions and carbon sequestration impacts, was available. Overall, the evidence indicates that use of organic nutrient sources, diversifying systems with legumes and integrated pest management lead to climate change adaptation in multiple contexts. Landscape mosaics, biological control (e.g., enhancement of beneficial organisms) and field sanitation measures do not yet have sufficient evidence based on this review. Widespread adoption of agroecological practices and system transformations shows promise to contribute to climate change services and food security in LMICs. Gaps in adaptation and mitigation strategies and areas for policy and research interventions are finally discussed.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE CROPS FOOD SUPPLY GAS EMISSIONS GREENHOUSE GASES FARMING SYSTEMS AGROECOLOGY FOOD SECURITY LESS FAVOURED AREAS SMALLHOLDERS YIELDS NUTRIENTS BIOLOGICAL PEST CONTROL CARBON SEQUESTRATION LEGUMES

Closing the yield gap of soybean (Glycine max (L.) Merril) in Southern Africa: a case of Malawi, Zambia, and Mozambique

Siyabusa Mkuhlani Isaiah Nyagumbo (2023, [Artículo])

Introduction: Smallholder farmers in Sub-Saharan Africa (SSA) are increasingly producing soybean for food, feed, cash, and soil fertility improvement. Yet, the difference between the smallholder farmers’ yield and either the attainable in research fields or the potential from crop models is wide. Reasons for the yield gap include low to nonapplication of appropriate fertilizers and inoculants, late planting, low plant populations, recycling seeds, etc. Methods: Here, we reviewed the literature on the yield gap and the technologies for narrowing it and modelled yields through the right sowing dates and suitable high-yielding varieties in APSIM. Results and Discussion: Results highlighted that between 2010 and 2020 in SSA, soybean production increased; however, it was through an expansion in the cropped area rather than a yield increase per hectare. Also, the actual smallholder farmers’ yield was 3.8, 2.2, and 2.3 times lower than the attainable yield in Malawi, Zambia, and Mozambique, respectively. Through inoculants, soybean yield increased by 23.8%. Coupling this with either 40 kg ha−1 of P or 60 kg ha−1 of K boosted the yields by 89.1% and 26.0%, respectively. Overall, application of 21–30 kg ha-1 of P to soybean in SSA could increase yields by about 48.2%. Furthermore, sowing at the right time increased soybean yield by 300%. Although these technologies enhance soybean yields, they are not fully embraced by smallholder farmers. Hence, refining and bundling them in a digital advisory tool will enhance the availability of the correct information to smallholder farmers at the right time and improve soybean yields per unit area.

Decision Support Tools Digital Tools Site-Specific Recommendations CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DECISION SUPPORT SYSTEMS LEGUMES YIELDS SOYBEANS

International Winter Wheat nurseries data: Facultative and Winter Wheat Observation Nurseries and International Winter Wheat yield trials for semi-arid and irrigated conditions

Mesut KESER fatih ozdemir Pietro Bartolini (2022, [Artículo])

Germplasm Exchange International Nurseries Multi-Locations CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WINTER WHEAT BREEDING GERMPLASM YIELDS DATA

Emmer wheat eco-geographic and genomic congruence shapes phenotypic performance under mediterranean climate

Dana Fuerst SHAILESH YADAV Rajib Roychowdhury Carolina Sansaloni Sariel Hübner (2022, [Artículo])

Emmer Wheat CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT GENETIC VARIATION CLIMATE PHENOLOGY YIELDS MEDITERRANEAN CLIMATE