A global perspective on sustainable intensification research

KG Cassman, P Grassini - Nature Sustainability, 2020 - nature.com
Despite general agreement that meeting food demand without further loss of natural
ecosystems requires sustainable intensification, there is little dialogue about the research …

[HTML][HTML] The concepts and quantification of yield gap using boundary lines. A review

C Miti, AE Milne, KE Giller, RM Lark - Field Crops Research, 2024 - Elsevier
Context The potential yield of crops is not usually realised on farms creating yield gaps.
Methods are needed to diagnose yield gaps and to select interventions. One method is the …

Adopting yield-improving practices to meet maize demand in Sub-Saharan Africa without cropland expansion

F Aramburu-Merlos, FAM Tenorio… - Nature …, 2024 - nature.com
Abstract Maize demand in Sub-Saharan Africa is expected to increase 2.3 times during the
next 30 years driven by demographic and dietary changes. Over the past two decades, the …

Soybean [Glycine max (L.) Merr.] Breeding: History, Improvement, Production and Future Opportunities

EJ Anderson, ML Ali, WD Beavis, P Chen… - Advances in plant …, 2019 - Springer
Abstract Soybean, Glycine max (L.) Merr., has been grown as a forage and as an important
protein and oil crop for thousands of years. Domestication, breeding improvements and …

Agronomic practices for reducing wheat yield gaps: a quantitative appraisal of progressive producers

RP Lollato, DA Ruiz Diaz, E DeWolf, M Knapp… - Crop …, 2019 - Wiley Online Library
There is limited information on agronomic practices affecting wheat (Triticum aestivum L.)
yield in intensively managed dryland systems despite the opportunity to narrow the existing …

[HTML][HTML] Delineation of management zones in agricultural fields using cover–crop biomass estimates from PlanetScope data

FM Breunig, LS Galvão, R Dalagnol, CE Dauve… - International Journal of …, 2020 - Elsevier
Several methods have been proposed to delineate management zones in agricultural fields,
which can guide interventions of the farmers to increase crop yield. In this study, we propose …

[HTML][HTML] Interpretable machine learning methods to explain on-farm yield variability of high productivity wheat in Northwest India

HS Nayak, JV Silva, CM Parihar, TJ Krupnik… - Field Crops …, 2022 - Elsevier
The increasing availability of complex, geo-referenced on-farm data demands analytical
frameworks that can guide crop management recommendations. Recent developments in …

[HTML][HTML] Agronomy explains large yield gaps in smallholder oil palm fields

JP Monzon, YL Lim, FA Tenorio, R Farrasati… - Agricultural …, 2023 - Elsevier
CONTEXT Palm oil production is a major source of income for millions of smallholders in
Indonesia. However, actual yield remains low in relation to the attainable yield. While …

[HTML][HTML] Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

JV Silva, J van Heerwaarden, P Reidsma… - Field Crops …, 2023 - Elsevier
Context Collection and analysis of large volumes of on-farm production data are widely seen
as key to understanding yield variability among farmers and improving resource-use …

On-farm data-rich analysis explains yield and quantifies yield gaps of winter wheat in the US central Great Plains

BR Jaenisch, LB Munaro, LM Bastos, M Moraes… - Field Crops …, 2021 - Elsevier
With an annual production of∼ 60 Mt, the US accounts for about 8% of the global wheat
(Triticum aestivum L.) production. Still, quantification of the yield gaps (YG) and major …