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Srinivasagan N. Subhashree, C. Igathinathane, Adnan Akyuz, Md. Borhan, John Hendrickson, David Archer, Mark Liebig, David Toledo, Kevin Sedivec, Scott Kronberg and Jonathan Halvorson
Farmers and ranchers depend on annual forage production for grassland livestock enterprises. Many regression and machine learning (ML) prediction models have been developed to understand the seasonal variability in grass and forage production, improve ma...
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Francisco Javier López-Escudero, Joaquín Romero, Rocío Bocanegra-Caro and Antonio Santos-Rufo
Developing models to understand disease dynamics and predict the risk of disease outbreaks to facilitate decision making is an integral component of plant disease management. However, these models have not yet been developed for one of the most damaging ...
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Tajamul Hussain, Hero T. Gollany, David J. Mulla, Zhao Ben, Muhammad Tahir, Syed Tahir Ata-Ul-Karim, Ke Liu, Saliha Maqbool, Nurda Hussain and Saowapa Duangpan
A suitable nitrogen (N) application rate (NAR) and ideal planting period could improve upland rice productivity, enhance the soil water utilization, and reduce N losses. This study was conducted for the assessment and application of the EPIC model to sim...
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Eli Argaman and Ilan Stavi
Water loss through surface runoff is a significant constraint for rainfed agricultural lands across the Mediterranean region. Using straw-mulch cover (SMC) as a runoff mitigator has been successfully utilized to negate the impact of raindrop splashing. H...
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Guanfang Sun, Yan Zhu, Zhaoliang Gao, Jinzhong Yang, Zhongyi Qu, Wei Mao and Jingwei Wu
Soil salinization is a major eco-environmental problem in irrigated agro-ecosystems. Understanding regional soil salinity spatial patterns and seasonal dynamics and their driving factors under changing environments is beneficial to managing soil salinity...
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