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Wenji Yang and Xiaoying Qiu
The damage caused by pests to crops results in reduced crop yield and compromised quality. Accurate and timely pest detection plays a crucial role in helping farmers to defend against and control pests. In this paper, a novel crop pest detection model na...
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Andrew Wilkinson, John N. Wilkinson, Peter Shotton, Enas Khalid Sufar, Gultekin Hasanaliyeva, Nikolaos Volakakis, Ismail Cakmak, Levent Ozturk, Paul Bilsborrow, Per Ole Iversen, Steve Wilcockson, Leonidas Rempelos and Carlo Leifert
Organic wheat production systems have lower yields compared with intensive conventional production and often do not achieve the grain protein content and quality thresholds set by millers and bakers. In contrast, organic production methods were reported ...
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Jaroslaw Kurek, Gniewko Niedbala, Tomasz Wojciechowski, Bartosz Swiderski, Izabella Antoniuk, Magdalena Piekutowska, Michal Kruk and Krzysztof Bobran
This research delves into the application of machine learning methods for predicting the yield of potato varieties used for French fries in Poland. By integrating a comprehensive dataset comprising agronomical, climatic, soil, and satellite-based vegetat...
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John Byabazaire, Gregory M. P. O?Hare, Rem Collier, Chamil Kulatunga and Declan Delaney
Smart agriculture relies on accurate yield maps as a crucial tool for decision-making. Many yield maps, however, suffer from spatial errors that can compromise the quality of their data, while several approaches have been proposed to address some of thes...
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Boyu Xie, Qi Su, Beilun Tang, Yan Li, Zhengwu Yang, Jiaoyang Wang, Chenxi Wang, Jingxian Lin and Lin Li
With the advancement in modern agricultural technologies, ensuring crop health and enhancing yield have become paramount. This study aims to address potential shortcomings in the existing chili disease detection methods, particularly the absence of optim...
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