UAV-based multi-sensor data fusion and machine learning algorithm for yield prediction in wheat [0.03%]
基于无人机多传感器数据融合和机器学习算法的小麦预测产量研究
Shuaipeng Fei,Muhammad Adeel Hassan,Yonggui Xiao et al.
Shuaipeng Fei et al.
Early prediction of grain yield helps scientists to make better breeding decisions for wheat. Use of machine learning (ML) methods for fusion of unmanned aerial vehicle (UAV)-based multi-sensor data can improve the prediction accuracy of cr...
A loss function to evaluate agricultural decision-making under uncertainty: a case study of soil spectroscopy [0.03%]
一种评估不确定性下农业决策的损失函数：土壤光谱法案例研究
T S Breure,S M Haefele,J A Hannam et al.
T S Breure et al.
Modern sensor technologies can provide detailed information about soil variation which allows for more precise application of fertiliser to minimise environmental harm imposed by agriculture. However, growers should lose neither income nor ...
Assessing expected utility and profitability to support decision-making for disease control strategies in ornamental heather production [0.03%]
评估预期效用和盈利能力以支持决策制定，助力疾病控制策略在观赏石竹生产中的实施
Marius Ruett,Tobias Dalhaus,Cory Whitney et al.
Marius Ruett et al.
Many farmers hesitate to adopt new management strategies with actual or perceived risks and uncertainties. Especially in ornamental plant production, farmers often stick to current production strategies to avoid the risk of economically har...
The adoption of precision agriculture enabling technologies in Swiss outdoor vegetable production: a Delphi study [0.03%]
精准农业使能技术在瑞士室外蔬菜生产中应用的德尔菲研究
Jeanine Ammann,Christina Umstätter,Nadja El Benni
Jeanine Ammann
Digital technologies are a promising means to tackle the increasing global challenges (e.g., climate change, water pollution, soil degradation) and revolutionising agricultural production. The current research used a two-stage Delphi study ...
Subfield crop yields and temporal stability in thousands of US Midwest fields [0.03%]
美国 Midwest 地区数千个农田的子区域作物产量和时间稳定性
Bernardo Maestrini,Bruno Basso
Bernardo Maestrini
Understanding subfield crop yields and temporal stability is critical to better manage crops. Several algorithms have proposed to study within-field temporal variability but they were mostly limited to few fields. In this study, a large dat...
James Lowenberg-DeBoer,Kit Franklin,Karl Behrendt et al.
James Lowenberg-DeBoer et al.
By collecting more data at a higher resolution and by creating the capacity to implement detailed crop management, autonomous crop equipment has the potential to revolutionise precision agriculture (PA), but unless farmers find autonomous e...
Predicting the growth of lettuce from soil infrared reflectance spectra: the potential for crop management [0.03%]
基于土壤红外光谱的生菜生长预测及其潜在应用价值
T S Breure,A E Milne,R Webster et al.
T S Breure et al.
How well could one predict the growth of a leafy crop from reflectance spectra from the soil and how might a grower manage the crop in the light of those predictions? Topsoil from two fields was sampled and analysed for various nutrients, p...