[HTML][HTML] The digitization of agricultural industry–a systematic literature review on agriculture 4.0
Agriculture is considered one of the most important sectors that play a strategic role in
ensuring food security. However, with the increasing world's population, agri-food demands …
ensuring food security. However, with the increasing world's population, agri-food demands …
Machine learning in agriculture: A comprehensive updated review
The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …
artificial intelligent systems for the sake of making value from the ever-increasing data …
Machine learning applications for precision agriculture: A comprehensive review
Agriculture plays a vital role in the economic growth of any country. With the increase of
population, frequent changes in climatic conditions and limited resources, it becomes a …
population, frequent changes in climatic conditions and limited resources, it becomes a …
Soybean yield prediction from UAV using multimodal data fusion and deep learning
Preharvest crop yield prediction is critical for grain policy making and food security. Early
estimation of yield at field or plot scale also contributes to high-throughput plant phenoty** …
estimation of yield at field or plot scale also contributes to high-throughput plant phenoty** …
Application of machine learning algorithms in plant breeding: predicting yield from hyperspectral reflectance in soybean
Recent substantial advances in high-throughput field phenoty** have provided plant
breeders with affordable and efficient tools for evaluating a large number of genotypes for …
breeders with affordable and efficient tools for evaluating a large number of genotypes for …
Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods
Closing the yield gap between actual and potential wheat yields in Australia is important to
meet the growing global demand for food. The identification of hotspots of the yield gap …
meet the growing global demand for food. The identification of hotspots of the yield gap …
Prediction of winter wheat yield based on multi-source data and machine learning in China
Wheat is one of the main crops in China, and crop yield prediction is important for regional
trade and national food security. There are increasing concerns with respect to how to …
trade and national food security. There are increasing concerns with respect to how to …
Alfalfa yield prediction using UAV-based hyperspectral imagery and ensemble learning
Alfalfa is a valuable and intensively produced forage crop in the United States, and the
timely estimation of its yield can inform precision management decisions. However …
timely estimation of its yield can inform precision management decisions. However …
Recognition of bloom/yield in crop images using deep learning models for smart agriculture: A review
Precision agriculture is a crucial way to achieve greater yields by utilizing the natural
deposits in a diverse environment. The yield of a crop may vary from year to year depending …
deposits in a diverse environment. The yield of a crop may vary from year to year depending …
Field-scale crop yield prediction using multi-temporal WorldView-3 and PlanetScope satellite data and deep learning
Agricultural management at field-scale is critical for improving yield to address global food
security, as providing enough food for the world's growing population has become a wicked …
security, as providing enough food for the world's growing population has become a wicked …