Computer vision (CV) combined with a deep convolutional neural network (CNN) has
emerged as a reliable analytical method to effectively characterize and quantify high …

Optical sensors and sensing-based phenotyping techniques have become mainstream
approaches in high-throughput phenotyping for improving trait selection and genetic gains …

In recent years, the agricultural sector has turned to robotic automation to deal with the
growing demand for food. Harvesting fruits and vegetables is the most labor-intensive and …

Crop leaf area index (LAI) is one of the important indicators to evaluate crop growth and
guide field management, and can be used to predict crop yield. Spectral and thermal …

Wheat is an important staple crop in the global food chain. The production of wheat in many
regions is constrained by the lack of use of advanced technologies for wheat monitoring …

Agricultural water accounts for more than 70% of the total global water usage, and the
scarcity of global freshwater resources will largely limit global agricultural production …

Deficit irrigation is a common approach in water-scarce regions to balance productivity and
water use, whereas drought stress still occurs to various extents, leading to reduced …

Sodic soils adversely affect crop production over extensive areas of rain-fed cropping
worldwide, with particularly large areas in Australia. Crop phenotyping may assist in …

Demand for food and other agricultural products is projected to increase by 50% globally by
2050. This increasing food demand places growing pressure on agricultural production at a …

Accurate estimation of soil moisture content (SMC) is essential for optimizing irrigation
schedules and identifying drought-tolerant varieties. The integration of unmanned aerial …