Fruit growing is important in the global agricultural economy, contributing significantly to
food security, job creation, and rural development. With the advancement of technologies …

The fine-scale spatial heterogeneity of low-growth Arctic tundra landscapes necessitates the
use of high-spatial-resolution remote sensing data for accurate detection of vegetation …

In this study, we explore spectral heterogeneity within plant canopies, a characteristic often
observed in stressed plants where certain leaves or intra-leaf regions exhibit stress …

As a pivotal role in crop development, the application of nitrogen fertilizers enhances yields,
while excessive use poses environmental risks. Precision nitrogen management requires …

Leaf chlorophyll content (LCC) and leaf area index (LAI) are crucial for rice growth and
development, serving as key parameters for assessing nutritional status, growth, water …

Potatoes are a vital part of our diet worldwide, but their cultivation poses challenges due to
environmental impacts from traditional farming methods. Precision agriculture offers a …

Leaf nitrogen content (LNC) is a crucial indicator for assessing the nitrogen status of forest
trees. The LNC retrieval can be achieved with the inversion of the PROSPECT-PRO model …

Various nitrogen (N) prediction approaches were tested using aerial hyperspectral imagery
and ground truth data (leaf tissue analysis) collected from a table grape vineyard in Shafter …

This paper presents an innovative method for predicting grape yield using a modified deep
convolutional neural network (M− DCNN). This approach integrates advanced image …

With the rapid development of Internet of Things (IOT), big data analysis, artificial
intelligence and other technologies, precision agriculture is receiving more and more …