Plant stresses have been monitored using the imaging or spectrometry of plant leaves in the
visible (red-green-blue or RGB), near-infrared (NIR), infrared (IR), and ultraviolet (UV) …

Rice is one of the most extensively cultivated food crops on the planet, especially in
Bangladesh, China, and India. However, rice production is frequently hampered by nutrient …

Symptoms of nutrient deficiencies in rice plants often appear on the leaves. The leaf color
and shape, therefore, can be used to diagnose nutrient deficiencies in rice. Image …

Early diagnosis of nutrient deficiencies can play a major role in avoiding significant
agricultural losses and increasing the final yield while preserving the environment through …

Recent research on the application of remote sensing and deep learning‐based analysis in
precision agriculture demonstrated a potential for improved crop management and reduced …

Macronutrient deficiency inhibits the growth and development of chili plants. One of the non-
destructive methods that plays a role in processing plant image data based on specific …

A compelling effort has been made in recent years to face several kinds of plant stresses
using a variety of sensors and deep learning methods. Yet most of the datasets are based …

Nutrient contents are important for plants. Lack of macronutrients causes plant damage.
Several macronutrient deficiencies exhibit similar visual characteristics that are difficult for …

This paper investigates the use of various deep convolutional neural networks (CNNs) with
transfer learning to identify nutrient deficiencies from a leaf image. Experiments were …

Recent years have seen an increased effort in the detection of plant stresses and diseases
using non-invasive sensors and deep learning methods. Nonetheless, no studies have been …