Intelligent Detection and Classification of External Traits in Crop Plants, Fruits, and Vegetables

Dear Colleagues,

A technological revolution is currently taking place in agriculture, termed 'Agriculture 4.0'. Modern, intelligent solutions are being introduced, mainly based on the digitalization of production processes and the classification and qualitative assessment of agricultural crops, fruit, and vegetables. The basis of these intelligent solutions is artificial intelligence (AI), which allows for the modeling, simulation, and prediction of complex agricultural processes, especially in the case of complex relationships between variables related to weather and agrotechnical conditions. Intelligent solutions are extremely helpful for extracting quality characteristics of agricultural products based on shape, color, texture, and light spectrum. Digital techniques and methods provide new knowledge that can be applied to control the quality of food and agricultural products with high accuracy. Texture, shape, and color characteristics of agricultural products are used to detect damaged apple or orange areas, weeds, and pests. Computer image analysis has become one of the main techniques used in agriculture to assess seeds and grains in terms of quality losses, quantifying their degree of mechanical damage, maturity stage, disease infestation, or contamination with other plant species.

In this Special Issue, we aim to exchange knowledge on precision agriculture, the use of computer systems in agricultural production, the application of artificial neural networks and image analysis for qualitative and quantitative classification of field crops, vegetables, and fruit, and the use of genetic algorithms to manage machinery and evaluate its efficiency.

Dr. Baohua Zhang
Dr. Yuxing Han
Prof. Dr. Piotr Rybacki
Prof. Dr. Janetta Niemann
Guest Editors

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