Timely and accurate detection of diseases plays a significant role in attaining optimal
growing conditions of olive crops. This study evaluated the use of two machine learning …

Olives are an essential crop for Greece and constitute a major economic and agricultural
factor. Diseases, pests, and environmental conditions are all factors that can deteriorate the …

Abstract Background Wild rocket (Diplotaxis tenuifolia) is prone to soil-borne stresses under
intensive cultivation systems devoted to ready-to-eat salad chain, increasing needs for …

Crop diseases have a significant impact on plant growth and can lead to reduced yields.
Traditional methods of disease detection rely on the expertise of plant protection experts …

The detection of water stress in vineyards plays an integral role in the sustainability of high-
quality grapes and prevention of devastating crop loses. Hyperspectral remote sensing …

Recently, there has been a significant increase in the use of proximal or remote
hyperspectral imaging systems to study plant properties, types, and conditions. Numerous …

Hyperspectral images can be used to uncover physiological processes in plants if
interpreted properly. Machine Learning methods such as Support Vector Machines (SVM) …

Non-invasive techniques for the detection of apple fruit damages are central to the correct
operation of sorting lines ensuring storability of the collected fruit batches. The choice of …

Machine Learning (ML) progressed significantly in the last decade, evolving the computer-
based learning/prediction paradigm to a much more effective class of models known as …

Hyperspectral signatures can provide abundant information regarding health status of crops;
however it is difficult to discriminate between biotic and abiotic stress. In this study, the case …