This manuscript presents a comprehensive survey on recent computer vision based food
grain classification techniques. It includes state-of-the-art approaches intended for different …

Evaluating binary classifications is a pivotal task in statistics and machine learning, because
it can influence decisions in multiple areas, including for example prognosis or therapies of …

This study focuses on the potential of multi-omics and machine learning approaches in
improving our understanding of the malting processes and cultivation systems in barley. The …

Accurately sorting high-quality soybean seeds is a key task in increasing soybean yield in
the breeding industry. At present, sorting systems based on machine vision focus on the …

Nondestructive inspection of varietal purity of seeds plays an important role in crop
improvement, agricultural production, and plant breeding. In the present study, a rapid and …

Leaf and fruit infections are the primary cause of the maximum harm to the crop, which
decreases the quality and amount of the goods. To improve the productivity of plants, the …

Highlights•Deep learning and transfer learning CNNs are compared in barley varietal
classification.•Simplifying the CNN model has positive impact on classification results.•Only …

Wheat variety recognition and authentication are essential tasks of the quality assessment in
the grain chain industry, especially for seed testing and certification processes. Recognition …

Crop cultivar identification is fundamental for agricultural research, industry and policies.
This paper investigates the feasibility of using visible/near infrared hyperspectral data …

This research aimed to improve selection of pepper seeds for separating high-quality seeds
from low-quality seeds. Past research has shown that seed vigor is significantly related to …