In the last few years, the use of artificial intelligence and technological advances such as
deep learning, new 3D-capable sensors, and edge computing embedded systems have …

Weeds are mainly spread by weed seeds being mixed with agricultural and forestry crop
seeds, grain, animal hair, and other plant products, and disturb the growing environment of …

Watermelon cultivators often encounter various challenges of the varietal mixing of triploid,
diploid, and tetraploid seeds, thus hindering the watermelon industry due to the uncertainty …

The widely used techniques for analyzing the quality of powdered food products focus on
targeted detection with a low-throughput screening of samples. Owing to potentially …

In the present study, a deep learning-based two-scenario method is proposed to distinguish
tomato seed cultivars. First, images of seeds of four different tomato cultivars (Sacher F1 …

The accurate and rapid detection of cotton seed quality is crucial for safeguarding cotton
cultivation. To increase the accuracy and efficiency of cotton seed detection, a deep learning …

Seed varieties are often differentiated via the manual and subjective classification of their
external textural, spectral, and morphological biosignatures. This traditional method of …

Seed quality is a critical factor in agricultural production, and variety purity is a crucial
measure of seed quality. Ensuring seed quality is essential for optimizing crop yields and …

Methods that combine targeted techniques and chemometrics for analyzing food authenticity
can only facilitate the detection of predefined or known adulterants, while unknown …

Image analysis can provide reproducible, objective and accurate results using a non-
destructive, inexpensive procedure. The aim of this study was to evaluate the usefulness of …