What is the most effective analytical method for quantification and identification of microplastics in contaminated soils?

The increasing concern over microplastics (MPs) contamination in agricultural soils due to excessive plastic use is a worldwide concern. The objective of this study was to determine which analytical technique is most effective for the analysis of MPs in agricultural soils. Near-infrared spectroscopy (NIR), scanning electron microscopy (SEM), multispectral analysis, and X-ray diffraction were used to analyze sections of clay soil containing varying percentages of virgin white MPs from 0 to 100%.

FT-NIR and linear discriminant analysis to classify chickpea seeds produced with harvest aid chemicals.

Spectroscopy and machine learning (ML) algorithms have provided significant advances to the modern food industry. Instruments focusing on near-infrared spectroscopy allow obtaining information about seed and grain chemical composition, which can be related to changes caused by field pesticides. We investigated the potential of FT-NIR spectroscopy combined with Linear Discriminant Analysis (LDA) to discriminate chickpea seeds produced using different desiccant herbicides at harvest anticipation.

Interactive machine learning for soybean seed and seedling quality classification.

New computer vision solutions combined with artificial intelligence algorithms can help recognize patterns in biological images, reducing subjectivity and optimizing the analysis process. The aim of this study was to propose an approach based on interactive and traditional machine learning methods to classify soybean seeds and seedlings according to their appearance and physiological potential. In addition, we correlated the appearance of seeds to their physiological performance.

Exogenous brassinosteroids increase lead stress tolerance in seed germination and seedling growth of Brassica juncea L.

Lead (Pb) is a highly toxic heavy metal to plants, animals, and human beings. The use of growth regulators has reversed the effects of heavy metal stress on germination and early plant development. The aim of this study was to evaluate the effect of brassinosteroids on seed germination and seedling growth of Brassica juncea (L.

Sugar metabolism and developmental stages of rubber tree (Hevea brasiliensis L.) seeds.

Changes in the concentration of sugars and sucrose metabolism enzymes can characterize the developmental stages of a seed. In recalcitrant species such as Hevea brasiliensis L., little is known about these changes.