AIMC Topic: Vegetables

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Impact of agricultural subsidy on chemical fertilizer use: Empirical evidence of China's Organic-Substitute-Chemical-Fertilizer policy based on double machine learning.

PloS one
The sustainable development of agriculture hinges on effective fertilizer management, and China's experience with chemical fertilizer overuse highlights the challenges and opportunities in this domain. This study examines the impact of agricultural s...

Efficacious paper-based colorimetric detection of bacterial contamination in vegetables utilizing indicator dyes and machine learning.

Food chemistry
Food contamination from bacteria and resulting spoilage has been a persistent problem in the supply chain, leading to substantial waste and financial loss. Likewise, vegetables are prone to microbial contamination due to poor/unhygienic agricultural ...

Comparative metabolomics profiling reveals the aroma and nutritional diversity of eight wild edible plants.

Food chemistry
Wild edible plants are important yet undervalued vegetables, due to limited knowledge of their bioactive components and nutritional/functional potential. In this study, we used full-spectrum metabolomics and machine learning to analyze the aroma-rela...

Unveiling Hidden Health Risks: Machine Learning Enhanced Modeling of Plastic Additive Release Kinetics in Fresh Produce Packaging.

Environmental science & technology
Fresh produce packaging (FPP) plays a critical role in protecting fruits and vegetables from various environmental factors. However, the presence, migration, and human health risks of additives in FPP have received limited attention. This study inves...

Comparing machine learning models to chemometric ones to detect food fraud: A case study in Slovenian fruits and vegetables.

Food chemistry
We present a method for comparing models used to detect food fraud based on stable isotopes and trace element (SITE) levels. Existing modeling procedures generally do not provide an uncertainty estimate on a model's performance due to variations in t...

Hyperspectral Imaging and Deep Learning for Quality and Safety Inspection of Fruits and Vegetables: A Review.

Journal of agricultural and food chemistry
Quality inspection of fruits and vegetables linked to food safety monitoring and quality control. Traditional chemical analysis and physical measurement techniques are reliable, they are also time-consuming, costly, and susceptible to environmental a...

Foodomics approaches: New insights in phenolic compounds analysis.

Food research international (Ottawa, Ont.)
Fruits, vegetables, and plant-based foods contain several bioactive substances such as phenolic compounds (PCs), that are plant secondary metabolites with attributed health properties. The study of the metabolic pathways of PCs, including those relat...

Light spectrum mediated improved graft-healing response by enhanced expression of transport protein in vegetables under drought conditions.

Plant physiology and biochemistry : PPB
Vegetable production faces unprecedented challenges due to a rapid change in climate. Among several challenges increased stress factors like drought, salinity, and temperature threaten overall vegetable production. Grafting, a well-established techni...

Hyperspectral discrimination of vegetable crops grown under organic and conventional cultivation practices: a machine learning approach.

Scientific reports
A verifiable and regional level method for mapping crops cultivated under organic practices holds significant promise for certifying and ensuring the quality of farm products marketed as organic. The prevailing method for the identification of organi...

MOF-Based Biomimetic Enzyme Microrobots for Efficient Detection of Total Antioxidant Capacity of Fruits and Vegetables.

Small (Weinheim an der Bergstrasse, Germany)
Green and efficient total antioxidant capacity (TAC) detection is significant for healthy diet and disease prevention. This work first proposed the concept of TAC colorimetric detection based on microrobots. A novel metal-organic framework (MOF)-base...