Estimation of komatsuna freshness using visible and near-infrared spectroscopy based on the interpretation of NMR metabolomics analysis

Classification of Packaged Vegetable Soybeans Based on Freshness by Metabolomics Combined with Convolutional Neural Networks

Background/Objectives: Effectiveness of modified atmosphere (MA) packaging for the preservation of the freshness of vegetable soybeans was confirmed by using metabolomics combined with convolutional neural networks (CNNs). Methods: Stored under a low O2, high CO2 environment, the vegetable soybeans' freshness was tracked through changes in hue angle on the surface of the crops and metabolite levels compared to those stored under normoxia. Results: MA packaging slowed respiration and reduced pectin decomposition, succinic acid oxidation, and fatty acid consumption, all linked to freshness maintenance. Using 62 key metabolite concentrations as inputs, CNNs classified vegetable soybean freshness into seven categories with 92.9% accuracy, outperforming traditional linear discriminant analysis by 14.3%. Conclusions: These findings demonstrate MA packaging's effectiveness in extending freshness of vegetable soybeans by monitoring specific metabolic changes. This will contribute to the advancement of research aimed at elucidating the relationship between freshness and metabolism in horticultural crops.

Enhanced decreases in rice evapotranspiration in response to elevated atmospheric carbon dioxide under warmer environments

A short period of exposure to elevated CO2 is known to decrease evapotranspiration via stomatal closure. Based on theoretical evaluation of a canopy transpiration model, we hypothesized that this decrease in the evapotranspiration of rice under elevated CO2 was greater under higher temperature conditions due to an increased sensitivity of transpiration to changes in CO2 induced by the greater vapour pressure deficit. In a temperature gradient chamber-based experiment, a 200 ppm increase in CO2 concentration led to 0.4 mm (-7%) and 1.5 mm (-15%) decreases in 12 h evapotranspiration under ambient temperature and high temperature (+3.7°C) conditions, respectively. Model simulations revealed that the greater vapour pressure deficit under higher temperature conditions explained the variations in the reduction of evapotranspiration observed under elevated CO2 levels between the temperature treatments. Our study suggests the utility of a simple modelling framework for mechanistic understanding of evapotranspiration and crop energy balance system under changing environmental conditions.

A multi-block data approach to assessing beef quality: ComDim analysis of hyperspectral imaging, 1H NMR, electronic nose and quality parameters data

Several factors affect the quality of beef. In the field of chemometrics, multi-block data analysis methods are useful for examining multiple sources of information from a sample. This study focuses on the application of ComDim, a multi-block data analysis method, to evaluate beef from different parts of hyperspectral spectrum and image texture information, ¹H NMR fingerprints, quality parameters and electronic nose. Compared to principal component analysis (PCA) methods based on low-level data fusion, ComDim is more efficient and powerful, because it reveals the relationships between the methods and techniques studied, as well as the variability of beef quality across multiple metrics. The quality and metabolite composition of beef tenderloin and hindquarters were differentiated, with low L* value and high shear tenderloin distinguished from hindquarters with opposite characteristics. The proposed strategy demonstrates that ComDim approach can be used to characterize samples when different techniques describe the same set of samples.

Current State of Metabolomics Research in Meat Quality Analysis and Authentication

In the past decades, as an emerging omic, metabolomics has been widely used in meat science research, showing promise in meat quality analysis and meat authentication. This review first provides a brief overview of the concept, analytical techniques, and analysis workflow of metabolomics. Additionally, the metabolomics research in quality analysis and authentication of meat is comprehensively described. Finally, the limitations, challenges, and future trends of metabolomics application in meat quality analysis and meat authentication are critically discussed. We hope to provide valuable insights for further research in meat quality.