Rice consumption and demand for premium rice are increasing worldwide. However, the characterizations and how to identify the premium rice are still unclear. Small molecular metabolites have a great advantage in distinguishing subtle differences among similar agricultural products. So, we hypothesized that the metabolites would be the key to identifying the tiny differences in premium rice among similar varieties. In this study, we performed metabolomic and transcriptomic profiles to comprehensively elucidate key metabolites, genes, and formation mechanisms of premium rice. As a result, eight compounds belong to four categories, and 49 different expressional genes were identified in premium rice varieties after comparing with the second-best varieties. Moreover, the integrated analysis confirmed that the amino acid pathway, including 42 expression genes and 11 metabolites, was critical for the premium rice formation. Six genes and two metabolites had significant regulatory effects on the pathways. Furthermore, amino acid quantification confirmed the content of 12 kinds of hydrolytic amino acids, such as aspartic acid and arginine were different between premium and other varieties. These amino acids may serve as potential biomarkers for differentiating premium rice in Northeast China. Our results strongly support the possibility of differentiating premium rice and would provide essential data for premium rice identification and metabolomics-assisted breeding.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11621605 | PMC |
http://dx.doi.org/10.1016/j.fochms.2024.100230 | DOI Listing |
Food Chem (Oxf)
December 2024
Quality and Safety Institute of Agricultural Products, Heilongjiang Academy of Agricultural Sciences/Key Laboratory of Quality and Safety of Cereals and Their Products, State Administration for Market Regulation, Harbin 150086, China.
Rice consumption and demand for premium rice are increasing worldwide. However, the characterizations and how to identify the premium rice are still unclear. Small molecular metabolites have a great advantage in distinguishing subtle differences among similar agricultural products.
View Article and Find Full Text PDFFoods
October 2024
School of Grain Science and Technology, Jiangsu University of Science and Technology, Zhenjiang 212100, China.
Near-infrared spectroscopy (NIRS) holds significant promise in detecting food adulteration due to its non-destructive, simple, and user-friendly properties. This study employed NIRS in conjunction with chemometrics to estimate the content of low-price rice flours (Nanjing, Songjing, Jiangxi silk, Yunhui) blended with high-price rice (Wuchang and Thai fragrant). Partial least squares regression (PLSR), support vector regression (SVR), and back-propagation neural network (BPNN) models were deployed to analyze the spectral data of adulterated samples and assess the degree of contamination.
View Article and Find Full Text PDFEnviron Res
December 2024
State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China; Shanghai Urban Pollution Control Engineering Research Center Co., Ltd., 588 Miyun Road, Shanghai, 200092, China. Electronic address:
Foods
August 2024
Institute of Agricultural Science and Technology Information, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China.
Understanding urban consumers' preferences for rice attributes is crucial for rice breeders, producers, and retailers to meet diverse and evolving market demands. Based on the sample data of 629 rice consumers in Shanghai, China, obtained through the choice experiment (CE) approach, this study uses the mixed logit (ML) model to analyze consumers' preferences and willingness to pay (WTP) for food safety labels, brands, nutritional quality, and taste quality. Furthermore, the latent class (LC) model examines the heterogeneity in consumer group preferences.
View Article and Find Full Text PDFJ Sci Food Agric
January 2025
School of Environmental and Chemical Engineering, Foshan University, Foshan, China.
Background: The co-application of biochar and wood vinegar has demonstrated the potential to enhance premium crop production. The present study reveals the effects of co-applying rice husk biochar and wood vinegar (both foliar and soil application) on soil properties and the growth of Chinese cabbage (Brassica chinensis L.) in a two-season pot experiment.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!