Identification of Baha'sib mung beans based on Fourier transform near infrared spectroscopy and partial least squares

Intelligent System/Equipment for Quality Deterioration Detection of Fresh Food: Recent Advances and Application

The quality of fresh foods tends to deteriorate rapidly during harvesting, storage, and transportation. Intelligent detection equipment is designed to monitor and ensure product quality in the supply chain, measure appropriate food quality parameters in real time, and thus minimize quality degradation and potential financial losses. Through various available tracking devices, consumers can obtain actionable information about fresh food products. This paper reviews the recent progress in intelligent detection equipment for sensing the quality deterioration of fresh foods, including computer vision equipment, electronic nose, smart colorimetric films, hyperspectral imaging (HSI), near-infrared spectroscopy (NIR), nuclear magnetic resonance (NMR), ultrasonic non-destructive testing, and intelligent tracing equipment. These devices offer the advantages of high speed, non-destructive operation, precision, and high sensitivity.

Rapid analysis technologies with chemometrics for food authenticity field: A review

In recent years, the problem of food adulteration has become increasingly rampant, seriously hindering the development of food production, consumption, and management. The common analytical methods used to determine food authenticity present challenges, such as complicated analysis processes and time-consuming procedures, necessitating the development of rapid, efficient analysis technology for food authentication. Spectroscopic techniques, ambient ionization mass spectrometry (AIMS), electronic sensors, and DNA-based technology have gradually been applied for food authentication due to advantages such as rapid analysis and simple operation. This paper summarizes the current research on rapid food authenticity analysis technology from three perspectives, including breeds or species determination, quality fraud detection, and geographical origin identification, and introduces chemometrics method adapted to rapid analysis techniques. It aims to promote the development of rapid analysis technology in the food authenticity field.

Agronomic Traits, Fresh Food Processing Characteristics and Sensory Quality of 26 Mung Bean (Vigna radiata L.) Cultivars (Fabaceae) in China

In recent years, with the expansion of mung bean (Vigna radiata L.) planting areas and the increase of consumer demand, it has become imperative to screen high-quality mung bean cultivars. In this study, the agronomic traits, fresh bean characteristics, and sensory evaluation of boiled beans were analyzed for 26 mung bean cultivars. The results showed that the variation coefficient and genetic diversity index of six agronomic traits of mung bean ranged from 9.04% to 44.98%, 1.68 to 1.96, respectively, with abundant genetic variation, and the highest was the grain yield. Mung bean cultivars with higher grain yield had more advantage in the number of branches, number of pods per plant, and 100-seed weight. The fresh bean traits were relatively stable, with an average coefficient variation of 8.48%. The trait with the highest genetic diversity index was the number of seeds per pod (2.03). The cultivar with the highest total sensory evaluation score of boiled beans was Zhanglv 3 (75.67), which had more advantages in taste and color. Through the comprehensive evaluation of grey relational analysis, the cultivars suitable for fresh food processing were Zhonglv 3 (0.960), Jilv 11 (0.942), Zhonglv 1 (0.915), CES-78 (0.899) and Kelv 2 (0.896). Generally, the high-quality cultivars with higher yield and fresh food processing characteristics were CES-78, Kelv 2, Zhonglv 16, and Zhonglv 2. This study provided a preference for the breeding of fresh mung bean cultivars, development of new products and improvement of mung bean resource utilization.