Given the diversity and richness of China's grain varieties, traditional physicochemical quality testing methods for rice, while providing accurate results, suffer from drawbacks such as time-consuming procedures, high costs, substantial reagent consumption, cumbersome sample preparation, and reliance on destructive or semi-destructive techniques. This study aims to employ near-infrared spectroscopy technology to establish rapid and non-destructive predictive models for key quality indicators of japonica rice. The research analyzed 133 samples from 71 widely cultivated japonica rice varieties across five major production regions in China, utilizing spectral data within a wavelength range of 660-1080 nm. Predictive models for moisture, protein, amylose, and fatty acid values were constructed using three algorithms-partial least squares regression (PLSR), ridge regression (RR), and extremely randomized trees (ERT)-linear regression and the extreme randomization tree (ERT)-their optimal parameters were determined using a 10-fold cross-validation optimization method. Eighty percent of the total dataset served as the training set, while the remaining 20% formed the test set, yielding a final test set comprising 26 samples. Performance comparisons revealed that the PLSR and RR models demonstrated superior predictive performance: the coefficient of determination (Rp2) exceeded 0.9 for all four indicators, with the R2 value for fatty acid prediction reaching as high as 0.99; the root mean square error (RMSEP) of the PLSR and RR models ranged between 0.0534% and 0.3360%, confirming their high predictive accuracy. Although all ERT models (except the protein model) achieved Rp2 values exceeding 0.9, their overall performance was slightly inferior to the first two methods. The protein ERT model demonstrated relatively low performance, with an Rp2 value of 0.6984 on the test set, which may be attributed to the limited sample size and weak protein spectral response signals. Although the samples covered five major production regions and 71 japonica rice varieties, their distribution was uneven (multiple varieties were represented by only one or a few samples). This study provides an efficient rapid quality assessment method for japonica rice; however, the generalization ability of the models requires further validation in future studies employing larger and more balanced sample sizes.

A large number of non-volatile metabolites are produced during the growth of rice; however, few studies have focused on the changes in these metabolites at different harvest times. In this study, Nangeng 5718 (a rice variety) was taken as the research object to study the changes in rice metabolites at different harvest times. Liquid chromatography mass spectrometry (LC-MS) was used to analyze the non-targeted metabolomics of rice at different harvest times in Nanjing, Huai’an, and Lianyungang in the Jiangsu Province of China. The results showed that 2111 metabolites were annotated by the human metabolome database (HMDB), accounting for 94.96% of the total number of metabolites. Rice metabolites included one categories, including 312 fatty acyls, 275 organooxygen compounds, 261 carboxylic acids and derivatives, etc. The results of the Kyoto encyclopedia of genes and genomes (KEGG) pathway showed that autophagy–other, ABC transporters, and glycerophospholipid metabolism had a great effect on rice heading to harvest. The experiments showed that L-histidine in Nangeng 5718 was upregulated. These results provide comprehensive insights into the relationship between rice harvest time and changes in metabolites.

The study explored the effects of different degrees of milling, including the moderate processing technology on the quality of japonica rice using Longdao 18, Longjing 31, Yanfeng 47, Yujingxiang, and Nanjing 46 rice varieties. The results indicated that as the milling intensity increased, the whiteness of the japonica rice and broken rice rate continuously increased, but the bran retention rate decreased. The taste value first increased and then plateaued, while the content of vitamin B1 and mineral elements generally showed a declining trend. From brown rice to the first stage of milling, there was a significant decrease in protein content. During the milling process, the vitamin B1 content in japonica rice was significantly positively correlated with the levels of magnesium, phosphorus, potassium, calcium, manganese, iron, copper, and zinc. Iron was more concentrated in the outer layers, and reducing the milling degree could significantly increase the retention rate of iron. Analysis of the coaxial curve diagram based on the proportion of the maximum value in each group relative to the brown-to-white rice yield for broken rice rate, taste value, vitamin B1, and iron content of five japonica rice varieties revealed that the moderate processing range for japonica rice corresponds to a brown-to-white rice yield of 88% to 92%. Within this range, the taste value of japonica rice reached its highest level, and more vitamin B1 and mineral elements such as iron were retained.

The palatability of rice is a crucial quality indicator; however, the mechanism by which blending improves rice palatability remains unclear. This study proposed a straightforward approach to improve rice palatability by blending high-amylose varieties, which generally exhibited lower palatability, with low-amylose or glutinous rice, the latter being nearly amylose-free. Various blending ratios were examined to optimize palatability, along with analyses of the physicochemical properties of blended rice, its leachate, and significantly different metabolites (SDMs). These findings revealed that a lower amylose content in the blended rice resulted in higher leachate production during cooking, with leachate containing less amylose. This contributed to the increased stickiness and reduced hardness of rice. Furthermore, a comparison of the SDMs in cooked blended and raw rice indicated that the primary SDMs were amino acids and lipid compounds.

Brown rice exhibits higher nutritional value and attracts more and more attentions; however, lipid alteration in brown rice during aging is poorly understood. In this study, lipidomics and volatilomics were employed to investigate free fatty acids, triglycerides, and volatile oxidative degradation products of lipids in brown rice during accelerated aging for 70 days. The results showed that the total free fatty acids in brown rice increased significantly (2.90-4.14 times) while triglycerides decreased remarkably at the initial stage of aging. Mono-unsaturated and polyunsaturated aldehydes, ketones, and acids increased obviously in brown rice during accelerated aging for 70 days. The screening of significantly different compounds indicated that the enzymatic hydrolysis of triglycerides (EHT) and enzymatic oxidation of lipids (EOL) were the main biochemical behaviors at the initial stage of aging (0-28 day) while automatic oxidation of lipids (AOL) was the primary chemical reaction for 28-70 days aging.

Four rice varieties from 3 production areas in Jiangsu, Heilongjiang and Liaoning were used as test materials, a "shotgun method" was established to identify rice varieties in different regions and varieties in China. The phospholipid species in rice were identified by "shotgun" mass spectrometry, and the differences among varieties were analyzed by partial least squares discriminant analysis（PLS-DA）. The results indicated that there were 67 kinds of phospholipids in rice, mainly including phosphatidyl choline, phosphatidyl ethanolamine, phosphatidyl glycerol, lyso-phosphatidyl choline, lyso-phosphatidyl ethanolamine and lyso-phosphatidyl glycerol, and the content of phospholipids in different varieties of rice was different. Combined with the method of PLS-DA, four rice varieties can be distinguished, the contributing components of phospholipid differences of different varieties can be determined, and the difference analysis of phospholipid characteristics among different rice varieties can be realized. Therefore, "shotgun" mass spectrometry combined with PLS-DA analysis can rapidly identify rice varieties.

Brown rice exhibits higher nutritional value and attracts more and more attentions; however, the change in phospholipid molecular species in brown rice during aging is poorly understood. In this study, shotgun lipidomics was employed to investigate the changes in phospholipid molecular species in four brown rice varieties (two japonica rice and two indica rice) during accelerated aging. A total of 64 phospholipid molecular species were identified, and most of them were rich in polyunsaturated fatty acids. For japonica rice, phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidylglycerol (PG) gradually decreased during accelerated aging. However, the content of PC, PE, and PG in indica rice showed no difference during accelerated aging. Significantly different phospholipid molecular species from four brown rice were screened during accelerated aging. Based on these significantly different phospholipids, the metabolic pathways including glycerophospholipid metabolism and linoleic acid metabolism during accelerated aging were depicted. The findings from this study could be helpful in explaining the impact of accelerated aging on phospholipids of brown rice, and offer an understanding on relationships between phospholipids degradation and brown rice deterioration.

大米的挥发组分是其香气的主要来源,虽然含量占比极低,却是决定大米品质的重要因素之一.目前,大米香气的评价方法包括感官评价法、电子舌/鼻法、以及气相色谱-质谱法(GC-MS)法等,其中,GC-MS法应用最为广泛.本文综述了近年来基于GC-MS技术研究大米挥发组分的进展,包括主要的前处理方法,分析了各种前处理方法的优势和不足,以及GC-MS技术在大米品种鉴别、加工机制和储藏机制研究领域的应用现状.其中,准确测定大米挥发组分的含量及阈值,以及从动态角度对大米香气成分的相互作用和形成机理进行研究是未来的研究方向.

In order to investigate the wheat quality in China, representative wheat covering more than 70% of the province were collected, based on wheat cultivars and planting areas. A total of 1,971 samples of wheat harvested in 2020 were collected for quality index evaluation. The overall level of crude protein content and gluten content is high, and the average values are 14.3% and 33.1% respectively. The quality of gluten is slightly poor, and the average value of gluten index is 68. The average flour stability is 7.1 min, and 32.8% of the samples accord with the requirements of strong gluten wheat (8 min). The overall level of maximum resistance and energy of extensograph test is general, and the average values are 355 EU and 70 cm2 respectively. In terms of food quality, the overall quality level of noodles was good, with the average score reached 81, and 74.2% of the samples reached over 80 points. The overall level of steamed bread and bread processing quality are general, with the average food score are 74, and the samples with more than 80 points are 30.5% and 43.3% respectively. The cake processing quality is poor, and the samples with more than 80 points account for only 14.3%. The proportion of wheat meet the standard of “High quality wheat-Strong gluten wheat” (GB/T 17893—1999) is 7.7%, 0.007% meet the standard of “High quality wheat-weak gluten wheat” (GB/T 17893—1999), and 36.5% meet the standard of “Quality classification of wheat varieties” (GB/T 17320—2013), of which 28.3% meet the requirements of high quality wheat. and 6.6% are high quality of strong gluten wheat, The proportion of wheat meeting the standard of “Quality Grain and Oils of China - Wheat” (LS/T 3109—2017 ) is 78.4%, of which the proportion of strong gluten and hard wheat is 6.8%.

To study the effect of malt flour and ascorbic acid addition on the quality of bread baking， the sensory score， texture and c-cell product image changes of the breads with malt flour and ascorbic acid addition were studied by using 29 representative samples from two major wheat producing provinces of henan and shandong. The results showed that， the volume， the volume score， the appearance score and the final comprehensive score of bread were significantly improved after the addition of malt flour and ascorbic acid. The bread crown became larger and the neck became more prominent; however， the color， texture and texture structure of bread scores changes were not obvious. In the analysis of texture， the hardness and toughness decreased significantly， the attenuation ratio did not change obviously. The slice area， slice circumference， cell number and cell density of bread increased significantly in the analysis of c-cell results.The slice brightness and cell diameter of the slices decreased significantly. There is a correlation between the instrument evaluation index and some parameters in the bread sensory evaluation.

The quality of wheat is affected by genotype and environment.Different varieties of wheat show different quality,and the influence of environment and genotype is also different.In this paper,the indexes of quality and food processing quality of 31 samples of Zhoumai 33 from different planting areas of Henan,Anhui,Jiangsu and Shanxi in 2018 and 2019 were studied and analyzed.The results showed that the quality performance of Zhoumai 33 was different in different locations,among which gluten content,farinograph stability,tensile energy,extensibility,maximum resistance,peak viscosity and bread quality varied greatly in different planting locations.The variation degree of noodle quality was little.The average score of sensory taste of bread and noodles in two years reached 81.7 and 87.1 respectively,all of which reached the level of high-quality bread and high-quality noodle wheat.The noodles had bright yellow color,good luster,good elasticity,high sensory score,the noodle score was not sensitive to environmental changes,and the quality was relatively stable.

为掌握我国主要粳稻品种食味品质概况,明确符合《中国好粮油稻谷》标准要求品种数量比例,收集了粳稻品种材料333份,对食味品质、蛋白质含量、垩白等指标进行了检测分析.结果 表明:食味值符合中国好粮油标准要求的品种数量占比约42％,按推广面积估算比例约为37％;垩白指标符合中国好粮油标准要求的占比为90.5％;粗蛋白含量平均值为8.8％,小于8.0％的样品占比为22.1％.通过本项目研究,基本掌握了我国主要粳稻品种的品质概况,为进一步完善好粮油标准和有效推进中国好粮油行动计划提供数据支撑.