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Pea (Pisum sativum L.) is a nutrient-dense legume whose nutritional indicators influence its functional qualities. Traditional methods to identify these components and examine the relationships between their contents could be more laborious, hindering the quality assessment of the varieties of peas. This study conducted a statistical analysis of data about the sensory and physicochemical nutritional attributes of peas acquired using traditional techniques. Additionally, 90 sets of spectral data were obtained using a portable near-infrared spectrometer, which were then integrated with chemical values to create a near-infrared model for the basic ingredient content of peas. The correlation analysis revealed significant findings: pea starch displayed a substantial negative correlation with moisture, crude fiber, and crude protein, while showing a highly significant positive correlation with pea seed thickness. Furthermore, pea protein exhibited a significant positive correlation with crude fiber and crude fat. Cluster analysis classified all pea varieties into three distinct groups, successfully distinguishing those with elevated protein content, high starch content, and low-fat content. The combined contribution of PC1 and PC2 in the principal component analysis (PCA) was 51.2%. Partial least squares regression (PLSR) and other spectral preprocessing methods improved the predictive model, which performed well with an external dataset, with calibration coefficients of 0.89–0.99 and prediction coefficients of 0.71–0.88. This method enables growers and processors to efficiently analyze the composition of peas and evaluate crop quality, thereby enhancing food industry development.

As the quality of life continues to improve globally, there is an increasing demand for nutritious and high-quality food products. Peanut butter, a widely consumed and nutritionally valuable product, must meet stringent quality standards and exhibit excellent stability to satisfy consumer expectations and maintain its competitive position in the market. However, its high fat content, particularly unsaturated fatty acids, makes it highly susceptible to quality deterioration during storage. Key issues such as fat separation, lipid oxidation, and rancidity can significantly compromise its texture, flavor, and aroma, while also reducing its shelf life. Understanding the underlying mechanisms that drive these processes is essential for developing effective preservation strategies. This understanding not only aids food scientists and industry professionals in improving product quality but also enables health-conscious consumers to make informed decisions regarding the selection and storage of peanut butter. Recent research has focused on elucidating the mechanisms responsible for the quality deterioration of peanut butter, with particular attention to the intermolecular interactions among its key components. Current regulatory techniques aimed at improving peanut butter quality encompass raw material selection, advancements in processing technologies, and the incorporation of food additives. Among these innovations, plant protein nanoparticles have garnered significant attention as a promising class of green emulsifiers. These nanoparticles have demonstrated potential for stabilizing peanut butter emulsions, thereby mitigating fat separation and oxidation while aligning with the growing demand for environmentally friendly food production. Despite these advances, challenges remain in optimizing the stability and emulsifying efficiency of plant protein nanoparticles to ensure the long-term quality and stability of peanut butter. Future research should focus on improving the structural properties and functional performance of these nanoparticles to enhance their practical application as emulsifiers. Such efforts could provide valuable theoretical and practical insights into the development of stable, high-quality peanut butter, ultimately advancing the field of food science and technology.

Oyster sauce (OS) is a highly processed oyster product. However, the significant price difference between OS and fresh oysters raises a question: Does authentic OS truly contain components from oysters or oyster enzymatic hydrolysates (OEH)? Therefore, the odor compounds of Lee Kum Kee oyster sauce (LKK), 4 OEHs, and 6 other seafood enzymatic hydrolysates (SEHs) were analyzed by using solid-phase microextraction and gas chromatography–olfactometry-mass spectrometry technology (SPME-GC-O-MS). The results of multivariate statistical analysis demonstrated the effective discrimination between LKK and OEHs from other SEHs. According to the VIP value and the differences in the composition of odor compounds among different samples, 15 essential odor compounds were screened out, which could distinguish whether the samples contained OEHs. Among them, acetic acid, 2-pentylfuran, 2-ethyl furan, 2-methylbutanal, and nonanal were only detected in LKK and OEHs, which further indicated the existence of OEH in LKK.

Fruit color affects its commercial value. β-carotene is the pigment that provides color for many fruits and vegetables. However, the molecular mechanism of β-carotene metabolism during apricot ripening is largely unknown. Here, we investigated whether β-carotene content affects apricot fruit color. First, the differences in β-carotene content between orange apricot ‘JTY’ and white apricot ‘X15’ during nine developmental stages (S1–S9) were compared. β-carotene contents highly significantly differed between ‘JTY’ and ‘X15’ from S5 (color transition stage) onwards. Whole-transcriptome analysis showed that the β-carotene synthesis genes 15-cis-phytoene desaturase (PaPDS) and 15-cis-phytoene synthase (PaPSY) significantly differed between the two cultivars during the color transition stage. There was a 5 bp deletion in exon 11 of PaPDS in ‘X15’, which led to early termination of amino acid translation. Gene overexpression and virus-induced silencing analysis showed that truncated PaPDS disrupted the β-carotene biosynthesis pathway in apricot pulp, resulting in decreased β-carotene content and a white phenotype. Furthermore, virus-induced silencing analysis showed that PaPSY was also a key gene in β-carotene biosynthesis. These findings provide new insights into the molecular regulation of apricot carotenoids and provide a theoretical reference for breeding new cultivars of apricot.

Abstract Background Apricot is cultivated worldwide because of its high nutritive content and strong adaptability. Its flesh is delicious and has a unique and pleasant aroma. Apricot kernel is also consumed as nuts. The genome of apricot has been sequenced, and the transcriptome, resequencing, and phenotype data have been increasely generated. However, with the emergence of new information, the data are expected to integrate, and disseminate. Results To better manage the continuous addition of new data and increase convenience, we constructed the apricot genomic and phenotypic database (AprGPD, http://apricotgpd.com ). At present, AprGPD contains three reference genomes, 1692 germplasms, 306 genome resequencing data, 90 RNA sequencing data. A set of user-friendly query, analysis, and visualization tools have been implemented in AprGPD. We have also performed a detailed analysis of 59 transcription factor families for the three genomes of apricot. Conclusion Six modules are displayed in AprGPD, including species, germplasm, genome, variation, product, tools. The data integrated by AprGPD will be helpful for the molecular breeding of apricot.

Aquaporins (AQPs) are essential channel proteins that play a major role in plant growth and development, regulate plant water homeostasis, and transport uncharged solutes across biological membranes. In this study, 33 AQP genes were systematically identified from the kernel-using apricot (Prunus armeniaca L.) genome and divided into five subfamilies based on phylogenetic analyses. A total of 14 collinear blocks containing AQP genes between P. armeniaca and Arabidopsis thaliana were identified by synteny analysis, and 30 collinear blocks were identified between P. armeniaca and P. persica. Gene structure and conserved functional motif analyses indicated that the PaAQPs exhibit a conserved exon-intron pattern and that conserved motifs are present within members of each subfamily. Physiological mechanism prediction based on the aromatic/arginine selectivity filter, Froger’s positions, and three-dimensional (3D) protein model construction revealed marked differences in substrate specificity between the members of the five subfamilies of PaAQPs. Promoter analysis of the PaAQP genes for conserved regulatory elements suggested a greater abundance of cis-elements involved in light, hormone, and stress responses, which may reflect the differences in expression patterns of PaAQPs and their various functions associated with plant development and abiotic stress responses. Gene expression patterns of PaAQPs showed that PaPIP1-3, PaPIP2-1, and PaTIP1-1 were highly expressed in flower buds during the dormancy and sprouting stages of P. armeniaca. A PaAQP coexpression network showed that PaAQPs were coexpressed with 14 cold resistance genes and with 16 cold stress-associated genes. The expression pattern of 70% of the PaAQPs coexpressed with cold stress resistance genes was consistent with the four periods [Physiological dormancy (PD), ecological dormancy (ED), sprouting period (SP), and germination stage (GS)] of flower buds of P. armeniaca. Detection of the transient expression of GFP-tagged PaPIP1-1, PaPIP2-3, PaSIP1-3, PaXIP1-2, PaNIP6-1, and PaTIP1-1 revealed that the fusion proteins localized to the plasma membrane. Predictions of an A. thaliana ortholog-based protein–protein interaction network indicated that PaAQP proteins had complex relationships with the cold tolerance pathway, PaNIP6-1 could interact with WRKY6, PaTIP1-1 could interact with TSPO, and PaPIP2-1 could interact with ATHATPLC1G. Interestingly, overexpression of PaPIP1-3 and PaTIP1-1 increased the cold tolerance of and protein accumulation in yeast. Compared with wild-type plants, PaPIP1-3- and PaTIP1-1-overexpressing (OE) Arabidopsis plants exhibited greater tolerance to cold stress, as evidenced by better growth and greater antioxidative enzyme activities. Overall, our study provides insights into the interaction networks, expression patterns, and functional analysis of PaAQP genes in P. armeniaca L. and contributes to the further functional characterization of PaAQPs.

Prunus mira Koehne, an important economic fruit crop with high breeding and medicinal values, and an ancestral species of many cultivated peach species, has recently been declared an endangered species. However, basic information about genetic diversity, population structure, and morphological variation is still limited for this species. In this study, we sampled 420 P. mira individuals from 21 wild populations in the Tibet plateau to conduct a comprehensive analysis of genetic and morphological characteristics. The results of molecular analyses based on simple sequence repeat (SSR) markers indicated moderate genetic diversity and inbreeding (A = 3.8, Ae = 2.5, He = 0.52, Ho = 0.44, I = 0.95, FIS = 0.17) within P. mira populations. STRUCTURE, GENELAND, and phylogenetic analyses assigned the 21 populations to three genetic clusters that were moderately correlated with geographic altitudes, and this may have resulted from significantly different climatic and environmental factors at different altitudinal ranges. Significant isolation-by-distance was detected across the entire distribution of P. mira populations, but geographic altitude might have more significant effects on genetic structure than geographic distance in partial small-scale areas. Furthermore, clear genetic structure, high genetic differentiation, and restricted gene flow were detected between pairwise populations from different geographic groups, indicating that geographic barriers and genetic drift have significant effects on P. mira populations. Analyses of molecular variance based on the SSR markers indicated high variation (83.7% and 81.7%), whereas morphological analyses revealed low variation (1.30%-36.17%) within the populations. Large and heavy fruits were better adapted than light fruits and nutlets to poor climate and environmental conditions at high altitudes. Based on the results of molecular and morphological analyses, we classified the area into three conservation units and proposed several conservation strategies for wild P. mira populations in the Tibet plateau.