Monitoring yellow rust progression during spring critical wheat growth periods using multi-temporal Sentinel-2 imagery.

BACKGROUND: Yellow rust (Puccinia striiformis f. sp. tritici) is a devastating hazard to wheat production, which poses a serious threat to yield and food security in the main wheat-producing areas in eastern China. It is necessary to monitor yellow rust progression during spring critical wheat growth periods to support its prediction by providing timely calibrations for disease prediction models and timely green prevention and control. RESULTS: Three Sentinel-2 images for the disease during the three wheat growth periods (jointing, heading, and filling) were acquired. Spectral, texture, and color features were all extracted for each growth period disease. Then three period-specific feature sets were obtained. Given the differences in field disease epidemic status in the three periods, three period-targeted monitoring models were established to map yellow rust damage progression in spring and track its spatiotemporal change. The models' performance was then validated based on the disease field truth data during the three periods (87 for the jointing period, 183 for the heading period, and 155 for the filling period). The validation results revealed that the representation of the wheat yellow rust damage progression based on our monitoring model group was realistic and credible. The overall accuracy of the healthy and diseased pixel classification monitoring model at the jointing period reached 87.4%, and the coefficient of determination (R2) of the disease index regression monitoring models at the heading and filling periods was 0.77 (heading period) and 0.76 (filling period). The model-group-result-based spatiotemporal change detection of the yellow rust progression across the entire study area revealed that the area proportions conforming to the expected disease spatiotemporal development pattern during the jointing-to-heading period and the heading-to-filling period reached 98.2% and 84.4% respectively. CONCLUSIONS: Our jointing, heading, and filling period-targeted monitoring model group overcomes the limitations of most existing monitoring models only based on single-phase remote sensing information. It performs well in revealing the wheat yellow rust spatiotemporal epidemic in spring, can timely update disease trends to optimize disease management, and provide a basis for disease prediction to timely correct model. © 2024 Society of Chemical Industry.

A Study on the Formation of Flavor Substances by Bacterial Diversity in the Fermentation Process of Canned Bamboo Shoots in Clear Water.

Canned bamboo shoots in clear water could produce a unique flavor through bacterial diversity via the fermentation process. Weissella, Streptococcus, Leuconostoc, Acinetobacter, Lactococcus and Lactobacillus were the main microorganisms. Tyrosine was the most abundant free amino acid (FAA), which had a negative correlation with Lactococcus. Ten kinds of flavor substances, such as 3-methyl-1-butanol, acetic acid, 2-phenylethyl ester, benzene acetaldehyde, benzoic acid and ethyl ester, were important influential factors in the flavor of fermented bamboo shoots. Through the verification test of tyrosine and phenylalanine decarboxylase, it was found that Lactococcus lactis TJJ2 could decompose tyrosine and phenylalanine to produce benzaldehyde and benzene acetaldehyde, which provided the fermented bamboo shoots with a grassy aroma.

Advances in sequencing and key character analysis of mango (Mangifera indica L.).

Mango (Mangifera indica L.) is an important fruit crop in tropical and subtropical countries associated with many agronomic and horticultural problems, such as susceptibility to pathogens, including powdery mildew and anthracnose, poor yield and quality, and short shelf life. Conventional breeding techniques exhibit significant limitations in improving mango quality due to the characteristics of long ripening, self-incompatibility, and high genetic heterozygosity. In recent years, much emphasis has been placed on identification of key genes controlling a certain trait through genomic association analysis and directly breeding new varieties through transgene or genotype selection of offspring. This paper reviews the latest research progress on the genome and transcriptome sequencing of mango fruit. The rapid development of genome sequencing and bioinformatics provides effective strategies for identifying, labeling, cloning, and manipulating many genes related to economically important traits. Preliminary verification of the functions of mango genes has been conducted, including genes related to flowering regulation, fruit development, and polyphenol biosynthesis. Importantly, modern biotechnology can refine existing mango varieties to meet the market demand with high economic benefits.

Independent flavonoid and anthocyanin biosynthesis in the flesh of a red-fleshed table grape revealed by metabolome and transcriptome co-analysis.

BACKGROUND: Red flesh is a desired fruit trait, but the regulation of red flesh formation in grape is not well understood. 'Mio Red' is a seedless table grape variety with light-red flesh and blue-purple skin. The skin color develops at veraison whereas the flesh color develops at a later stage of berry development. The flesh and skin flavonoid metabolomes and transcriptomes were analyzed. RESULTS: A total of 161 flavonoids were identified, including 16 anthocyanins. A total of 66 flavonoids were found at significantly different levels in the flesh and skin (fold change ≥ 2 or ≤ 0.5, variable importance in projection (VIP) ≥ 1). The main anthocyanins in the flesh were pelargonidin and peonidin, and in the skin were peonidin, delphinidin, and petunidin. Transcriptome comparison revealed 57 differentially expressed structural genes of the flavonoid-metabolism pathway (log2fold change ≥ 1, FDR < 0.05, FPKM ≥ 1). Two differentially expressed anthocyanin synthase (ANS) genes were annotated, ANS2 (Vitvi02g00435) with high expression in flesh and ANS1 (Vitvi11g00565) in skin, respectively. One dihydro flavonol 4-reductase (DFR, Vitvi18g00988) gene was differentially expressed although high in both skin and flesh. Screened and correlation analysis of 12 ERF, 9 MYB and 3 bHLH genes. The Y1H and dual luciferase assays showed that MYBA1 highly activates the ANS2 promoter in flesh and that ERFCBF6 was an inhibitory, EFR23 and bHLH93 may activate the DFR gene. These genes may be involved in the regulation of berry flesh color. CONCLUSIONS: Our study revealed that anthocyanin biosynthesis in grape flesh is independent of that in the skin. Differentially expressed ANS, MYB and ERF transcription factors provide new clues for the future breeding of table grapes that will provide the health benefits as red wine.

Polygalacturonase gene family analysis identifies FcPG12 as a key player in fig (Ficus carica L.) fruit softening.

BACKGROUND: The fig (Ficus carica L.) tree has high economic value. However, its fruit have a short shelf life due to rapid softening. Polygalacturonases (PGs) are essential hydrolases, responsible for the pectin degradation that plays a key role in fruit softening. However, fig PG genes and their regulators have not yet been characterized. RESULTS: In this study, 43 FcPGs were identified in the fig genome. They were non-uniformly distributed on 13 chromosomes, and tandem repeat PG gene clusters were found on chromosomes 4 and 5. Ka/Ks calculation and collinear analysis indicated negative selection as the main driver of FcPG family expansion. Fourteen FcPGs were found expressed in fig fruit with FPKM values > 10, of which seven were positively correlated, and three, negatively correlated with fruit softening. Eleven FcPGs were upregulated and two downregulated in response to ethephon treatment. FcPG12, a member of the tandem repeat cluster on chromosome 4, was selected for further analyses due to its sharp increment in transcript abundance during fruit softening and its response to ethephon treatment. Transient overexpression of FcPG12 led to decreased fig fruit firmness and increased PG enzyme activity in the tissue. Two ethylene response factor (ERF)-binding GCC-box sites were found on the FcPG12 promoter. Yeast one-hybrid and dual luciferase assays showed that FcERF5 binds directly to the FcPG12 promoter and upregulates its expression. Transient overexpression of FcERF5 upregulated FcPG12 expression, thereby increasing PG activity and fruit softening. CONCLUSIONS: Our study identified FcPG12 as a key PG gene in fig fruit softening, and its direct positive regulation by FcERF5. The results provide new information on the molecular regulation of fig fruit softening.

Screening, Identification and Physiological Characteristics of Lactobacillus rhamnosus M3 (1) against Intestinal Inflammation.

The probiotic role of lactic acid bacteria (LAB) in regulating intestinal microbiota to promote human health has been widely reported. However, the types and quantities of probiotics used in practice are still limited. Therefore, isolating and screening LAB with potential probiotic functions from various habitats has become a hot topic. In this study, 104 strains of LAB were isolated from and identified in traditionally fermented vegetables, fresh milk, healthy infant feces, and other environments. The antibacterial properties-resistance to acid, bile salts, and digestive enzymes-and adhesion ability of the strains were determined, and the biological safety of LAB with better performance was studied. Three LAB with good comprehensive performance were obtained. These bacteria had broad-spectrum antibacterial properties and good acid resistance and adhesion ability. They exhibited some tolerance to pig bile salt, pepsin, and trypsin and showed no hemolysis. They were sensitive to the selected antibiotics, which met the required characteristics and safety evaluation criteria for probiotics. An in vitro fermentation experiment and milk fermentation performance test of Lactobacillus rhamnosus (L. rhamnosus) M3 (1) were carried out to study its effect on the intestinal flora and fermentation performance in patients with inflammatory bowel disease (IBD). Studies have shown that this strain can effectively inhibit the growth of harmful microorganisms and produce a classic, pleasant flavor. It has probiotic potential and is expected to be used as a microecological agent to regulate intestinal flora and promote intestinal health. It can also be used as an auxiliary starter to enhance the probiotic value of fermented milk.

Akkermansia muciniphila Cell-Free Supernatant Improves Glucose and Lipid Metabolisms in Caenorhabditis elegans.

To explore the mechanism by which Akkermansia muciniphila cell-free supernatant improves glucose and lipid metabolisms in Caenorhabditis elegans, the present study used different dilution concentrations of Akkermansia muciniphila cell-free supernatant as an intervention for with Caenorhabditis elegans under a high-glucose diet. The changes in lifespan, exercise ability, level of free radicals, and characteristic indexes of glucose and lipid metabolisms were studied. Furthermore, the expression of key genes of glucose and lipid metabolisms was detected by qRT-PCR. The results showed that A. muciniphila cell-free supernatant significantly improved the movement ability, prolonged the lifespan, reduced the level of ROS, and alleviated oxidative damage in Caenorhabditis elegans. A. muciniphila cell-free supernatant supported resistance to increases in glucose and triglyceride induced by a high-glucose diet and downregulated the expression of key genes of glucose metabolism, such as gsy-1, pygl-1, pfk-1.1, and pyk-1, while upregulating the expression of key genes of lipid metabolism, such as acs-2, cpt-4, sbp-1, and tph-1, as well as down-regulating the expression of the fat-7 gene to inhibit fatty acid biosynthesis. These findings indicated that A. muciniphila cell-free supernatant, as a postbiotic, has the potential to prevent obesity and improve glucose metabolism disorders and other diseases.

Migration risk of fall armyworm (Spodoptera frugiperda) from North Africa to Southern Europe.

With the development of globalization and agriculture trade, as well as its own strong migratory capacity, fall armyworm (FAW) (Spodoptera frugiperda) (J.E. Smith) has invaded more than 70 countries, posing a serious threat to the production of major crops in these areas. FAW has now also been detected in Egypt in North Africa, putting Europe, which is separated from it only by the Mediterranean Sea, at high risk of invasion. Therefore, this study integrated multiple factors of insect source, host plant, and environment to provide a risk analysis of the potential trajectories and time periods of migration of FAW into Europe in 2016~2022. First, the CLIMEX model was used to predict the annual and seasonal suitable distribution of FAW. The HYSPLIT numerical trajectory model was then used to simulate the possibility of the FAW invasion of Europe through wind-driven dispersal. The results showed that the risk of FAW invasion between years was highly consistent (P<0.001). Coastal areas were most suitable for the expansion of the FAW, and Spain and Italy had the highest risk of invasion, with 39.08% and 32.20% of effective landing points respectively. Dynamic migration prediction based on spatio-temporal data can enable early warning of FAW, which is important for joint multinational pest management and crop protection.

AP2/ERF genes associated with superfast fig (Ficus carica L.) fruit ripening.

Fig fruits have significant health value and are culturally important. Under suitable climatic conditions, fig fruits undergo a superfast ripening process, nearly doubling in size, weight, and sugar content over three days in parallel with a sharp decrease in firmness. In this study, 119 FcAP2/ERF genes were identified in the fig genome, namely 95 ERFs, 20 AP2s, three RAVs, and one soloist. Most of the ERF subfamily members (76) contained no introns, whereas the majority of the AP2 subfamily members had at least two introns each. Three previously published transcriptome datasets were mined to discover expression patterns, encompassing the fruit peel and flesh of the 'Purple Peel' cultivar at six developmental stages; the fruit receptacle and flesh of the 'Brown Turkey' cultivar after ethephon treatment; and the receptacle and flesh of parthenocarpic and pollinated fruits of the 'Brown Turkey' cultivar. Eighty-three FcAP2/ERFs (68 ERFs, 13 AP2s, one RAV, and one soloist) were expressed in the combined transcriptome dataset. Most FcAP2/ERFs were significantly downregulated (|log2(fold change) | ≥ 1 and p-adjust < 0.05) during both normal fruit development and ethephon-induced accelerated ripening, suggesting a repressive role of these genes in fruit ripening. Five significantly downregulated ERFs also had repression domains in the C-terminal. Seven FcAP2/ERFs were identified as differentially expressed during ripening in all three transcriptome datasets. These genes were strong candidates for future functional genetic studies to elucidate the major FcAP2/ERF regulators of the superfast fig fruit ripening process.

Detection of wheat Fusarium head blight using UAV-based spectral and image feature fusion.

Infection caused by Fusarium head blight (FHB) has severely damaged the quality and yield of wheat in China and threatened the health of humans and livestock. Inaccurate disease detection increases the use cost of pesticide and pollutes farmland, highlighting the need for FHB detection in wheat fields. The combination of spectral and spatial information provided by image analysis facilitates the detection of infection-related damage in crops. In this study, an effective detection method for wheat FHB based on unmanned aerial vehicle (UAV) hyperspectral images was explored by fusing spectral features and image features. Spectral features mainly refer to band features, and image features mainly include texture and color features. Our aim was to explain all aspects of wheat infection through multi-class feature fusion and to find the best FHB detection method for field wheat combining current advanced algorithms. We first evaluated the quality of the two acquired UAV images and eliminated the excessively noisy bands in the images. Then, the spectral features, texture features, and color features in the images were extracted. The random forest (RF) algorithm was used to optimize features, and the importance value of the features determined whether the features were retained. Feature combinations included spectral features, spectral and texture features fusion, and the fusion of spectral, texture, and color features to combine support vector machine, RF, and back propagation neural network in constructing wheat FHB detection models. The results showed that the model based on the fusion of spectral, texture, and color features using the RF algorithm achieved the best performance, with a prediction accuracy of 85%. The method proposed in this study may provide an effective way of FHB detection in field wheat.