The target strain DB-8 in this study was isolated from naturally fermented yogurt residues in a herder’s house in Dangxiong County,Xizang.Multi-omics and genetic evolutionary analysis has been multidimensionally vali...The target strain DB-8 in this study was isolated from naturally fermented yogurt residues in a herder’s house in Dangxiong County,Xizang.Multi-omics and genetic evolutionary analysis has been multidimensionally validated the species attribute of DB-8,revealing traits in its metabolic properties and genetic evolution in high-altitude environments.In accordance with the data obtained from the whole genome sequence and genetic evolution of DB-8,the bacterium is confirmed to be Lactobacillus delbrueckii subsp.lactis.The results of genome functional annotation demonstrated that DB-8 possesses a multitude of distinctive genes pertaining to cell wall,membrane,envelope biosynthesis,carbohydrate metabolism,and energy metabolism.Comparative genomics analysis revealed that DB-8 has 122 specific genes that support its energy metabolism,cellular repair,and biofilm systems.It is also anticipated that these genes will have exceptionally strong acid resistance.Targeted metabolic studies confirm that DB-8 produces significantly more propionic acid and isobutyric acid than other reference strains.Furthermore,based on the results of the untargeted metabolomics study,44 different metabolites were screened to create support vector machine models based on t-test-based feature screening,with an accuracy of 0.92 for the model validation set and a prediction accuracy of 100%,which marks the first successful application of machine learning to predict subspecies characterization of Lactobacillus delbrueckii.This study offers novel ideas for the precise identification between Lactobacillus delbrueckii subsp.bulgaricus and subsp.lactis,while enhancing the understanding of the fermentation characteristics of DB-8,thereby offering a scientific basis for its in-depth application in the dairy industry.展开更多
Water is an important component in agricultural production for both yield quantity and quality. Although all weather conditions are driving factors in the agricultural sector, the precipitation in rainfed agriculture ...Water is an important component in agricultural production for both yield quantity and quality. Although all weather conditions are driving factors in the agricultural sector, the precipitation in rainfed agriculture is the most limiting weather parameter. Water deficit may occur continuously over the total growing period or during any particular growth stage of the crop. Optical remote sensing is very useful but, in cloudy days it becomes useless. Radar penetrates the cloud and collects information through the backscattering data. Normalized Difference Vegetation Index (NDVI) was extracted from Landsat 8 satellite data and used to calculate Crop Coefficient (Kc). The FAO-Penman-Monteith equation was used to calculate reference evapotranspiration (ETo). NDVI and Land Surface Temperature (LST) were calculated from satellite data and integrated with air temperature measurements to estimate Crop Water Stress Index (CWSI). Then, both CWSI and potential crop evapotranspiration (ETc) were used to calculate actual evapotranspiration (ETa). Sentinel-1 radar data were calibrated using SNAP software. The relation between backscattering (dB) and CWSI was an inverse relationship and R2 was as high as 0.82.展开更多
基金supported by the grants from the project for science and technology in the Xizhang autonomous region,‘Research and development of highland probiotic resources in Shannan city’(No.QYXTCXZX-SNS.2022-2)。
文摘The target strain DB-8 in this study was isolated from naturally fermented yogurt residues in a herder’s house in Dangxiong County,Xizang.Multi-omics and genetic evolutionary analysis has been multidimensionally validated the species attribute of DB-8,revealing traits in its metabolic properties and genetic evolution in high-altitude environments.In accordance with the data obtained from the whole genome sequence and genetic evolution of DB-8,the bacterium is confirmed to be Lactobacillus delbrueckii subsp.lactis.The results of genome functional annotation demonstrated that DB-8 possesses a multitude of distinctive genes pertaining to cell wall,membrane,envelope biosynthesis,carbohydrate metabolism,and energy metabolism.Comparative genomics analysis revealed that DB-8 has 122 specific genes that support its energy metabolism,cellular repair,and biofilm systems.It is also anticipated that these genes will have exceptionally strong acid resistance.Targeted metabolic studies confirm that DB-8 produces significantly more propionic acid and isobutyric acid than other reference strains.Furthermore,based on the results of the untargeted metabolomics study,44 different metabolites were screened to create support vector machine models based on t-test-based feature screening,with an accuracy of 0.92 for the model validation set and a prediction accuracy of 100%,which marks the first successful application of machine learning to predict subspecies characterization of Lactobacillus delbrueckii.This study offers novel ideas for the precise identification between Lactobacillus delbrueckii subsp.bulgaricus and subsp.lactis,while enhancing the understanding of the fermentation characteristics of DB-8,thereby offering a scientific basis for its in-depth application in the dairy industry.
文摘Water is an important component in agricultural production for both yield quantity and quality. Although all weather conditions are driving factors in the agricultural sector, the precipitation in rainfed agriculture is the most limiting weather parameter. Water deficit may occur continuously over the total growing period or during any particular growth stage of the crop. Optical remote sensing is very useful but, in cloudy days it becomes useless. Radar penetrates the cloud and collects information through the backscattering data. Normalized Difference Vegetation Index (NDVI) was extracted from Landsat 8 satellite data and used to calculate Crop Coefficient (Kc). The FAO-Penman-Monteith equation was used to calculate reference evapotranspiration (ETo). NDVI and Land Surface Temperature (LST) were calculated from satellite data and integrated with air temperature measurements to estimate Crop Water Stress Index (CWSI). Then, both CWSI and potential crop evapotranspiration (ETc) were used to calculate actual evapotranspiration (ETa). Sentinel-1 radar data were calibrated using SNAP software. The relation between backscattering (dB) and CWSI was an inverse relationship and R2 was as high as 0.82.
