Salicylic acid(SA) plays a pivotal role in delaying fruit ripening and senescence. However, little is known about its underlying mechanism of action. In this study, RNA sequencing was conducted to analyze and compare ...Salicylic acid(SA) plays a pivotal role in delaying fruit ripening and senescence. However, little is known about its underlying mechanism of action. In this study, RNA sequencing was conducted to analyze and compare the transcriptome profiles of SA-treated and control pear fruits. We found a total of 159 and 419 genes differentially expressed between the SA-treated and control pear fruits after 12 and 24 h of treatment, respectively. Among these differentially expressed genes(DEGs), 125 genes were continuously differentially expressed at both treatment times, and they were identified as candidate genes that might be associated with SA-regulated fruit ripening and senescence. Bioinformatics analysis results showed that 125 DEGs were mainly associated with plant hormone biosynthesis and metabolism, cell wall metabolism and modification, antioxidant systems, and senescence-associated transcription factors. Additionally, the expression of several candidate DEGs in ripening and senescent pear fruits after SA treatments were further validated by quantitative real-time PCR(qRT-PCR). This study provides valuable information and enhances the understanding of the comprehensive mechanisms of SA-meditated pear fruit ripening and senescence.展开更多
The aim of this study was to establish the applicability of near-infrared reflectance spectroscopy(NIRS)as a rapid method for the accurate estimation of nutrient components in agricultural soils.Focusing on the soil o...The aim of this study was to establish the applicability of near-infrared reflectance spectroscopy(NIRS)as a rapid method for the accurate estimation of nutrient components in agricultural soils.Focusing on the soil of the Sanjiang Plain,NIRS was used to predict soil organic matter(SOM),the total nitrogen(TN)and the total phosphorus(TP).A total of 540 samples were collected from the three different depths(180 samples from each depth:0-10,10-20 and 20-30 cm),from 2015 to 2017,from the Sanjiang Plain in Heilongjiang Province,China.From every depth,120 samples were used to construct the calibration set.Other 60 samples were used to check the efficiency of the model.Combining the first-order differentiation with the partial least square(PLS)method,a prediction model was obtained to measure SOM,TN and TP.The correlation coefficient of SOM from 0 to 10 cm was R2=0.9567,from 10 to 20 cm was R2=0.9416,and from 20 to 30 cm was R2=0.9402.The corresponding ratio(standard deviation[SD]/root mean square error of prediction[RMSEP])was>2.96.R2 of TN with the three depths was 0.9154,0.9028 and 0.9024,respectively,all with SD/RMSEP>2.89.Meanwhile,R2 of TP with the three depths was 0.8974,0.8624 and 0.7804,respectively,all with SD/RMSEP>2.50.These results demonstrated that NIRS based on the first-order differentiation and PLS could efficiently predict SOM,TN and TP from different soil depths.展开更多
基金supported by the National Natural Science Foundation of China (31301761)the China Scholarship Council (201608130248)the Second Round of the Youth Top-Notch Talent Support Programs of Hebei Province, China (2019)。
文摘Salicylic acid(SA) plays a pivotal role in delaying fruit ripening and senescence. However, little is known about its underlying mechanism of action. In this study, RNA sequencing was conducted to analyze and compare the transcriptome profiles of SA-treated and control pear fruits. We found a total of 159 and 419 genes differentially expressed between the SA-treated and control pear fruits after 12 and 24 h of treatment, respectively. Among these differentially expressed genes(DEGs), 125 genes were continuously differentially expressed at both treatment times, and they were identified as candidate genes that might be associated with SA-regulated fruit ripening and senescence. Bioinformatics analysis results showed that 125 DEGs were mainly associated with plant hormone biosynthesis and metabolism, cell wall metabolism and modification, antioxidant systems, and senescence-associated transcription factors. Additionally, the expression of several candidate DEGs in ripening and senescent pear fruits after SA treatments were further validated by quantitative real-time PCR(qRT-PCR). This study provides valuable information and enhances the understanding of the comprehensive mechanisms of SA-meditated pear fruit ripening and senescence.
基金Supported by the National Natural Science Foundation(31802120)Research and Demonstration of Large-scale Artificial Grassland Combined Plant and Circular Mode(2017YFD0502106)Academic Backbone Fund Project of Northeast Agricultural University。
文摘The aim of this study was to establish the applicability of near-infrared reflectance spectroscopy(NIRS)as a rapid method for the accurate estimation of nutrient components in agricultural soils.Focusing on the soil of the Sanjiang Plain,NIRS was used to predict soil organic matter(SOM),the total nitrogen(TN)and the total phosphorus(TP).A total of 540 samples were collected from the three different depths(180 samples from each depth:0-10,10-20 and 20-30 cm),from 2015 to 2017,from the Sanjiang Plain in Heilongjiang Province,China.From every depth,120 samples were used to construct the calibration set.Other 60 samples were used to check the efficiency of the model.Combining the first-order differentiation with the partial least square(PLS)method,a prediction model was obtained to measure SOM,TN and TP.The correlation coefficient of SOM from 0 to 10 cm was R2=0.9567,from 10 to 20 cm was R2=0.9416,and from 20 to 30 cm was R2=0.9402.The corresponding ratio(standard deviation[SD]/root mean square error of prediction[RMSEP])was>2.96.R2 of TN with the three depths was 0.9154,0.9028 and 0.9024,respectively,all with SD/RMSEP>2.89.Meanwhile,R2 of TP with the three depths was 0.8974,0.8624 and 0.7804,respectively,all with SD/RMSEP>2.50.These results demonstrated that NIRS based on the first-order differentiation and PLS could efficiently predict SOM,TN and TP from different soil depths.
