Small auxin up RNA (SAUR) is a large gene family that is widely distributed among land plants.  In this study, a comprehensive analysis of the SAUR family was performed in sweet cherry, and the potential biological functions of PavSAUR55 were identified using the method of genetic transformation.  The sweet cherry genome encodes 86 SAUR members, the majority of which are intron-less.  These genes appear to be divided into seven subfamilies through evolution.  Gene duplication events indicate that fragment duplication and tandem duplication events occurred in the sweet cherry.  Most of the members mainly underwent purification selection pressure during evolution.  During fruit development, the expression levels of PavSAUR16/45/56/63 were up-regulated, and conversely, those of PavSAUR12/61 were down-regulated.  Due to the significantly differential expressions of PavSAUR13/16/55/61 during the fruitlet abscission process, they might be the candidate genes involved in the regulation of physiological fruit abscission in sweet cherry.  Overexpression of PavSAUR55 in Arabidopsis produced earlier reproductive growth, root elongation, and delayed petal abscission.  In addition, this gene did not cause any change in the germination time of seeds and was able to increase the number of lateral roots under abscisic acid (ABA) treatment.  The identified SAURs of sweet cherry play a crucial role in fruitlet abscission and will facilitate future insights into the mechanism underlying the heavy fruitlet abscission that can occur in this fruit crop.

Increasing wheat yield is a long-term goal for wheat breeders around the world.  Exploiting elite genetic resources and dissecting the genetic basis of important agronomic traits in wheat are the necessary methods for high-yield wheat breeding.  This study evaluated nine crucial agronomic traits found in a natural population of 156 wheat varieties and 77 landraces from Sichuan, China in seven environments over two years.  The results of this investigation of agronomic traits showed that the landraces had more tillers and higher kernel numbers per spike (KNS), while the breeding varieties had higher thousand-kernel weight (TKW) and kernel weight per spike (KWS).  The generalized heritability (H²) values of the nine agronomic traits varied from 0.74 to 0.95.  Structure analysis suggested that the natural population could be divided into three groups using 43 198 single nucleotide polymorphism (SNP) markers from the wheat 55K SNP chip.  A total of 67 quantitative trait loci (QTLs) were identified by the genome-wide association study (GWAS) analysis based on the Q+K method of a mixed linear model.  Three important QTLs were analyzed in this study.  Four haplotypes of QFTN.sicau-7BL.1 for fertile tillers number (FTN), three haplotypes of QKNS.sicau-1AL.2 for KNS, and four haplotypes of QTKW.sicau-3BS.1 for TKW were detected.  FTN-Hap2, KNS-Hap1, and TKW-Hap2 were excellent haplotypes for each QTL based on the yield performance of 42 varieties in regional trials from 2002 to 2013.  The varieties with all three haplotypes showed the highest yield compared to those with either two haplotypes or one haplotype.  In addition, the KASP-AX-108866053 marker of QTL QKNS.sicau-1AL.2 was successfully distinguished between three haplotypes (or alleles) in 63 varieties based on the number of kernels per spike in regional trials between 2018 and 2021.  These genetic loci and reliable makers can be applied in marker-assisted selection or map-based gene cloning for the genetic improvement of wheat yield. 

The research aimed to understand farmers’ willingness to adopt (WTA) and willingness to pay (WTP) for precision pesticide technologies and analyzed the determinants of farmers’ decision-making.  We used a two-stage approach to consider farmers’ WTA and WTP for precision pesticide technologies.  A survey of 545 apple farmers was administered in Bohai Bay and the Loess Plateau in China.  The data were analyzed using the double-hurdle model.  The results indicated that 78.72% of respondents were willing to apply precision pesticide technologies provided by service organizations such as cooperatives and dedicated enterprises, and 69.72% were willing to buy the equipment for using precision pesticide technologies.  The results of the determinant analysis indicated that farmers’ perceived perceptions, farm scale, cooperative membership, access to digital information, and availability of financial services had significant and positive impacts on farmers’ WTA precision pesticide technologies.  Cooperative membership, technical training, and adherence to environmental regulations increased farmers’ WTP for precision pesticide technologies.  Moreover, nonlinear relationships between age, agricultural experience, and farmers’ WTA and WTP for precision pesticide technology services were found.

Milling and appearance quality are important contributors to rice grain quality.  Abundant genetic diversity and a suitable environment are crucial for rice improvement.  In this study, we investigated the milling and appearance quality-related traits in a panel of 200 japonica rice cultivars selected from Liaoning, Jilin and Heilongjiang provinces in Northeast China.  Pedigree assessment and genetic diversity analysis indicated that cultivars from Jilin harbored the highest genetic diversity among the three geographic regions.  An evaluation of grain quality indicated that cultivars from Liaoning showed superior milling quality, whereas cultivars from Heilongjiang tended to exhibit superior appearance quality.  Single- and multi-locus genome-wide association studies (GWAS) were conducted to identify loci associated with milling and appearance quality-related traits.  Ninety-nine significant single-nucleotide polymorphisms (SNPs) were detected.  Three common SNPs were detected using the mixed linear model (MLM), mrMLM, and FASTmrMLM methods.  Linkage disequilibrium decay was estimated and indicated three candidate regions (qBRR-1, qBRR-9 and qDEC-3) for further candidate gene analysis.  More than 300 genes were located in these candidate regions.  Gene Ontology (GO) analysis was performed to discover the potential candidate genes.  Genetic diversity analysis of the candidate regions revealed that qBRR-9 may have been subject to strong selection during breeding.  These results provide information that will be valuable for the improvement of grain quality in rice breeding.

Viral diseases are among the most critical damaging factors that impose a global threat to the cucurbit industry.  China is the world’s leading country for the production and consumption of cucurbits.  Guangdong, a province in southern China dominated by the tropical and subtropical climate, favors the survival of different plant viruses and their vectors.  Five main cucurbit crops showing various disease symptoms were surveyed and collected to identify viruses infecting cucurbits in Guangdong during 2018–2020.  In the field, the incidence ranged from 5–30%, or even 60–100% in the case of severely infected cucurbits.  A total of 357 symptomatic samples were collected and subsequently screened for cucurbit viruses by small RNA deep sequencing and assembly (sRSA).  Seventeen virus species belonging to 10 genera were identified in the five main cucurbit crops.  The most common viruses were papaya ringspot virus (PRSV; Potyvirus), zucchini tigre mosaic virus (ZTMV; Potyvirus), zucchini yellow mosaic virus (ZYMV; Potyvirus), and watermelon silver mottle virus (WSMoV; Orthotospovirus), with infection rates of 24.4, 19.0, 17.1, and 14.3%, respectively.  Notably, the most prevalent viruses were melon yellow spot orthotospovirus (MYSV) in cucumber, PRSV in squash, cucumber green mottle mosaic virus (CGMMV; Tobamovirus) in bottle gourd, WSMoV in white gourd, and ZYMV in luffa.  Mixed infections were prevalent, and the types of mixed infections varied substantially in different cucurbit crops.  Moreover, the full-length nucleotide sequences of watermelon green mottle mosaic virus (WGMMV), CGMMV, and watermelon virus A (WVA; Wamavirus) identified in bottle gourd were cloned and analyzed.  This study is the first reporting WGMMV infecting bottle gourd in China mainland.  In summary, the results demonstrate that in Guangdong, the most prevalent viruses belong to potyviruses, orthotospoviruses, and tobamoviruses groups.  The findings will facilitate agricultural researchers and farmers to plan and implement effective disease control strategies aiming at timely detection and management of cucurbit-infecting viral pathogens.

Sugar transporters are essential for osmotic process regulation, various signaling pathways and plant growth and development.  Currently, few studies are available on the function of sugar transporters in sorghum (Sorghum bicolor L.).  In this study, we performed a genome-wide survey of sugar transporters in sorghum.  In total, 98 sorghum sugar transporters (SSTs) were identified via BLASTP.  These SSTs were classified into three families based on the phylogenetic and conserved domain analysis, including six sucrose transporters (SUTs), 23 sugars will eventually be exported transporters (SWEETs), and 69 monosaccharide transporters (MSTs).  The sorghum MSTs were further divided into seven subfamilies, including 24 STPs, 23 PLTs, two VGTs, four INTs, three pGlcT/SBG1s, five TMTs, and eight ERDs.  Chromosomal localization of the SST genes showed that they were randomly distributed on 10 chromosomes, and substantial clustering was evident on the specific chromosomes.  Twenty-seven SST genes from the families of SWEET, ERD, STP, and PLT were found to cluster in eight tandem repeat event regions.  In total, 22 SSTs comprising 11 paralogous pairs and accounting for 22.4% of all the genes were located on the duplicated blocks.  The different subfamilies of SST proteins possessed the same conserved domain, but there were some differences in features of the motif and transmembrane helices (TMH).  The publicly-accessible RNA-sequencing data and real-time PCR revealed that the SST genes exhibited distinctive tissue specific patterns.  Functional studies showed that seven SSTs were mainly located on the cell membrane and membrane organelles, and 14 of the SSTs could transport different types of monosaccharides in yeast.  These findings will help us to further elucidate their roles in the sorghum sugar transport and sugar signaling pathways.

A crop growth model, integrating genotype, environment, and management factor, was developed to serve as an analytical tool to study the influence of these factors on crop growth, production, and agricultural planning.  A major challenge of model application is the optimization and calibration of a considerable number of parameters.  Sensitivity analysis (SA) has become an effective method to identify the importance of various parameters.  In this study, the extended Fourier Amplitude Sensitivity Test (EFAST) approach was used to evaluate the sensitivity of the DSSAT-CERES model output responses of interest to 39 crop genotype parameters and six soil parameters.  The outputs for the SA included grain yield and quality (take grain protein content (GPC) as an indicator) at maturity stage, as well as leaf area index, aboveground biomass, and aboveground nitrogen accumulation at the critical process variables.  The key results showed that: (1) the influence of parameter bounds on the sensitivity results was slight and less than the impacts from the significance of the parameters themselves; (2) the sensitivity parameters of grain yield and GPC were different, and the sensitivity of the interactions between parameters to GPC was greater than those between the parameters to grain yield; and (3) the sensitivity analyses of some process variables, including leaf area index, aboveground biomass, and aboveground nitrogen accumulation, should be performed differently.  Finally, some parameters, which improve the model’s structure and the accuracy of the process simulation, should not be ignored when maturity output as an objective variable is studied.

Ovine bones are the major by-products after slaughtered.  The present study was conducted to extract and characterize acid soluble collagens (ASC) and pepsin soluble collagens (PSC) from ovine bones (Ujumuqin sheep).  Ovine bones collagen were identified by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) as type I collagen.  The results of Fourier transform infrared (FTIR) spectra analysis testified the existence of triple superhelical structure in both ASC and PSC, showing pepsin did not disrupt the triple helical structure of ovine bones collagen.  Glycine, accounting for one-third of total amino acids, was the major amino acid for ovine bones collagen.  Higher imino acid content was responsible for higher thermal denaturation temperature of ovine bones collagen compared to fish collagens.  The isoelectric point of ASC was lower than PSC due to the higher content of acidic amino acids.  Therefore, this study provides the potential reference for collagen extraction and application of ovine bones by-procduct.

This study investigated the influence of activities of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and lactate dehydrogenase-B (LDH-B) on the colour stability of mutton.  From 60 sheep (Bayannur mutton sheep), 15 longissimus dorsi (LD) muscles were selected on the basis of colour stability (R630/580 and a* value) during the storage and classified into three groups (5 for each group) as high colour stability (HCS), intermediate colour stability (ICS) and low colour stability (LCS).  The activities of GAPDH and LDH-B, muscle colour attributes, nicotinamide adenine dinucleuotide (NADH) concentration and lactate concentration were measured.  The samples in HCS had higher activities of GAPDH and LDH-B than the samples in the LCS, and the samples in the HCS group also possessed higher NADH and lower lactate concentration.  The higher activity of dehydrogenase enzyme may result in higher NADH concentrations and colour stability in muscle tissue.  The results suggest that the activity of GAPDH and LDH-B may also play a role in maintaining colour stability.

Sensitivity analysis (SA) is an effective tool for studying crop models; it is an important link in model localization and plays an important role in crop model calibration and application.  The objectives were to (i) determine influential and non-influential parameters with respect to above ground biomass (AGB), canopy cover (CC), and grain yield of winter wheat in the Beijing area based on the AquaCrop model under different water treatments (rainfall, normal irrigation, and over-irrigation); and (ii) generate an AquaCrop model that can be used in the Beijing area by setting non-influential parameters to fixed values and adjusting influential parameters according to the SA results.  In this study, field experiments were conducted during the 2012–2013, 2013–2014, and 2014–2015 winter wheat growing seasons at the National Precision Agriculture Demonstration Research Base in Beijing, China.  The extended Fourier amplitude sensitivity test (EFAST) method was used to perform SA of the AquaCrop model using 42 crop parameters, in order to verify the SA results, data from the 2013–2014 growing season were used to calibrate the AquaCrop model, and data from 2012–2013 and 2014–2015 growing seasons were validated.  For AGB and yield of winter wheat, the total order sensitivity analysis had more sensitive parameters than the first order sensitivity analysis.  For the AGB time-series, parameter sensitivity was changed under different water treatments; in comparison with the non-stressful conditions (normal irrigation and over-irrigation), there were more sensitive parameters under water stress (rainfall), while root development parameters were more sensitive.  For CC with time-series and yield, there were more sensitive parameters under water stress than under no water stress.  Two parameters sets were selected to calibrate the AquaCrop model, one group of parameters were under water stress, and the others were under no water stress, there were two more sensitive parameters (growing degree-days (GDD) from sowing to the maximum rooting depth (root) and the maximum effective rooting depth (rtx)) under water stress than under no water stress.  The results showed that there was higher accuracy under water stress than under no water stress.  This study provides guidelines for AquaCrop model calibration and application in Beijing, China, as well providing guidance to simplify the AquaCrop model and improve its precision, especially when many parameters are used.  

Rice area has been expanding rapidly during the past 30 years under the influence of global change in northeastern China, which is the northernmost region of rice cultivation in China.  However, the spatio-temporal dynamic changes in rice area are still unclear, although they may have important policy implications for environmental protection and adaptation to climate change.  In this study, we aimed to identify the dynamic changes of the rice area in Heilongjiang Province of northeastern China by extracting data from multiple Landsat images.  The study used ground quadrats selected from Google Earth and the extraction of a confusion matrix to verify the accuracy of extraction.  The overall accuracy of the extracted rice area was higher than 95% as a result of using the artificial neural network (ANN) classification method.  The results showed that the rice area increased by approximately 2.4×10⁶ ha during the past 30 years at an annual rate of 8.0×10⁴ ha, and most of the increase occurred after 2000.  The central latitude of the rice area shifted northwards from 46 to 47°N during the study period, and moved eastwards from 130 to 133°E.  The rice expansion area accounted for 98% of the total change in rice area, and rice loss was notably rare.  The rice expansion was primarily from dryland.  In addition, rice cultivation in marshland and grassland played a minor role in the rice expansion in this region.

Leaf area index (LAI) is a key parameter for describing vegetation structures and is closely associated with vegetative photosynthesis and energy balance.  The accurate retrieval of LAI is important when modeling biophysical processes of vegetation and the productivity of earth systems.  The Random Forests (RF) method aggregates an ensemble of decision trees to improve the prediction accuracy and demonstrates a more robust capacity than other regression methods.  This study evaluated the RF method for predicting grassland LAI using ground measurements and remote sensing data. 
Parameter optimization and variable reduction were conducted before model prediction.  Two variable reduction methods were examined: the Variable Importance Value method and the principal component analysis (PCA) method.  Finally, the sensitivity of RF to highly correlated variables was tested.  The results showed that the RF parameters have a small effect on the performance of RF, and a satisfactory prediction was acquired with a root mean square error (RMSE) of 0.1956.  The two variable reduction methods for RF prediction produced different results; variable reduction based on the Variable Importance Value method achieved nearly the same prediction accuracy with no reduced prediction, whereas variable reduction using the PCA method had an obviously degraded result that may have been caused by the loss of subtle variations and the fusion of noise information.  After removing highly correlated variables, the relative variable importance remained steady, and the use of variables selected based on the best-performing vegetation indices performed better than the variables with all vegetation indices or those selected based on the most important one.  The results in this study demonstrate the practical and powerful ability of the RF method in predicting grassland LAI, which can also be applied to the estimation of other vegetation traits as an alternative to conventional empirical regression models and the selection of relevant variables used in ecological models.

    Carboxylesterase is a multifunctional superfamily and can be found in almost all living organisms. As the metabolic enzymes, carboxylesterases are involved in insecticides resistance in insects for long time. In our previous studies, the enhanced carboxylesterase activities were found in the chlorantraniliprole resistance strain of diamondback moth (DBM). However, the related enzyme gene of chlorantraniliprole resistance has not been clear in this strain. Here, a full-length cDNA of carboxylesterase pxCCE016b was cloned and exogenously expressed in Escherichia coli at the first time, which contained a 1 693 bp open reading frame (ORF) and encoded a protein of 542 amino acids. Sequence analysis showed that this cDNA has a predicted mass of 61.56 kDa and a theoretical isoelectric point value of 5.78. The sequence of deduced amino acid possessed the classical structural features: a type-B carboxylesterase signature 2 (EDCLYLNVYTK), a type-B carboxylesterase serine active site (FGGDPENITIFGESAG) and the catalytic triad (Ser186, Glu316, and His444). The real-time quantitative PCR (qPCR) analysis showed that the expression level of the pxCCE016b was significantly higher in the chlorantraniliprole resistant strain than in the susceptible strain. Furthermore, pxCCE016b was highly expressed in the midgut and epidermis of the DBM larvae. When the 3rd-instar larvae of resistant DBM were exposed to abamectin, alpha-cypermethrin, chlorantraniliprole, spinosad, chlorfenapyr and indoxacarb insecticides, the up-regulated expression of pxCCE016b was observed only in the group treated by chlorantraniliprole. In addition, recombinant vector pET-pxCCE016b was constructed with the most coding region (1 293 bp) and large number of soluble recombinant proteins (less than 48 kDa) were expressed successfully with prokaryotic cell. Western blot analysis showed that it was coded by pxCCE016b. All the above findings provide important information for further functional study, although we are uncertainty whether the pxCCE016b gene is actually involved in chlorantraniliprole resistance.

A novel phytoplasma was detected in a cherry plum (Prunus cerasifera Ehrh) tree that mainly showed yellow leaf symptom. The tree was growing in an orchard located in Yangling District, Shaanxi Province, China. The leaves started as chlorotic and yellowing along leaf minor veins and leaf tips. Chlorosis rapidly developed to inter-veinal areas with the whole leaf becoming pale yellow in about 1-4 wk. Large numbers of phytoplasma-like bodies (PLBs) were seen under transmission electron microscopy. The majority of the PLBs was spherical or elliptical vesicles, with diameters in range of 0.1-0.6 μm, and distributed in the phloem cells of the infected tissues. A 1246-bp 16S ribosomal RNA (rRNA) gene fragment was amplified from DNA samples extracted from the yellow leaf tissues using two phytoplasma universal primer pairs R16mF2/R16mR1 and R16F2n/R16R2. Phylogenetic analysis using the 16S rRNA gene sequence suggested that the phytoplasma associated with the yellow leaf symptoms belongs to a novel subclade in the aster yellows (AY) group (16SrI group). Virtual and actual restriction fragment length polymorphism (RFLP) analysis of the 16S rRNA gene fragment revealed that the phytoplasma was distinguishable from all existing 19 subgroups in the AY group (16SrI) by four restriction sites, Hinf I, Mse I, Sau3A I and Taq I. The similarity coefficients of comparing the RFLP pattern of the 16S rRNA gene fragment of this phytoplasma to each of the 19 reported subgroups ranged from 0.73 to 0.87, which indicates the phytoplasma associated with the cherry plum yellow leaf (CPYL) symptoms is probably a distinct and novel subgroup lineage in the AY group (16SrI). In addition, the novel phytoplasma was experimentally transmitted to periwinkle (Catharanthus roseus) plants from the tree with CPYL symptoms and then back to a healthy 1-yr-old cherry plum tree via dodder (Cuscuta odorata) connections.

For the scientific management of farmland, it is significant to understand the spatio-temporal variability of soil organic matter and to study the influences of related factors. Using geostatistical theory, GIS spatial analysis, trend analysis and a Geographically Weighted Regression (GWR) model, this study analyzed the response of soil organic matter to climate and socio-economic factors in central Heilongjiang Province during the past 25 years. Second soil survey data of China for 1979-1985, 2005 field sampling data, climate observations and socio-economic data for 1980-2005 were analyzed. First, soil organic matter in 2005 was spatially interpolated using the Co-Kriging method along with auxiliary data sets of soil type and pH. The spatio-temporal variability was then studied by comparison with the 1980s second soil census data. Next, the temporal trends in climate and socio-economic factors over the past 25 years were investigated. Finally, we examined the variation of the response of soil organic matter to climate and socio-economic factors using the GWR model spatially and temporally. The model showed that 53.82% area of the organic matter content remained constant and 29.39% has decreased during the past 25 years. The impact of precipitation on organic matter content is mainly negative, with increasing absolute values of the regression coefficient. The absolute value of regression coefficient of annual average temperature has decreased, and more areas are now under its negative effects. In addition, the areas of positive regression coefficient of annual sunshine hours have northward shifted, with the increasing absolute value of positive coefficient and decreasing absolute value of negative coefficient. The areas of positive regression coefficient of mechanized farming as a socio-economic factor have westward shifted, with the increasing absolute value of negative coefficient and decreasing absolute value of positive coefficient. The area of regions with the positive regression coefficient of irrigation has expanded. The regions with positive regression coefficient of fertilizer use have shrinked. The positive regression coefficient of mulch film consumption has significantly increased. The regression coefficient of pesticide consumption was mainly positive in the west of the study area, while it was negative to the east. Generally, GWR model is capable to investigate the influence of both climatic and socio-economic factors, avoided the insufficiency of other research based on the single perspective of climatic or socio-economic factors. Therefore, we can conclude that GWR model could provide methodological support for global change research and serve as basic reference for cultivated land quality improvement and agricultural decision making.

The insecticide chlorantraniliprole exhibits good efficacy and plays an important role in controlling the diamondback moth, Plutella xylostella Linnaeus. However, resistance to chlorantraniliprole has been observed recently in some field populations. At present study, diamondback moths with resistance to chlorantraniliprole (resistant ratio (RR) was 82.18) for biochemical assays were selected. The assays were performed to determine potential resistance mechanisms. The results showed that the selected resistant moths (GDLZ-R) and susceptible moth could be synergized by known metabolic inhibitors such as piperonyl butoxide (PBO), triphenyl phosphate (TPP) and diethyl-maleate (DEM) at different levels (1.68-5.50-fold and 2.20-2.89-fold, respectively), and DEM showed the maximum synergism in both strains. In enzymes assays, a high level of glutathione-S-transferase (GST) was observed in the resistant moth, in contrast, moths that are susceptible to the insecticide had only 1/3 the GST activity of the resistant moths. The analysis of short-term exposure of chlorantraniliprole on biochemical response in the resistant strain also showed that GST activity was significantly elevated after exposure to a sub-lethal concentration of chlorantraniliprole (about 1/3 LC50, 12 mg L-1) 12 and 24 h, respectively. The results show that there is a strong correlation between the enzyme activity and resistance, and GST is likely the main detoxification mechanism responsible for resistance to chlorantraniliprole in P. xylostella L., cytochrome P450 monooxygenase (P450) and carboxy-lesterase (CarE) are involved in to some extent.