Comparison of CWSI and T_(s)-T_(a)-VIs in moisture monitoring of dryland crops(sorghum and maize)based on UAV remote sensing

Monitoring agricultural drought using remote sensing data is crucial for precision irrigation in modern agriculture.Utilizing unmanned aerial vehicle(UAV)remote sensing,we explored the applicability of an empirical crop water stress index(CWSI)based on canopy temperature and three-dimensional drought indices(TDDI)constructed from surface temperature(T_(s)),air temperature(T_(a))and five vegetation indices(VIs)for monitoring the moisture status of dryland crops.Three machine learning algorithms(random forest regression(RFR),support vector regression,and partial least squares regression)were used to compare the performance of the drought indices for vegetation moisture content(VMC)estimation in sorghum and maize.The main results of the study were as follows:(1)Comparative analysis of the drought indices revealed that T_(s)-T_(a)-normalized difference vegetation index(TDDIn)and T_(s)-T_(a)-enhanced vegetation index(TDDIe)were more strongly correlated with VMC compared with the other indices.The indices exhibited varying sensitivities to VMC under different irrigation regimes;the strongest correlation observed was for the TDDIe index with maize under the fully irrigated treatment(r=-0.93).(2)Regarding spatial and temporal characteristics,the TDDIn,TDDIe and CWSI indices showed minimal differences Over the experimental period,with coefficients of variation were 0.25,0.18 and 0.24,respectively.All three indices were capable of effectively characterizing the moisture distribution in dryland maize and sorghum crops,but the TDDI indices more accurately monitored the spatial distribution of crop moisture after a rainfall or irrigation event.(3)For prediction of the moisture content of single crops,RFR models based on TDDIn and TDDIe estimated VMC most accurately(R^(2)>0.7),and the TDDIn-based model predicted VMC with the highest accuracy when considering multiple-crop samples,with R^(2)and RMSE of 0.62 and 14.26%,respectively.Thus,TDDI proved more effective than the CWSI in estimating crop water content.

Co-overexpression of genes for nitrogen transport, assimilation, and utilization boosts rice grain yield and nitrogen use efficiency

Nitrogen(N)fertilization is necessary for obtaining high rice yield.But excessive N fertilizer reduces rice plant N efficiency and causes negative effects such as environmental pollution.In this study,we assembled key genes involved in different nodes of N pathways to boost nitrate and ammonium uptake and assimilation,and to strengthen amino acid utilization to increase grain yield and nitrogen use efficiency(NUE)in rice.The combinations OsNPF8.9a×OsNR2,OsAMT1;2×OsGS1;2×OsAS1,and OsGS2×OsAS2×OsANT3 optimized nitrate assimilation,ammonium conversion,and N reutilization,respectively.In co-overexpressing rice lines obtained by co-transformation,the tiller number,biomass,and grain yield per plant of the OsAMT1;2×OsGS1;2×OsAS1-overexpressing line exceeded those of wild-type ZH11,the OsNPF8.9a×OsNR2×OsGS1;2×OsAS1-overexpressing line,and the OsGS2×OsAS2×OsANT3-overexpressing line.The glutamine synthase activity,free amino acids,and nitrogen utilization efficiency(NUt E)of the OsAMT1;2×OsGS1;2×OsAS1-overexpressing line exceeded those of ZH11 and other lines that combined key genes.N influx efficiency was increased in the OsAMT1;2×OsGS1;2×OsAS1-overexpressing line and OsNPF8.9a×OsNR2×OsGS1;2×OsAS1-overexpressing line under a low ammonium and a low nitrate treatment,respectively.We propose that combining overexpression of OsAMT1;2,OsGS1;2,and OsAS1 is a promising breeding strategy for systematically increasing rice grain yield and NUE by focusing on key nodes in the N pathway.

Transcriptome analysis combined with metabolome analysis reveals the significant functions of CesA genes in cotton(Gossypium hirsutum)fiber length development

Cotton is widely distributed worldwide,and improving the quality of its fiber is one of the most important tasks in cotton breeding.Cotton fibers are primarily composed of cellulose,which is synthesized by CesA complexes(CSCs).However,the functions of CesA genes in cotton fiber development have not been comprehensively analysed.In this study,the cotton transcriptome and metabolome were used to investigate the function of CesA genes in fiber development.Finally,321 metabolites were obtained,84 of which were associated with the corresponding genes.Interestingly,a target gene named Gh_A08G144300,one of the CesA gene family members,was closely correlated with the development of cotton fibers.The target CesA gene Gh_A08G144300 was analysed to determine its specific function in cotton fiber development.High-level gene expression of Gh_A08G144300 was found at different fiber development stages by RNA-seq analysis,and the silencing of Gh_A08G144300 visibly inhibited the growth of cotton fibers,showing that it is critical for their growth.This study provides an important reference for research on the gene function of Gh_A08G144300 and the regulatory mechanism of fiber development in cotton.

Natural variation in MORE GRAINS 1 regulates grain number and grain weight in rice

Grain yield is determined mainly by grain number and grain weight.In this study,we identified and characterized MORE GRAINS1(MOG1),a gene associated with grain number and grain weight in rice(Oryza sativa L.),through map-based cloning.Overexpression of MOG1 increased grain yield by 18.6%-22.3%under field conditions.We determined that MOG1,a bHLH transcription factor,interacts with OsbHLH107 and directly activates the expression of LONELY GUY(LOG),which encodes a cytokinin-activating enzyme and the cell expansion gene EXPANSIN-LIKE1(EXPLA1),positively regulating grain number per panicle and grain weight.Natural variations in the promoter and coding regions of MOG1 between Hap-LNW and Hap-HNW alleles resulted in changes in MOG1 expression level and transcriptional activation,leading to functional differences.Haplotype analysis revealed that Hap-HNW,which results in a greater number and heavier grains,has undergone strong selection but has been poorly utilized in modern lowland rice breeding.In summary,the MOG1-OsbHLH107 complex activates LOG and EXPLA1 expression to promote cell expansion and division of young panicles through the cytokinin pathway,thereby increasing grain number and grain weight.These findings suggest that Hap-HNW could be used in strategies to breed high-yielding temperate japonica lowland rice.

Strigolactone and gibberellin signaling coordinately regulate metabolic adaptations to changes in nitrogen availability in rice

Modern semi-dwarf rice varieties of the“Green Revolution”require a high supply of nitrogen(N)fertilizer to produce high yields.A better understanding of the interplay between N metabolism and plant developmental processes is required for improved N-use efficiency and agricultural sustainability.Here,we show that strigolactones(SLs)modulate root metabolic and developmental adaptations to low N availability for ensuring efficient uptake and translocation of available N.The key repressor DWARF 53(D53)of the SL signaling pathway interacts with the transcription factor GROWTH-REGULATING FACTOR 4(GRF4)and prevents GRF4 from binding to its target gene promoters.N limitation induces the accumulation of SLs,which in turn promotes SL-mediated degradation of D53,leading to the release of GRF4 and thus promoting the expression of genes associated with N metabolism.N limitation also induces degradation of the DELLA protein SLENDER RICE 1(SLR1)in an D14-and D53-dependent manner,effectively releasing GRF4 from competitive inhibition caused by SLR1.Collectively,our findings reveal a previously unrecognized mechanism underlying SL and gibberellin crosstalk in response to N availability,advancing our understanding of plant growth–metabolic coordination and facilitating the design of the strategies for improving N-use efficiency in high-yield crops.

The miR167-OsARF12 module regulates rice grain filling and grain size downstream of miR159

Grain weight and quality are always determined by grain filling.Plant microRNAs have drawn attention as key targets for regulation of grain size and yield.However,the mechanisms that underlie grain size regulation remain largely unclear because of the complex networks that control this trait.Our earlier studies demonstrated that suppressed expression of miR167(STTM/MIM167)substantially increased grain weight.In a field test,the yield increased up to 12.90%-21.94% because of a significantly enhanced grain filling rate.Here,biochemical and genetic analyses revealed the regulatory effects of miR159 on miR167 expression.Further analysis indicated that OsARF12 is the major mediator by which miR167 regulates rice grain filling.Overexpression of OsARF12 produced grain weight and grain filling phenotypes resembling those of STTM/MIM167 plants.Upon in-depth analysis,we found that OsARF12 activates OsCDKF;2 expression by directly binding to the TGTCGG motif in its promoter region.Flow cytometry analysis of young panicles from OsARF12-overexpressing plants and examination of cell number in cdkf;2 mutants verified that OsARF12 positively regulates grain filling and grain size by targeting OsCDKF;2.Moreover,RNA sequencing results suggested that the miR167-OsARF12 module is involved in the cell development process and hormone pathways.OsARF12-overexpressing plants and cdkf;2 mutants exhibited enhanced and reduced sensitivity to exogenous auxin and brassinosteroid(BR)treatment,confirming that targeting of OsCDKF;2 by OsARF12 mediates auxin and BR signaling.Our results reveal that the miR167-OsARF12 module works downstream of miR159 to regulate rice grain filling and grain size via OsCDKF;2 by controlling cell division and mediating auxin and BR signals.

A Resource for Inactivation of MicroRNAs Using Short Tandem Target Mimic Technology in Model and Crop Plants

microRNAs (miRNAs)are endogenous small non-coding RNAs that bind to mRNAs and target them for cleavage and/or translational repression,leading to gene silencing.We previously developed short tandem target mimic (STTM)technology to deactivate endogenous miRNAs in Arabidopsis.Here,we created hundreds of STTMs that target both conserved and species-specific miRNAs in Arabidopsis,tomato,rice,and maize,providing a resource for the functional interrogation of miRNAs.We not only revealed the functions of several miRNAs in plant development,but also demonstrated that tissue-specific inactivation of a few miRNAs in rice leads to an increase in grain size without adversely affecting overall plant growth and development.RNA-seq and small RNAseq analyses of STTM156/157 and STTM165/166 transgenic plants revealed the roles of these miRNAs in plant hormone biosynthesis and activation,secondary metabolism,and ion-channel activity-associated electrophysiology,demonstrating that STTM technology is an effective approach for studying miRNA functions.To facilitate the study and application of STTM transgenic plants and to provide a useful platform for storing and sharing of information about miRNA-regulated gene networks,we have established an online Genome Browser (https://blossom.ffr.mtu.edu/designindex2.php) to display the transcriptomic and miRNAomic changes in STTMinduced miRNA knockdown plants.