Drought is an important abiotic stress factor in cotton production.The root system architecture(RSA)of cotton shows high plasticity which can alleviate drought-related stress under drought stress(DS)conditions;however...Drought is an important abiotic stress factor in cotton production.The root system architecture(RSA)of cotton shows high plasticity which can alleviate drought-related stress under drought stress(DS)conditions;however,this alleviation is cultivar dependent.Therefore,this study estimated the genetic variability of RSA in cotton under DS.Using the paper-based growth system,we assessed the RSA variability in 80 cotton cultivars at the seedling stage,with 0 and10%polyethylene glycol 6000(PEG6000)as the control(CK)and DS treatment,respectively.An analysis of 23 aboveground and root traits in the 80 cotton cultivars revealed different responses to DS.On the 10th day after DS treatment,the degree of variation in the RSA traits under DS(5–55%)was greater than that of CK(5–49%).The 80 cultivars were divided into drought-tolerant cultivars(group 1),intermediate drought-tolerant cultivars(group 2),and drought-sensitive cultivars(group 3)based on their comprehensive evaluation values of drought resistance.Under DS,the root lengthlower,root area-lower,root volume-lower,and root length density-lower were significantly reduced by 63,71,76,and 4%in the drought-sensitive cultivars compared to CK.Notably,the drought-tolerant cultivars maintained their root lengthlower,root area-lower,root volume-lower,and root length density–lower attributes.Compared to CK,the root diameter(0–2 mm)-lower increased by 21%in group 1 but decreased by 3 and 64%in groups 2 and 3,respectively,under DS.Additionally,the drought-tolerant cultivars displayed a plastic response under DS that was characterized by an increase in the root-lower characteristics.Drought resistance was positively correlated with the root area-lower and root length density-lower.Overall,the RSA of the different cotton cultivars varied greatly under DS.Therefore,important root traits,such as the root-lower traits,provide great insights for exploring whether drought-tolerant cotton cultivars can effectively withstand adverse environments.展开更多
Plant height and above-ground biomass are important growth parameters that affect crop yield.Efficient and non-destructive technologies of crop phenotypic monitoring play crucial roles in intelligent farmland manageme...Plant height and above-ground biomass are important growth parameters that affect crop yield.Efficient and non-destructive technologies of crop phenotypic monitoring play crucial roles in intelligent farmland management.However,the feasibility of using these technologies to estimate cotton plant height and above-ground biomass has not been determined.This study proposed a low cost and high-throughput imaging method combined with Canopeo to extract the percentages of green color from high-definition digital images and establish a model to estimate the cotton plant height and above-ground biomass.The plant height and above-ground biomass field trials were conducted at two levels of irrigation(soil water content 70%±5% and 40%-45%,respectively)using 80 cotton genotypes.The linear fitting performed well across the different cotton genotypes(PH,R^(2)=0.9829;RMSE=2.4 cm;NRMSE=11%and AGB,R^(2)=0.9609;RMSE=0.6 g/plant;and NRMSE=5%),and two levels of irrigation(PH,R^(2)=0.9604;RMSE=2.15 cm;NRMSE=6%and AGB,R^(2)=0.9650;RMSE=4.51 g/plant;and NRMSE=17%).All reached a higher fitting degree.Additionally,the most comprehensive model to estimate the cotton plant height and above-ground biomass(Y=0.4832*X+11.04;Y=0.4621*X-0.3591)was determined using a simple linear regression modeling method.The percentages of green color positively correlated with plant height and above-ground biomass,and each model exhibited higher accuracy(R2≥0.8392,RMSE≤0.0158,NRMSE≤0.06%).Combining a high-definition digital camera with Canopeo enables the prediction of crop growth in the field.The simple linear regression modeling method and the most comprehensive model enable the rapid estimation of the cotton plant height and above-ground biomass.This method can also be used as a baseline to measure other important crop phenotypes.展开更多
H-tensor is a new developed concept which plays an important role in tensor analysis and computing. In this paper, we explore the properties of H-tensors and establish some new criteria for strong H-tensors. In partic...H-tensor is a new developed concept which plays an important role in tensor analysis and computing. In this paper, we explore the properties of H-tensors and establish some new criteria for strong H-tensors. In particular, based on the principal subtensor, we provide a new necessary and sufficient condition of strong H-tensors, and based on a type of generalized diagonal product dominance, we establish some new criteria for identifying strong H-tensors. The results obtained in this paper extend the corresponding conclusions for strong H-matrices and improve the existing results for strong H-tensors.展开更多
基金the National Natural Science Foundation of China(31871569 and 32172120)the Natural Science Foundation of Hebei Province,China(C2020204066)。
文摘Drought is an important abiotic stress factor in cotton production.The root system architecture(RSA)of cotton shows high plasticity which can alleviate drought-related stress under drought stress(DS)conditions;however,this alleviation is cultivar dependent.Therefore,this study estimated the genetic variability of RSA in cotton under DS.Using the paper-based growth system,we assessed the RSA variability in 80 cotton cultivars at the seedling stage,with 0 and10%polyethylene glycol 6000(PEG6000)as the control(CK)and DS treatment,respectively.An analysis of 23 aboveground and root traits in the 80 cotton cultivars revealed different responses to DS.On the 10th day after DS treatment,the degree of variation in the RSA traits under DS(5–55%)was greater than that of CK(5–49%).The 80 cultivars were divided into drought-tolerant cultivars(group 1),intermediate drought-tolerant cultivars(group 2),and drought-sensitive cultivars(group 3)based on their comprehensive evaluation values of drought resistance.Under DS,the root lengthlower,root area-lower,root volume-lower,and root length density-lower were significantly reduced by 63,71,76,and 4%in the drought-sensitive cultivars compared to CK.Notably,the drought-tolerant cultivars maintained their root lengthlower,root area-lower,root volume-lower,and root length density–lower attributes.Compared to CK,the root diameter(0–2 mm)-lower increased by 21%in group 1 but decreased by 3 and 64%in groups 2 and 3,respectively,under DS.Additionally,the drought-tolerant cultivars displayed a plastic response under DS that was characterized by an increase in the root-lower characteristics.Drought resistance was positively correlated with the root area-lower and root length density-lower.Overall,the RSA of the different cotton cultivars varied greatly under DS.Therefore,important root traits,such as the root-lower traits,provide great insights for exploring whether drought-tolerant cotton cultivars can effectively withstand adverse environments.
基金supported by grants from the National Natural Science Foundation of China(No.31871569 and No.32172120)Natural Science Foundation of Hebei Province(C2020204066)the Modern System of Agricultural Technology in Hebei Province(No.HBCT2018040201).
文摘Plant height and above-ground biomass are important growth parameters that affect crop yield.Efficient and non-destructive technologies of crop phenotypic monitoring play crucial roles in intelligent farmland management.However,the feasibility of using these technologies to estimate cotton plant height and above-ground biomass has not been determined.This study proposed a low cost and high-throughput imaging method combined with Canopeo to extract the percentages of green color from high-definition digital images and establish a model to estimate the cotton plant height and above-ground biomass.The plant height and above-ground biomass field trials were conducted at two levels of irrigation(soil water content 70%±5% and 40%-45%,respectively)using 80 cotton genotypes.The linear fitting performed well across the different cotton genotypes(PH,R^(2)=0.9829;RMSE=2.4 cm;NRMSE=11%and AGB,R^(2)=0.9609;RMSE=0.6 g/plant;and NRMSE=5%),and two levels of irrigation(PH,R^(2)=0.9604;RMSE=2.15 cm;NRMSE=6%and AGB,R^(2)=0.9650;RMSE=4.51 g/plant;and NRMSE=17%).All reached a higher fitting degree.Additionally,the most comprehensive model to estimate the cotton plant height and above-ground biomass(Y=0.4832*X+11.04;Y=0.4621*X-0.3591)was determined using a simple linear regression modeling method.The percentages of green color positively correlated with plant height and above-ground biomass,and each model exhibited higher accuracy(R2≥0.8392,RMSE≤0.0158,NRMSE≤0.06%).Combining a high-definition digital camera with Canopeo enables the prediction of crop growth in the field.The simple linear regression modeling method and the most comprehensive model enable the rapid estimation of the cotton plant height and above-ground biomass.This method can also be used as a baseline to measure other important crop phenotypes.
基金Acknowledgements The authors would like to give their sincere thanks to the anonymous referees for their valuable suggestions and helpful comments, which help improve the presen- tation of the paper. This work was supported by the National Natural Science Foundation of China （Grant No. 61572283）.
文摘H-tensor is a new developed concept which plays an important role in tensor analysis and computing. In this paper, we explore the properties of H-tensors and establish some new criteria for strong H-tensors. In particular, based on the principal subtensor, we provide a new necessary and sufficient condition of strong H-tensors, and based on a type of generalized diagonal product dominance, we establish some new criteria for identifying strong H-tensors. The results obtained in this paper extend the corresponding conclusions for strong H-matrices and improve the existing results for strong H-tensors.
