To study the effect of soil water and salt environment factors on the root growth of cotton under different moisture control,three different emergence water volumes(60,105,and 150 m^(3)/hm^(2)),two different frequenci...To study the effect of soil water and salt environment factors on the root growth of cotton under different moisture control,three different emergence water volumes(60,105,and 150 m^(3)/hm^(2)),two different frequencies(high frequency and low frequency)and one double film cover winter irrigation control treatment(CK:2250 m^(3)/hm^(2))were set up to analyze the spatial distribution patterns of soil water and salt environment and root density in dry sown and wet emerged cotton fields under diffe-rent moisture control conditions.The results show that the soil water content and water infiltration range gradually become larger with the increase of seedling water quantity,and the larger the seedling water quantity,the higher the soil water content.With the same seedling water quantity,the soil water content of the high-frequency(HF)treatment becomes obviously larger.The soil conductivity of each treatment tends to decrease gradually with the increase of seedling water and drip frequency,among which the distribution of soil conductivity of S6 treatment is closest to that of CK.With the increase in soil depth,the soil conductivity tends to increase first and then decrease.Compared with the low-frequency(LF)treatment,the high-frequency treatment shows a significantly deeper soil salt accumulation layer.The root length density(RLD)of cotton gradually increases with the amount of seedling water and the frequency of dripping.The soil layer of root distribution gradually deepens with the amount of seedling water in the vertical direction,and the RLD value in the horizontal direction is significantly greater in the mulched area than that in the bare area between films.This research can serve as a solid scientific foundation for the use of dry sowing and wet emergence techniques in cotton fields in southern Xinjiang.展开更多
To address the relationships between the amount of nitrogen fertilizer application and the yield of double cropping rice systems,we investigated the effects of a cultivation pattern of strong seedlings with increased ...To address the relationships between the amount of nitrogen fertilizer application and the yield of double cropping rice systems,we investigated the effects of a cultivation pattern of strong seedlings with increased planting density and reduced nitrogen application(SDN)on the morphological and physiological characteristics of double cropping rice.Our results indicated that the effects of SDN on the morphological characteristics of the single plant roots of double cropping rice were not significant,but the morphological characteristics of the population roots were largely different.Specifically,SDN significantly increased the morphological indexes of the root population such as root fresh weight,root volume,root number,root length and root dry weight.The effects of SDN on the total root absorption areas and root active absorption areas of the single plants were non-significant,but it dramatically enhanced the total root absorption areas and root active absorption areas of the plant population during the tillering,heading and mature stages.In addition,SDN significantly increased the root bleeding intensity and elevated the soluble sugar and free amino acid contents of root bleeding sap.Compared to the traditional cultivation pattern(CK),SDN significantly increased root bleeding intensity at the heading stage by 4.37 and 8.90% for early and late rice,respectively.Meanwhile,SDN profoundly enhanced the soluble sugar contents of root bleeding sap by 12.85 and 10.41% for early and late rice,respectively.In addition,SDN also significantly enhanced free amino acid content of root bleeding sap by 43.25% for early rice and by 37.50% for late rice systems compared to CK.Furthermore,SDN increased the actual yield of double cropping rice mainly due to the higher effective panicle number and the larger seedsetting rate.The actual yields of early rice under SDN were higher than CK by 9.37 and 5.98% in 2016 and 2017,and the actual yields of late rice under SDN were higher than CK by 0.20 and 1.41% in 2016 and 2017,respectively.C展开更多
Background： Biomass regression equations are claimed to yield the most accurate biomass estimates than biomass expansion factors （BEFs）. Yet, national and regional biomass estimates are generally calculated based o...Background： Biomass regression equations are claimed to yield the most accurate biomass estimates than biomass expansion factors （BEFs）. Yet, national and regional biomass estimates are generally calculated based on BEFs, especially when using national forest inventory data. Comparison of regression equations based and BEF-based biomass estimates are scarce. Thus, this study was intended to compare these two commonly used methods for estimating tree and forest biomass with regard to errors and biases. Methods： The data were collected in 2012 and 2014. In 2012, a two-phase sampling design was used to fit tree component biomass regression models and determine tree BEFs. In 2014, additional trees were felled outside sampling plots to estimate the biases associated with regression equation based and BEF-based biomass estimates; those estimates were then compared in terms of the following sources of error： plot selection and variability, biomass model, model parameter estimates, and residual variability around model prediction. Results： The regression equation based below-, aboveground and whole tree biomass stocks were, approximately, 7.7, 8.5 and 8.3 % larger than the BEF-based ones. For the whole tree biomass stock, the percentage of the total error attributed to first phase （random plot selection and variability） was 90 and 88 % for regression- and BEF-based estimates, respectively, being the remaining attributed to biomass models （regression and BEF models, respectively）. The percent bias of regression equation based and BEF-based biomass estimates for the whole tree biomass stock were -2.7 and 5.4 %, respectively. The errors due to model parameter estimates, those due to residual variability around model prediction, and the percentage of the total error attributed to biomass model were larger for BEF models （than for regression models）, except for stem and stem wood components. Conclusions＂ The regression equation based biomass stocks were found to be slightly larger, associated with re展开更多
前期研究工作提出了以预测均方根相对误差最小为回归目标的方法(Minimization of prediction relative error,MPRE),它能使得预测结果的均方根相对误差更小。偏最小二乘法(Partial least squares,PLS)是以预测均方根误差为回归目标,能...前期研究工作提出了以预测均方根相对误差最小为回归目标的方法(Minimization of prediction relative error,MPRE),它能使得预测结果的均方根相对误差更小。偏最小二乘法(Partial least squares,PLS)是以预测均方根误差为回归目标,能使得预测结果的均方根误差更小。基于多模型结合的思想,提出将MPRE与PLS相结合的双模型结合多元校正方法。本方法步骤为:(1)分别采用MPRE与PLS法对校正集建模;(2)计算阈值;(3)分别采用已建立好的MPRE与PLS模型进行预测;(4)将预测结果与阈值进行比较,得到预测结果。通过对酒精的近红外光谱与汽油紫外光谱进行定量分析结果表明,本方法可进一步减小预测均方根误差与相对误差。展开更多
基金National Key Research and Development Plan(2021YFD1900805)Funded Project of Basic Scientific Research Business of Public Welfare Research Institutes in Autonomous Region(KY2022127)。
文摘To study the effect of soil water and salt environment factors on the root growth of cotton under different moisture control,three different emergence water volumes(60,105,and 150 m^(3)/hm^(2)),two different frequencies(high frequency and low frequency)and one double film cover winter irrigation control treatment(CK:2250 m^(3)/hm^(2))were set up to analyze the spatial distribution patterns of soil water and salt environment and root density in dry sown and wet emerged cotton fields under diffe-rent moisture control conditions.The results show that the soil water content and water infiltration range gradually become larger with the increase of seedling water quantity,and the larger the seedling water quantity,the higher the soil water content.With the same seedling water quantity,the soil water content of the high-frequency(HF)treatment becomes obviously larger.The soil conductivity of each treatment tends to decrease gradually with the increase of seedling water and drip frequency,among which the distribution of soil conductivity of S6 treatment is closest to that of CK.With the increase in soil depth,the soil conductivity tends to increase first and then decrease.Compared with the low-frequency(LF)treatment,the high-frequency treatment shows a significantly deeper soil salt accumulation layer.The root length density(RLD)of cotton gradually increases with the amount of seedling water and the frequency of dripping.The soil layer of root distribution gradually deepens with the amount of seedling water in the vertical direction,and the RLD value in the horizontal direction is significantly greater in the mulched area than that in the bare area between films.This research can serve as a solid scientific foundation for the use of dry sowing and wet emergence techniques in cotton fields in southern Xinjiang.
基金financially supported by the National Key Research and Development Program of China(2017YFD0300106,2018YFD0301103,and 2016YFD0300108)the National Key Technologies R&D Program of China during the 12th Five-Year Plan period(2013BAD07B12)the National Natural Science Foundation of China(31601263)。
文摘To address the relationships between the amount of nitrogen fertilizer application and the yield of double cropping rice systems,we investigated the effects of a cultivation pattern of strong seedlings with increased planting density and reduced nitrogen application(SDN)on the morphological and physiological characteristics of double cropping rice.Our results indicated that the effects of SDN on the morphological characteristics of the single plant roots of double cropping rice were not significant,but the morphological characteristics of the population roots were largely different.Specifically,SDN significantly increased the morphological indexes of the root population such as root fresh weight,root volume,root number,root length and root dry weight.The effects of SDN on the total root absorption areas and root active absorption areas of the single plants were non-significant,but it dramatically enhanced the total root absorption areas and root active absorption areas of the plant population during the tillering,heading and mature stages.In addition,SDN significantly increased the root bleeding intensity and elevated the soluble sugar and free amino acid contents of root bleeding sap.Compared to the traditional cultivation pattern(CK),SDN significantly increased root bleeding intensity at the heading stage by 4.37 and 8.90% for early and late rice,respectively.Meanwhile,SDN profoundly enhanced the soluble sugar contents of root bleeding sap by 12.85 and 10.41% for early and late rice,respectively.In addition,SDN also significantly enhanced free amino acid content of root bleeding sap by 43.25% for early rice and by 37.50% for late rice systems compared to CK.Furthermore,SDN increased the actual yield of double cropping rice mainly due to the higher effective panicle number and the larger seedsetting rate.The actual yields of early rice under SDN were higher than CK by 9.37 and 5.98% in 2016 and 2017,and the actual yields of late rice under SDN were higher than CK by 0.20 and 1.41% in 2016 and 2017,respectively.C
基金funded by the Swedish International Development Cooperation Agency(SIDA)Professor Agnelo Fernandes and Madeirarte Lda for financial and logistical support
文摘Background： Biomass regression equations are claimed to yield the most accurate biomass estimates than biomass expansion factors （BEFs）. Yet, national and regional biomass estimates are generally calculated based on BEFs, especially when using national forest inventory data. Comparison of regression equations based and BEF-based biomass estimates are scarce. Thus, this study was intended to compare these two commonly used methods for estimating tree and forest biomass with regard to errors and biases. Methods： The data were collected in 2012 and 2014. In 2012, a two-phase sampling design was used to fit tree component biomass regression models and determine tree BEFs. In 2014, additional trees were felled outside sampling plots to estimate the biases associated with regression equation based and BEF-based biomass estimates; those estimates were then compared in terms of the following sources of error： plot selection and variability, biomass model, model parameter estimates, and residual variability around model prediction. Results： The regression equation based below-, aboveground and whole tree biomass stocks were, approximately, 7.7, 8.5 and 8.3 % larger than the BEF-based ones. For the whole tree biomass stock, the percentage of the total error attributed to first phase （random plot selection and variability） was 90 and 88 % for regression- and BEF-based estimates, respectively, being the remaining attributed to biomass models （regression and BEF models, respectively）. The percent bias of regression equation based and BEF-based biomass estimates for the whole tree biomass stock were -2.7 and 5.4 %, respectively. The errors due to model parameter estimates, those due to residual variability around model prediction, and the percentage of the total error attributed to biomass model were larger for BEF models （than for regression models）, except for stem and stem wood components. Conclusions＂ The regression equation based biomass stocks were found to be slightly larger, associated with re
文摘前期研究工作提出了以预测均方根相对误差最小为回归目标的方法(Minimization of prediction relative error,MPRE),它能使得预测结果的均方根相对误差更小。偏最小二乘法(Partial least squares,PLS)是以预测均方根误差为回归目标,能使得预测结果的均方根误差更小。基于多模型结合的思想,提出将MPRE与PLS相结合的双模型结合多元校正方法。本方法步骤为:(1)分别采用MPRE与PLS法对校正集建模;(2)计算阈值;(3)分别采用已建立好的MPRE与PLS模型进行预测;(4)将预测结果与阈值进行比较,得到预测结果。通过对酒精的近红外光谱与汽油紫外光谱进行定量分析结果表明,本方法可进一步减小预测均方根误差与相对误差。
