Accurate winter wheat identification and phenology extraction are essential for field management and agricultural policy making. Here, we present mechanisms of winter wheat discrimination and phenological detection in...Accurate winter wheat identification and phenology extraction are essential for field management and agricultural policy making. Here, we present mechanisms of winter wheat discrimination and phenological detection in the Yellow River Delta（YRD） region using moderate resolution imaging spectroradiometer（MODIS） time-series data. The normalized difference vegetation index（NDVI） was obtained by calculating the surface reflectance in red and infrared. We used the Savitzky-Golay filter to smooth time series NDVI curves. We adopted a two-step classification to identify winter wheat. The first step was designed to mask out non-vegetation classes, and the second step aimed to identify winter wheat from other vegetation based on its phenological features. We used the double Gaussian model and the maximum curvature method to extract phenology. Due to the characteristics of the time-series profiles for winter wheat, a double Gaussian function method was selected to fit the temporal profile. A maximum curvature method was performed to extract phenological phases. Phenological phases such as the green-up, heading and harvesting phases were detected when the NDVI curvature exhibited local maximum values. The extracted phenological dates then were validated with records of the ground observations. The spatial patterns of phenological phases were investigated. This study concluded that, for winter wheat, the accuracy of classification is 87.07%, and the accuracy of planting acreage is 90.09%. The phenological result was comparable to the ground observation at the municipal level. The average green-up date for the whole region occurred on March 5, the average heading date occurred on May 9, and the average harvesting date occurred on June 5. The spatial distribution of the phenology for winter wheat showed a significant gradual delay from the southwest to the northeast. This study demonstrates the effectiveness of our proposed method for winter wheat classification and phenology detection.展开更多
Analysis of genetic progress for lodging-related traits provides important information for further improvement of lodging resistance.Forty winter wheat cultivars widely grown in the Yellow-Huai River Valleys Winter Wh...Analysis of genetic progress for lodging-related traits provides important information for further improvement of lodging resistance.Forty winter wheat cultivars widely grown in the Yellow-Huai River Valleys Winter Wheat Zone(YHWZ)of China during the period of 1964–2015 were evaluated for several lodging-related traits in three cropping seasons.Plant height,height at center of gravity,length of the basal second internode,and lodging index decreased significantly in this period,and the average annual genetic gains for these traits were–0.50 cm or–0.62%,–0.27 cm or–0.60%,–0.06 cm or–0.63%,and–0.01 or–0.94%,respectively.Different from other traits,stem strength showed a significant increasing trend with the breeding period,and the annual genetic gains were 0.03 N or 0.05%.Correlation analysis showed that lodging index was positively correlated with plant height,height at center of gravity,and length of the basal second internode,but negatively correlated with stem strength.Meanwhile,significantly positive correlations were observed between plant height,height at center of gravity,and length of the basal first and second internodes.By comparison with the wild types,dwarfing genes had significant effects on all lodging-related traits studied except for length of the basal first internode and stem strength.Principle component analysis demonstrated that plant height and stem strength were the most important factors influencing lodging resistance.Clustering analysis based on the first two principle components further indicated the targets of wheat lodging-resistant breeding have changed from reducing plant height to strengthening stem strength over the breeding periods.This study indicates that the increase of stem strength is vital to improve lodging resistance in this region under the high-yielding condition when plant height is in an optimal range.展开更多
基金supported by the National Natural Science Foundation of China (41471335, 41271407)the National Remote Sensing Survey and Assessment of Eco-Environment Change between 2000 and 2010, China (STSN-1500)+2 种基金the National Key Technologies R&D Program of China during the 12th Five-Year Plan period (2013BAD05B03)the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA05050601)the International Science and Technology (S&T) Cooperation Program of China (2012DFG22050)
文摘Accurate winter wheat identification and phenology extraction are essential for field management and agricultural policy making. Here, we present mechanisms of winter wheat discrimination and phenological detection in the Yellow River Delta（YRD） region using moderate resolution imaging spectroradiometer（MODIS） time-series data. The normalized difference vegetation index（NDVI） was obtained by calculating the surface reflectance in red and infrared. We used the Savitzky-Golay filter to smooth time series NDVI curves. We adopted a two-step classification to identify winter wheat. The first step was designed to mask out non-vegetation classes, and the second step aimed to identify winter wheat from other vegetation based on its phenological features. We used the double Gaussian model and the maximum curvature method to extract phenology. Due to the characteristics of the time-series profiles for winter wheat, a double Gaussian function method was selected to fit the temporal profile. A maximum curvature method was performed to extract phenological phases. Phenological phases such as the green-up, heading and harvesting phases were detected when the NDVI curvature exhibited local maximum values. The extracted phenological dates then were validated with records of the ground observations. The spatial patterns of phenological phases were investigated. This study concluded that, for winter wheat, the accuracy of classification is 87.07%, and the accuracy of planting acreage is 90.09%. The phenological result was comparable to the ground observation at the municipal level. The average green-up date for the whole region occurred on March 5, the average heading date occurred on May 9, and the average harvesting date occurred on June 5. The spatial distribution of the phenology for winter wheat showed a significant gradual delay from the southwest to the northeast. This study demonstrates the effectiveness of our proposed method for winter wheat classification and phenology detection.
基金supported by the National Key Research and Development Program of China (2016YFD0101600 and 2016YFD0100102)the National Natural Science Foundation of China (31401468 and 31771881)the Innovation Team and the National Engineering Laboratory of Crop Molecular Breeding of Chinese Academy of Agricultural Sciences
文摘Analysis of genetic progress for lodging-related traits provides important information for further improvement of lodging resistance.Forty winter wheat cultivars widely grown in the Yellow-Huai River Valleys Winter Wheat Zone(YHWZ)of China during the period of 1964–2015 were evaluated for several lodging-related traits in three cropping seasons.Plant height,height at center of gravity,length of the basal second internode,and lodging index decreased significantly in this period,and the average annual genetic gains for these traits were–0.50 cm or–0.62%,–0.27 cm or–0.60%,–0.06 cm or–0.63%,and–0.01 or–0.94%,respectively.Different from other traits,stem strength showed a significant increasing trend with the breeding period,and the annual genetic gains were 0.03 N or 0.05%.Correlation analysis showed that lodging index was positively correlated with plant height,height at center of gravity,and length of the basal second internode,but negatively correlated with stem strength.Meanwhile,significantly positive correlations were observed between plant height,height at center of gravity,and length of the basal first and second internodes.By comparison with the wild types,dwarfing genes had significant effects on all lodging-related traits studied except for length of the basal first internode and stem strength.Principle component analysis demonstrated that plant height and stem strength were the most important factors influencing lodging resistance.Clustering analysis based on the first two principle components further indicated the targets of wheat lodging-resistant breeding have changed from reducing plant height to strengthening stem strength over the breeding periods.This study indicates that the increase of stem strength is vital to improve lodging resistance in this region under the high-yielding condition when plant height is in an optimal range.
