Nitrogen(N)and potassium(K)are two key mineral nutrient elements involved in rice growth.Accurate diagnosis of N and K status is very important for the rational application of fertilizers at a specific rice growth sta...Nitrogen(N)and potassium(K)are two key mineral nutrient elements involved in rice growth.Accurate diagnosis of N and K status is very important for the rational application of fertilizers at a specific rice growth stage.Therefore,we propose a hybrid model for diagnosing rice nutrient levels at the early panicle initiation stage(EPIS),which combines a convolutional neural network(CNN)with an attention mechanism and a long short-term memory network(LSTM).The model was validated on a large set of sequential images collected by an unmanned aerial vehicle(UAV)from rice canopies at different growth stages during a two-year experiment.Compared with VGG16,AlexNet,GoogleNet,DenseNet,and inceptionV3,ResNet101 combined with LSTM obtained the highest average accuracy of 83.81%on the dataset of Huanghuazhan(HHZ,an indica cultivar).When tested on the datasets of HHZ and Xiushui 134(XS134,a japonica rice variety)in 2021,the ResNet101-LSTM model enhanced with the squeeze-and-excitation(SE)block achieved the highest accuracies of 85.38 and 88.38%,respectively.Through the cross-dataset method,the average accuracies on the HHZ and XS134 datasets tested in 2022 were 81.25 and 82.50%,respectively,showing a good generalization.Our proposed model works with the dynamic information of different rice growth stages and can efficiently diagnose different rice nutrient status levels at EPIS,which are helpful for making practical decisions regarding rational fertilization treatments at the panicle initiation stage.展开更多
Pyrus pashia Buch-Ham, a wild specie was used to investigate the physiological effects of iron deficiency in culture solution. The result showed that Chla, Chlb, total chlorophyll content and photosynthesis rate(Pn) d...Pyrus pashia Buch-Ham, a wild specie was used to investigate the physiological effects of iron deficiency in culture solution. The result showed that Chla, Chlb, total chlorophyll content and photosynthesis rate(Pn) decreased sharply, and the decrease of Pn was prior to that of Chl content under the iron deficiency. The iron deficiency symptoms were visible when the iron concentration in culture medium was less than 25 μmol L-1. Peroxidase(POD) and catalase(CAT) activity in iron-deficient leaves declined significantly, and POD was more sensitive than CAT to Fe deficiency. However, the positive correlation between CAT activity and Chl content was more significant than that between POD activity and Chl content. The content of nutrient elements in Fe-deficient leaves, which changed irregularly, were higher than that in normal leaves. There were a most significant positive correlation between active Fe and Chl content, and between active Fe and Pn respectively. Therefore, active Fe could be useful physiological predicting index for diagnosis.展开更多
A series ofresearches on the nutrition problems in the cultivation of Chinese fir seedlings and plantations, which are mainly focus on the problems of serious land degradation in Chinese fir plantations in contradicti...A series ofresearches on the nutrition problems in the cultivation of Chinese fir seedlings and plantations, which are mainly focus on the problems of serious land degradation in Chinese fir plantations in contradiction with the rapid development of the plantations in China, were summarized. Twelve years was taken and more than 30 pieces of research papers were published for the researches, which refers to the problems of growth effect, physiological effect, vegetation variation, biomass accumulation, n...展开更多
基金supported by the National Key Research and Development Program of China(2022YFD2300700)the Open Project Program of State Key Laboratory of Rice Biology,China National Rice Research Institute(20210403)the Zhejiang“Ten Thousand Talents”Plan Science and Technology Innovation Leading Talent Project,China(2020R52035)。
文摘Nitrogen(N)and potassium(K)are two key mineral nutrient elements involved in rice growth.Accurate diagnosis of N and K status is very important for the rational application of fertilizers at a specific rice growth stage.Therefore,we propose a hybrid model for diagnosing rice nutrient levels at the early panicle initiation stage(EPIS),which combines a convolutional neural network(CNN)with an attention mechanism and a long short-term memory network(LSTM).The model was validated on a large set of sequential images collected by an unmanned aerial vehicle(UAV)from rice canopies at different growth stages during a two-year experiment.Compared with VGG16,AlexNet,GoogleNet,DenseNet,and inceptionV3,ResNet101 combined with LSTM obtained the highest average accuracy of 83.81%on the dataset of Huanghuazhan(HHZ,an indica cultivar).When tested on the datasets of HHZ and Xiushui 134(XS134,a japonica rice variety)in 2021,the ResNet101-LSTM model enhanced with the squeeze-and-excitation(SE)block achieved the highest accuracies of 85.38 and 88.38%,respectively.Through the cross-dataset method,the average accuracies on the HHZ and XS134 datasets tested in 2022 were 81.25 and 82.50%,respectively,showing a good generalization.Our proposed model works with the dynamic information of different rice growth stages and can efficiently diagnose different rice nutrient status levels at EPIS,which are helpful for making practical decisions regarding rational fertilization treatments at the panicle initiation stage.
文摘Pyrus pashia Buch-Ham, a wild specie was used to investigate the physiological effects of iron deficiency in culture solution. The result showed that Chla, Chlb, total chlorophyll content and photosynthesis rate(Pn) decreased sharply, and the decrease of Pn was prior to that of Chl content under the iron deficiency. The iron deficiency symptoms were visible when the iron concentration in culture medium was less than 25 μmol L-1. Peroxidase(POD) and catalase(CAT) activity in iron-deficient leaves declined significantly, and POD was more sensitive than CAT to Fe deficiency. However, the positive correlation between CAT activity and Chl content was more significant than that between POD activity and Chl content. The content of nutrient elements in Fe-deficient leaves, which changed irregularly, were higher than that in normal leaves. There were a most significant positive correlation between active Fe and Chl content, and between active Fe and Pn respectively. Therefore, active Fe could be useful physiological predicting index for diagnosis.
文摘A series ofresearches on the nutrition problems in the cultivation of Chinese fir seedlings and plantations, which are mainly focus on the problems of serious land degradation in Chinese fir plantations in contradiction with the rapid development of the plantations in China, were summarized. Twelve years was taken and more than 30 pieces of research papers were published for the researches, which refers to the problems of growth effect, physiological effect, vegetation variation, biomass accumulation, n...