In order to study the correlation between the cracking of rice (Oryza sativa L.) kernels and the molecular structure of the amylopectin in them, we attempted optical sum frequency generation (SFG) spectroscopy in the ...In order to study the correlation between the cracking of rice (Oryza sativa L.) kernels and the molecular structure of the amylopectin in them, we attempted optical sum frequency generation (SFG) spectroscopy in the C-H stretching vibration region for normal and cracked japonica non-glutinous rice kernels. The samples were Koshihikari and Nipponbare. In Nipponbare, the width of the SFG spectrum peak at 2915 cm<sup>- 1</sup> of the cracked rice kernels was broader than that of the normal ones, while for Koshihikari there was no clear difference. The width of the 2915 cm<sup>- 1</sup> peak is suggested to originate from the variety of the higher-order structure of the saccharide chains in amylopectin. Although this is a tentative result, this method is shown to have a potential of serving for preventing the cracking of the rice kernels.展开更多
By comparative analysis on the meteorological conditions and occurrences of rice planthoppers in Guilin of Guangxi during recent 5 years,the temperature,precipitation,wind direction,wind velocity,humidity were chosen ...By comparative analysis on the meteorological conditions and occurrences of rice planthoppers in Guilin of Guangxi during recent 5 years,the temperature,precipitation,wind direction,wind velocity,humidity were chosen as the factors that affected the migration of rice planthopper in Guilin.Thinking of meteorological conditions and injurious number in early period,regression analysis method was used to establish the work system for grade forecast of meteorological conditions that affected the migration of rice planthopper.The forecast factors and targets were divided as 5 grades in the work system.Using one-week's weather forecast conclusion that local observatory had published,whether the meteorological conditions and injurious number were favorable or not was analyzed synthetically.The meteorological conditions grades that affected the migration of rice planthopper for each day in future 1-7 days were predicted.This is a practical forecast work system and the forecast accuracy for each day is larger than 70%.The work system has positive function in the manufacture practice.展开更多
Using the commercial seeds of two hybrid rice varieties including Lu- liangyou 996 and Liangyoupeijiu as the materials, four specific gravity-based seed grading treatments, Le., the specific gravity of 〈1.0 (T1), 1...Using the commercial seeds of two hybrid rice varieties including Lu- liangyou 996 and Liangyoupeijiu as the materials, four specific gravity-based seed grading treatments, Le., the specific gravity of 〈1.0 (T1), 1.0-1.09 (T2), 1.1-1.19(T3) and ≥1.2 (T4), by selection with different saline solutions, and the control without seed grading (CK) were designed to study the effects of seed grading on seed germination, seedling emergence, seedling quality and grain yield. The results showed that the treatments of T2, T3 and T4 had higher or significantly higher seed germination rate, germination index and vigor index, seedling emergence rate and adult seedling rate than the CK, while T1 had significantly lower values of these traits than the CK. Compared with the CK, the number of spikelets per pani- cle was found to be the main reason for the yield increase of these treatments with high seed viability.展开更多
Due to the inconsistency of rice variety,agricultural industry faces an important challenge of rice grading and classification by the traditional grading system.The existing grading system is manual,which introduces s...Due to the inconsistency of rice variety,agricultural industry faces an important challenge of rice grading and classification by the traditional grading system.The existing grading system is manual,which introduces stress and strain to humans due to visual inspection.Automated rice grading system development has been proposed as a promising research area in computer vision.In this study,an accurate deep learning-based non-contact and cost-effective rice grading system was developed by rice appearance and characteristics.The proposed system provided real-time processing by using a NI-myRIO with a high-resolution camera and user interface.We firstly trained the network by a rice public dataset to extract rice discriminative features.Secondly,by using transfer learning,the pre-trained network was used to locate the region by extracting a feature map.The proposed deep learning model was tested using two public standard datasets and a prototype real-time scanning system.Using AlexNet architecture,we obtained an average accuracy of 98.2%with 97.6%sensitivity and 96.4%specificity.To validate the real-time performance of proposed rice grading classification system,various performance indices were calculated and compared with the existing classifier.Both simulation and real-time experiment evaluations confirmed the robustness and reliability of the proposed rice grading system.展开更多
文摘In order to study the correlation between the cracking of rice (Oryza sativa L.) kernels and the molecular structure of the amylopectin in them, we attempted optical sum frequency generation (SFG) spectroscopy in the C-H stretching vibration region for normal and cracked japonica non-glutinous rice kernels. The samples were Koshihikari and Nipponbare. In Nipponbare, the width of the SFG spectrum peak at 2915 cm<sup>- 1</sup> of the cracked rice kernels was broader than that of the normal ones, while for Koshihikari there was no clear difference. The width of the 2915 cm<sup>- 1</sup> peak is suggested to originate from the variety of the higher-order structure of the saccharide chains in amylopectin. Although this is a tentative result, this method is shown to have a potential of serving for preventing the cracking of the rice kernels.
基金Supported by The Project of Guilin Science and Technology in Guangxi (2009011405)
文摘By comparative analysis on the meteorological conditions and occurrences of rice planthoppers in Guilin of Guangxi during recent 5 years,the temperature,precipitation,wind direction,wind velocity,humidity were chosen as the factors that affected the migration of rice planthopper in Guilin.Thinking of meteorological conditions and injurious number in early period,regression analysis method was used to establish the work system for grade forecast of meteorological conditions that affected the migration of rice planthopper.The forecast factors and targets were divided as 5 grades in the work system.Using one-week's weather forecast conclusion that local observatory had published,whether the meteorological conditions and injurious number were favorable or not was analyzed synthetically.The meteorological conditions grades that affected the migration of rice planthopper for each day in future 1-7 days were predicted.This is a practical forecast work system and the forecast accuracy for each day is larger than 70%.The work system has positive function in the manufacture practice.
基金Supported by Special Scientific Research Fund of Agricultural Public Welfare Profession of China(201303002,201203052)Key Project of Education Department of Hunan Province(14A073)~~
文摘Using the commercial seeds of two hybrid rice varieties including Lu- liangyou 996 and Liangyoupeijiu as the materials, four specific gravity-based seed grading treatments, Le., the specific gravity of 〈1.0 (T1), 1.0-1.09 (T2), 1.1-1.19(T3) and ≥1.2 (T4), by selection with different saline solutions, and the control without seed grading (CK) were designed to study the effects of seed grading on seed germination, seedling emergence, seedling quality and grain yield. The results showed that the treatments of T2, T3 and T4 had higher or significantly higher seed germination rate, germination index and vigor index, seedling emergence rate and adult seedling rate than the CK, while T1 had significantly lower values of these traits than the CK. Compared with the CK, the number of spikelets per pani- cle was found to be the main reason for the yield increase of these treatments with high seed viability.
基金the Indian National Academy of Science, New Delhi for providing research fellowship in the Department of Electrical Engineering, Indian Institute of Technology, New Delhi and Department of Electrical and Electronics Engineering, Mepco Schlenk Engineering College, Sivakasi, India for providing the necessary research facilities
文摘Due to the inconsistency of rice variety,agricultural industry faces an important challenge of rice grading and classification by the traditional grading system.The existing grading system is manual,which introduces stress and strain to humans due to visual inspection.Automated rice grading system development has been proposed as a promising research area in computer vision.In this study,an accurate deep learning-based non-contact and cost-effective rice grading system was developed by rice appearance and characteristics.The proposed system provided real-time processing by using a NI-myRIO with a high-resolution camera and user interface.We firstly trained the network by a rice public dataset to extract rice discriminative features.Secondly,by using transfer learning,the pre-trained network was used to locate the region by extracting a feature map.The proposed deep learning model was tested using two public standard datasets and a prototype real-time scanning system.Using AlexNet architecture,we obtained an average accuracy of 98.2%with 97.6%sensitivity and 96.4%specificity.To validate the real-time performance of proposed rice grading classification system,various performance indices were calculated and compared with the existing classifier.Both simulation and real-time experiment evaluations confirmed the robustness and reliability of the proposed rice grading system.