Edible mushrooms are rich in nutrients;however,harvesting mainly relies on manual labor.Coarse localization of each mushroom is necessary to enable a robotic arm to accurately pick edible mushrooms.Previous studies us...Edible mushrooms are rich in nutrients;however,harvesting mainly relies on manual labor.Coarse localization of each mushroom is necessary to enable a robotic arm to accurately pick edible mushrooms.Previous studies used detection algorithms that did not consider mushroom pixel-level information.When these algorithms are combined with a depth map,the information is lost.Moreover,in instance segmentation algorithms,convolutional neural network(CNN)-based methods are lightweight,and the extracted features are not correlated.To guarantee real-time location detection and improve the accuracy of mushroom segmentation,this study proposed a new spatial-channel transformer network model based on Mask-CNN(SCT-Mask-RCNN).The fusion of Mask-RCNN with the self-attention mechanism extracts the global correlation outcomes of image features from the channel and spatial dimensions.Subsequently,Mask-RCNN was used to maintain a lightweight structure and extract local features using a spatial pooling pyramidal structure to achieve multiscale local feature fusion and improve detection accuracy.The results showed that the SCT-Mask-RCNN method achieved a segmentation accuracy of 0.750 on segm_Precision_mAP and detection accuracy of 0.638 on Bbox_Precision_mAP.Compared to existing methods,the proposed method improved the accuracy of the evaluation metrics Bbox_Precision_mAP and segm_Precision_mAP by over 2%and 5%,respectively.展开更多
Cutting mechanisms in existing grafting machines are unable to completely cut through the rootstock growth point and can easily damage seedlings.During the mechanical operation of splice grafting,the cutting angle of ...Cutting mechanisms in existing grafting machines are unable to completely cut through the rootstock growth point and can easily damage seedlings.During the mechanical operation of splice grafting,the cutting angle of the rootstock is an essential factor for ensuring the quality and survival rate of grafting seedlings and a stable process for grafting robots.Therefore,in this study,commonly used grafting rootstocks,e.g.,cucurbita moschata,and calabash gourd were used as research objects for studying and analyzing the cutting angle of a splice grafting method.The morphological and structural parameters of the rootstock and scion were measured,and a structural model of the internal cavity of the rootstock was constructed using an image analysis method.The critical cutting angles for the cucurbita moschata and calabash gourd seedlings were obtained.According to the analysis,the grafting cutting angles for cucumber seedlings matching with cucurbita moschata seedlings were 20°and 25°,respectively,and the fitting rate of the cutting surface of the rootstock and scion was 99.04%.A cutting mechanism for the rootstock growth point and geometric model of the cutting operation were established,and the structural parameters of the mechanism and cutting angle adjustment were optimized.A cutting performance test showed that the success rate of the pressing the cotyledons of cucurbita moschata seedlings was 96.67%,and the success rate of cutting was 98%.The cutting accuracy was 96.8%,and the cutting surface fitting rate of the rootstock and scion was 98.61%.The latter differed by 0.43%from the theoretical rate but met the requirements for the splice grafting method.Thus,this study can provide a reference for the design of a cutting mechanism for a grafting robot.展开更多
The side-curtain is popular in cattle buildings to regulate indoor climates and ventilation rates by adjusting the opening ratio.It normally had three different adjusting strategies relate to the position of rollers,i...The side-curtain is popular in cattle buildings to regulate indoor climates and ventilation rates by adjusting the opening ratio.It normally had three different adjusting strategies relate to the position of rollers,i.e.central roller(S1),top roller(S2)and bottom roller(S3),which result in different opening behaviors to generate the same opening ratio but different opening positions in the side wall for a full-curtain house.Numerical simulations were conducted using computational fluid dynamics(CFD)to investigate the effects of the eight potential opening behaviors of side curtains on the indoor climates and airflow rates in winter for a typical naturally ventilated dairy house in China when the opening ratio were 8.5%and 17%.Airflow patterns,wind chilled temperature(WCT)and age of air were analyzed in the animal occupied zone(AOZ)by taking reference planes.Openings at the very bottom of side walls had more efficient ventilation due to the younger air age,more effective air disturbing,more uniformly distributed indicators in AOZ.However,it will result in a lower WCT in AOZ although a lower ventilation rate was observed in this case.Openings on the very top of side wall would generate a better thermal comfort in AOZ but with very poor air quality and nonuniformly distributed airflows in the dairy house.S1 was not recommended to the practical application due to the poor indoor climate and the higher cost of the mechanical structure.Based on the comprehensive evaluations of the analytic hierarchy process,the most satisfaction opening positions were at the bottom of the side curtains and the optimized adjusting strategy is S2.展开更多
Water stress status of plants is very important for irrigation scheduling.However,plant water stress status monitoring has become the bottleneck of irrigation scheduling.In this study,an automatic water stress status ...Water stress status of plants is very important for irrigation scheduling.However,plant water stress status monitoring has become the bottleneck of irrigation scheduling.In this study,an automatic water stress status monitoring method for strawberry plant was proposed and realized using combined RGB and infrared image information.RGB image and infrared images were obtained using RGB digital camera and infrared thermal camera,which were placed in a fixed shell in parallel.In the first experimental stage,three kinds of water stress treatments were carried out on three groups of strawberry plants,and each group includes three repetitions.Single point plant temperature,dry surface temperature,wet surface temperature were measured.In the second experimental stage,the infrared and visible light images of the canopy leaves were obtained.Meanwhile,plant temperature,dry surface temperature,wet surface temperature,and stomatal conductance were measured not only for single point but also for plant area temperature measurement.Fusion information of infrared image and visible light image was analyzed using image processing technology,to calculate the average temperature of plant areas.Based on single point temperature,area temperature,dry surface temperature and wet surface temperature of the plant,single point crop water stress index(CWSI)and area CWSI were calculated.Through analysis of variance(ANOVA),the experimental results showed that CWSI measured for plants under different treatments,were significantly different.Through correlation analysis,the experimental results showed that,determination coefficient between area CWSI and the corresponding stomatal conductance of three strawberry groups were 0.8834,0.8730 and 0.8851,respectively,which were larger than that of single-point CWSI and stomatal conductance.The results showed that area CWSI is more suitable to be used as the criteria for automatic diagnosis of plants.展开更多
Owing to the requirements of a high yield and high-quality tomatoes, tomato grading is important-particularly for fruit morphology, and accuracy has become the focus of attention. Machine vision provides a fast and no...Owing to the requirements of a high yield and high-quality tomatoes, tomato grading is important-particularly for fruit morphology, and accuracy has become the focus of attention. Machine vision provides a fast and nondestructive manner to address this demand. In this study, the gamma correction method was used for preprocessing to enhance the edge information of tomatoes, and Otsu’s method was used to eliminate the tomato-image background in the A-component image under the LAB color model. On this basis, two levels of exploration were conducted. First, new evaluation indices were proposed for tomato shapes from different views. For the top view, two shape-evaluation indices were established: the area ratio of the maximum inscribed circle to the maximum circumscribed circle and the dispersion of the contour centroid distance (range and coefficient of variation), the highest accuracy was 94%. For the side view, the difference between the maximum and minimum centroid distances in the contour was established as a shape index, the highest accuracy was 91.91%. Second, an evaluation method based on multi-view fusion was developed by combining the advantage indices for different views. The classification accuracy reached 96%, with the highest identification accuracy of unqualified tomatoes. The results show that the proposed evaluation method combining top views (dispersion of centroid distance) with side views (difference between maximum and minimum centroid distances) is effective for classifying tomatoes.展开更多
基金supported by China Agriculture Research System of MOF and MARA(CARS-20)Zhejiang Provincial Key Laboratory of Agricultural Intelligent Equipment and Robotics Open Fund(2023ZJZD2301)+1 种基金Chinese Academy of Agricultural Science and Technology Innovation Project“Fruit And Vegetable Production And Processing Technical Equipment Team”(2024)Beijing Nova Program(20220484023).
文摘Edible mushrooms are rich in nutrients;however,harvesting mainly relies on manual labor.Coarse localization of each mushroom is necessary to enable a robotic arm to accurately pick edible mushrooms.Previous studies used detection algorithms that did not consider mushroom pixel-level information.When these algorithms are combined with a depth map,the information is lost.Moreover,in instance segmentation algorithms,convolutional neural network(CNN)-based methods are lightweight,and the extracted features are not correlated.To guarantee real-time location detection and improve the accuracy of mushroom segmentation,this study proposed a new spatial-channel transformer network model based on Mask-CNN(SCT-Mask-RCNN).The fusion of Mask-RCNN with the self-attention mechanism extracts the global correlation outcomes of image features from the channel and spatial dimensions.Subsequently,Mask-RCNN was used to maintain a lightweight structure and extract local features using a spatial pooling pyramidal structure to achieve multiscale local feature fusion and improve detection accuracy.The results showed that the SCT-Mask-RCNN method achieved a segmentation accuracy of 0.750 on segm_Precision_mAP and detection accuracy of 0.638 on Bbox_Precision_mAP.Compared to existing methods,the proposed method improved the accuracy of the evaluation metrics Bbox_Precision_mAP and segm_Precision_mAP by over 2%and 5%,respectively.
基金This work was funded by theBeijingAcademyofAgriculture and Forestry SciencesInnovation Ability Project(Grant No.KJCX20180422)the Key Research and Development projects in Ningxia Hui Autonomous Region(Grant No.2018BBF02024)the National Key Technology Research and Development Program of China(Grant,No.2013AA102406).
文摘Cutting mechanisms in existing grafting machines are unable to completely cut through the rootstock growth point and can easily damage seedlings.During the mechanical operation of splice grafting,the cutting angle of the rootstock is an essential factor for ensuring the quality and survival rate of grafting seedlings and a stable process for grafting robots.Therefore,in this study,commonly used grafting rootstocks,e.g.,cucurbita moschata,and calabash gourd were used as research objects for studying and analyzing the cutting angle of a splice grafting method.The morphological and structural parameters of the rootstock and scion were measured,and a structural model of the internal cavity of the rootstock was constructed using an image analysis method.The critical cutting angles for the cucurbita moschata and calabash gourd seedlings were obtained.According to the analysis,the grafting cutting angles for cucumber seedlings matching with cucurbita moschata seedlings were 20°and 25°,respectively,and the fitting rate of the cutting surface of the rootstock and scion was 99.04%.A cutting mechanism for the rootstock growth point and geometric model of the cutting operation were established,and the structural parameters of the mechanism and cutting angle adjustment were optimized.A cutting performance test showed that the success rate of the pressing the cotyledons of cucurbita moschata seedlings was 96.67%,and the success rate of cutting was 98%.The cutting accuracy was 96.8%,and the cutting surface fitting rate of the rootstock and scion was 98.61%.The latter differed by 0.43%from the theoretical rate but met the requirements for the splice grafting method.Thus,this study can provide a reference for the design of a cutting mechanism for a grafting robot.
基金This study was financially supported by the National Key Research and Development Program of China(2018YFD0500702-02,2018YFE0108500)the Beijing Natural Science Foundation(6194037)the Youth Personnel Project of Beijing Outstanding Talents in 2018.
文摘The side-curtain is popular in cattle buildings to regulate indoor climates and ventilation rates by adjusting the opening ratio.It normally had three different adjusting strategies relate to the position of rollers,i.e.central roller(S1),top roller(S2)and bottom roller(S3),which result in different opening behaviors to generate the same opening ratio but different opening positions in the side wall for a full-curtain house.Numerical simulations were conducted using computational fluid dynamics(CFD)to investigate the effects of the eight potential opening behaviors of side curtains on the indoor climates and airflow rates in winter for a typical naturally ventilated dairy house in China when the opening ratio were 8.5%and 17%.Airflow patterns,wind chilled temperature(WCT)and age of air were analyzed in the animal occupied zone(AOZ)by taking reference planes.Openings at the very bottom of side walls had more efficient ventilation due to the younger air age,more effective air disturbing,more uniformly distributed indicators in AOZ.However,it will result in a lower WCT in AOZ although a lower ventilation rate was observed in this case.Openings on the very top of side wall would generate a better thermal comfort in AOZ but with very poor air quality and nonuniformly distributed airflows in the dairy house.S1 was not recommended to the practical application due to the poor indoor climate and the higher cost of the mechanical structure.Based on the comprehensive evaluations of the analytic hierarchy process,the most satisfaction opening positions were at the bottom of the side curtains and the optimized adjusting strategy is S2.
基金The project was supported by the National Natural Science Fund(Grant No.31701319)National Key Research and Development Program(Grant No.2016YFD0200602)+1 种基金Marie Curie project entitled“A Traceability and Early warning system for supply chain of Agricultural Product:complementarities between EU and China”(TEAP,EU-CHINA project PIRSES-GA-2013-612659)CAU Special funds for basic research and business expenses(2017QC020).
文摘Water stress status of plants is very important for irrigation scheduling.However,plant water stress status monitoring has become the bottleneck of irrigation scheduling.In this study,an automatic water stress status monitoring method for strawberry plant was proposed and realized using combined RGB and infrared image information.RGB image and infrared images were obtained using RGB digital camera and infrared thermal camera,which were placed in a fixed shell in parallel.In the first experimental stage,three kinds of water stress treatments were carried out on three groups of strawberry plants,and each group includes three repetitions.Single point plant temperature,dry surface temperature,wet surface temperature were measured.In the second experimental stage,the infrared and visible light images of the canopy leaves were obtained.Meanwhile,plant temperature,dry surface temperature,wet surface temperature,and stomatal conductance were measured not only for single point but also for plant area temperature measurement.Fusion information of infrared image and visible light image was analyzed using image processing technology,to calculate the average temperature of plant areas.Based on single point temperature,area temperature,dry surface temperature and wet surface temperature of the plant,single point crop water stress index(CWSI)and area CWSI were calculated.Through analysis of variance(ANOVA),the experimental results showed that CWSI measured for plants under different treatments,were significantly different.Through correlation analysis,the experimental results showed that,determination coefficient between area CWSI and the corresponding stomatal conductance of three strawberry groups were 0.8834,0.8730 and 0.8851,respectively,which were larger than that of single-point CWSI and stomatal conductance.The results showed that area CWSI is more suitable to be used as the criteria for automatic diagnosis of plants.
基金supported by the Beijing Nova Program (Grant No.2023141)Yunnan Key Research and Development Program (Grant No.202202AE090066)the Project of Beijing Academy of Agricultural Sciences (Grant No.YXQN202304)。
文摘Owing to the requirements of a high yield and high-quality tomatoes, tomato grading is important-particularly for fruit morphology, and accuracy has become the focus of attention. Machine vision provides a fast and nondestructive manner to address this demand. In this study, the gamma correction method was used for preprocessing to enhance the edge information of tomatoes, and Otsu’s method was used to eliminate the tomato-image background in the A-component image under the LAB color model. On this basis, two levels of exploration were conducted. First, new evaluation indices were proposed for tomato shapes from different views. For the top view, two shape-evaluation indices were established: the area ratio of the maximum inscribed circle to the maximum circumscribed circle and the dispersion of the contour centroid distance (range and coefficient of variation), the highest accuracy was 94%. For the side view, the difference between the maximum and minimum centroid distances in the contour was established as a shape index, the highest accuracy was 91.91%. Second, an evaluation method based on multi-view fusion was developed by combining the advantage indices for different views. The classification accuracy reached 96%, with the highest identification accuracy of unqualified tomatoes. The results show that the proposed evaluation method combining top views (dispersion of centroid distance) with side views (difference between maximum and minimum centroid distances) is effective for classifying tomatoes.
