Uniformseed distribution within the row is the prime objective of precision planters for better crop growth and yield.Inclined plate planters are generally used for sowing bold seeds likemaize,groundnut,chickpea,and t...Uniformseed distribution within the row is the prime objective of precision planters for better crop growth and yield.Inclined plate planters are generally used for sowing bold seeds likemaize,groundnut,chickpea,and their operating parameters like the forward speed of operation,the seedmetering plate inclination,and the seed level in the hopper affect the cell fill and subsequently the uniformseed distribution.Therefore,to achieve precise seed distribution,these parameters need to be optimized.In the present study,out of the different optimization techniques,a new intelligent optimization technique based on the integrated ANN-PSO approach has been used to achieve the set goal.A 3–5-1 artificial neural network(ANN)model was developed for predicting the cell fill of inclined plate seedmetering device,and the particle swarmoptimization(PSO)algorithmwas applied to obtain the optimum values of the operating parameters corresponding to 100%cell fill.The most appropriate optimal values of the forward speed of operation,the seed metering plate inclination,and the seed level in the hopper for achieving 100%cell fill were found to be 3 km/h,50-degree,and 75%of total height,respectively.The proposed integrated ANN-PSO approach was capable of predicting the optimal values of operating parameters with amaximumdeviation of 2%compared to the experimental results,thus confirmed the reliability of the proposed optimization technique.展开更多
The agrochemical applicationwith conventional sprayers results inwastage of applied chemicals,which not only increases the economic losses but also pollutes the environment.In order to overcome these drawbacks,an imag...The agrochemical applicationwith conventional sprayers results inwastage of applied chemicals,which not only increases the economic losses but also pollutes the environment.In order to overcome these drawbacks,an image processing based real-time variable-rate chemical spraying systemwas developed for the precise application of agrochemicals in diseased paddy crop based on crop disease severity information.The developed system comprised ofweb cameras for image acquisition,laptop for image processing,microcontroller for controlling the system functioning,and solenoid valve assisted spraying nozzles.The chromatic aberration(CA)based image segmentation method was used to detect the diseased region of paddy plants.The system further calculated the disease severity level of paddy plants,based onwhich the solenoid valves remained on for a specific timeduration so that the required amount of agrochemical could be sprayed on the diseased paddy plants.Field performance of developed sprayer prototype was evaluated in the variable-rate application(VRA)and constant-rate application(CRA)modes.The field testing results showed a minimum 33.88%reduction in applied chemical while operating in the VRA mode as compared with the CRA mode.Hence,the developed systemappears promising and could be used extensively to reduce the cost of pest management as well as to control environmental pollution due to such agrochemicals.展开更多
Artificial aeration system for aquaculture ponds becomes essential to meet the oxygen requirement posed by the aquatic species.The performance of an aerator is generally mea-sured in terms of standard aeration efficie...Artificial aeration system for aquaculture ponds becomes essential to meet the oxygen requirement posed by the aquatic species.The performance of an aerator is generally mea-sured in terms of standard aeration efficiency(SAE),which is significantly affected by the different geometric and dynamic parameters of the aerator.Therefore,to enhance the aer-ation performance of an aerator,these parameters need to be optimized.In the present study,a perforated pooled circular stepped cascade(PPCSC)aerator was developed,and the geometric and dynamic parameters of the developed aerator were optimized using the hybrid ANN-PSO technique for maximizing its aeration efficiency.The geometric parameters include consecutive step width ratio(W_(i-1)/W_(i))and the perforation diameter to the bottom-most radius ratio(d/R_(b)),whereas the dynamic parameter includes the water flow rate(Q).A 3–6-1 ANN model coupled with particle swarm optimization(PSO)approach was used to obtain the optimum values of geometric and dynamic parameters correspond-ing to the maximum SAE.The optimal values of the consecutive step width ratio(W_(i-1)/W_(i)),the perforation diameter to the bottom-most radius ratio(d/R_(b)),and the water flow rate(Q)for maximizing the SAE were found to be 1.15,0.0027 and 0.0167 m^(3)/s,respectively.The cross-validation results showed a deviation of 3.07%between the predicted and experimen-tal SAE values,thus confirming the adequacy of the proposed hybrid ANN-PSO technique.展开更多
In developing countries,the cotton harvesting operation is currently being performed manually.Due to the monotonous nature of this task and the involvement of a considerable amount of labor,this operation becomes very...In developing countries,the cotton harvesting operation is currently being performed manually.Due to the monotonous nature of this task and the involvement of a considerable amount of labor,this operation becomes very tedious and costly.The harvesting robots can be a good alternative for the selective picking of cotton bolls from the field.In this study,an attempt has been made to develop the image processing algorithms for in-field cotton boll detection in natural lighting conditions for the cotton harvesting robot.Four image processing algorithms namely color difference,band ratio,YCbCr method,and chromatic aberration were proposed for the real-time segmentation of cotton bolls under natural outdoor light conditions.The performance of developed image processing algorithms was evaluated and the experimental results revealed that the chromatic aberration method outperforms as compared to other developed algorithms.The chromatic aberration method showed the highest identification rate of 91.05%with false positive and false negative rates of 6.99%and 4.88%respectively,among all the proposed algorithms.The highest sensitivity and specificitywere found to be 81.31%and 97.53%,respectively,using the chromatic aberration method.Overall,the chromatic aberration approach demonstrated a very promising performance for in-field cotton bolls detection under natural lighting conditions which confirms its applicability for the robotic cotton harvesters.展开更多
文摘Uniformseed distribution within the row is the prime objective of precision planters for better crop growth and yield.Inclined plate planters are generally used for sowing bold seeds likemaize,groundnut,chickpea,and their operating parameters like the forward speed of operation,the seedmetering plate inclination,and the seed level in the hopper affect the cell fill and subsequently the uniformseed distribution.Therefore,to achieve precise seed distribution,these parameters need to be optimized.In the present study,out of the different optimization techniques,a new intelligent optimization technique based on the integrated ANN-PSO approach has been used to achieve the set goal.A 3–5-1 artificial neural network(ANN)model was developed for predicting the cell fill of inclined plate seedmetering device,and the particle swarmoptimization(PSO)algorithmwas applied to obtain the optimum values of the operating parameters corresponding to 100%cell fill.The most appropriate optimal values of the forward speed of operation,the seed metering plate inclination,and the seed level in the hopper for achieving 100%cell fill were found to be 3 km/h,50-degree,and 75%of total height,respectively.The proposed integrated ANN-PSO approach was capable of predicting the optimal values of operating parameters with amaximumdeviation of 2%compared to the experimental results,thus confirmed the reliability of the proposed optimization technique.
文摘The agrochemical applicationwith conventional sprayers results inwastage of applied chemicals,which not only increases the economic losses but also pollutes the environment.In order to overcome these drawbacks,an image processing based real-time variable-rate chemical spraying systemwas developed for the precise application of agrochemicals in diseased paddy crop based on crop disease severity information.The developed system comprised ofweb cameras for image acquisition,laptop for image processing,microcontroller for controlling the system functioning,and solenoid valve assisted spraying nozzles.The chromatic aberration(CA)based image segmentation method was used to detect the diseased region of paddy plants.The system further calculated the disease severity level of paddy plants,based onwhich the solenoid valves remained on for a specific timeduration so that the required amount of agrochemical could be sprayed on the diseased paddy plants.Field performance of developed sprayer prototype was evaluated in the variable-rate application(VRA)and constant-rate application(CRA)modes.The field testing results showed a minimum 33.88%reduction in applied chemical while operating in the VRA mode as compared with the CRA mode.Hence,the developed systemappears promising and could be used extensively to reduce the cost of pest management as well as to control environmental pollution due to such agrochemicals.
文摘Artificial aeration system for aquaculture ponds becomes essential to meet the oxygen requirement posed by the aquatic species.The performance of an aerator is generally mea-sured in terms of standard aeration efficiency(SAE),which is significantly affected by the different geometric and dynamic parameters of the aerator.Therefore,to enhance the aer-ation performance of an aerator,these parameters need to be optimized.In the present study,a perforated pooled circular stepped cascade(PPCSC)aerator was developed,and the geometric and dynamic parameters of the developed aerator were optimized using the hybrid ANN-PSO technique for maximizing its aeration efficiency.The geometric parameters include consecutive step width ratio(W_(i-1)/W_(i))and the perforation diameter to the bottom-most radius ratio(d/R_(b)),whereas the dynamic parameter includes the water flow rate(Q).A 3–6-1 ANN model coupled with particle swarm optimization(PSO)approach was used to obtain the optimum values of geometric and dynamic parameters correspond-ing to the maximum SAE.The optimal values of the consecutive step width ratio(W_(i-1)/W_(i)),the perforation diameter to the bottom-most radius ratio(d/R_(b)),and the water flow rate(Q)for maximizing the SAE were found to be 1.15,0.0027 and 0.0167 m^(3)/s,respectively.The cross-validation results showed a deviation of 3.07%between the predicted and experimen-tal SAE values,thus confirming the adequacy of the proposed hybrid ANN-PSO technique.
文摘In developing countries,the cotton harvesting operation is currently being performed manually.Due to the monotonous nature of this task and the involvement of a considerable amount of labor,this operation becomes very tedious and costly.The harvesting robots can be a good alternative for the selective picking of cotton bolls from the field.In this study,an attempt has been made to develop the image processing algorithms for in-field cotton boll detection in natural lighting conditions for the cotton harvesting robot.Four image processing algorithms namely color difference,band ratio,YCbCr method,and chromatic aberration were proposed for the real-time segmentation of cotton bolls under natural outdoor light conditions.The performance of developed image processing algorithms was evaluated and the experimental results revealed that the chromatic aberration method outperforms as compared to other developed algorithms.The chromatic aberration method showed the highest identification rate of 91.05%with false positive and false negative rates of 6.99%and 4.88%respectively,among all the proposed algorithms.The highest sensitivity and specificitywere found to be 81.31%and 97.53%,respectively,using the chromatic aberration method.Overall,the chromatic aberration approach demonstrated a very promising performance for in-field cotton bolls detection under natural lighting conditions which confirms its applicability for the robotic cotton harvesters.
