The increasing demand of water in the country highlights the need to introduce low-input and water saving technologies for agricultural sustainability and crop production,mainly in semi-arid region.A study was conduct...The increasing demand of water in the country highlights the need to introduce low-input and water saving technologies for agricultural sustainability and crop production,mainly in semi-arid region.A study was conducted to minimize deep percolation losses from the furrow bottom under two different irrigation treatments viz.(1)furrow bottom with plastic sheet(T1)and(2)furrow bottom without plastic Sheet(T0).The physical and chemical analyses of soil profile were taken at a depth of 0-80 cm before and after crop harvesting.The dry density of soil slightly increased(0.01 g/cm^(3))under both treatments,while soil pH decreased under T1.The average yield was 8332 kg/hm^(2) and 7575 kg/hm^(2),with 21.56 m^(3) and 31.09 m^(3) total volume of irrigation water applied under T1and T0,respectively.The saving percentages of water under treatments were 52.22% and 31.00% under T1 and T0 respectively as compared to the saving of water under traditional irrigation practice.Overall,better performance,in terms of crop production and water saving,was obtained with use of plastic sheet integrated with bottom of furrows.Hence,it is suggested that the furrow irrigation method with plastic sheet may be used to preventing moisture and minimize deep percolation losses from furrow bottom.展开更多
With large-scale production and the need for high-quality tomatoes to meet consumer and market standards criteria,have led to the need for an inline,accurate,reliable grading system during the post-harvest process.Thi...With large-scale production and the need for high-quality tomatoes to meet consumer and market standards criteria,have led to the need for an inline,accurate,reliable grading system during the post-harvest process.This study introduced a tomato grading machine vision system based on RGB images.The proposed system performed calyx and stalk scar detection at an average accuracy of 0.9515 for both defected and healthy tomatoes by histogramthresholding based on themean g-r value of these regions of interest.Defected regionswere detected by an RBF-SVMclassifier using the LAB color-space pixel values.Themodel achieved an overall accuracy of 0.989 upon validation.Four grading categories recognitionmodelswere developed based on color and texture features.The RBF-SVMoutperformed all the explored modelswith the highest accuracy of 0.9709 for healthy and defected category.However,the grading accuracy decreased as the number of grading categories increased.A combination of color and texture features achieved the highest accuracy in all the grading categories in image features evaluation.This proposed system can be used as an inline tomato sorting tool to ensure that quality standards are adhered to and maintained.展开更多
基金Authors wish to thank the National Natural Science Foundation of China(Grant No.51275250)for supporting.
文摘The increasing demand of water in the country highlights the need to introduce low-input and water saving technologies for agricultural sustainability and crop production,mainly in semi-arid region.A study was conducted to minimize deep percolation losses from the furrow bottom under two different irrigation treatments viz.(1)furrow bottom with plastic sheet(T1)and(2)furrow bottom without plastic Sheet(T0).The physical and chemical analyses of soil profile were taken at a depth of 0-80 cm before and after crop harvesting.The dry density of soil slightly increased(0.01 g/cm^(3))under both treatments,while soil pH decreased under T1.The average yield was 8332 kg/hm^(2) and 7575 kg/hm^(2),with 21.56 m^(3) and 31.09 m^(3) total volume of irrigation water applied under T1and T0,respectively.The saving percentages of water under treatments were 52.22% and 31.00% under T1 and T0 respectively as compared to the saving of water under traditional irrigation practice.Overall,better performance,in terms of crop production and water saving,was obtained with use of plastic sheet integrated with bottom of furrows.Hence,it is suggested that the furrow irrigation method with plastic sheet may be used to preventing moisture and minimize deep percolation losses from furrow bottom.
基金We thank the editor and the reviewers for assisting in improving the manuscript and acknowledge Fundamental Research Funds for the Central Universities,China(KYGX201701)for funding the research.
文摘With large-scale production and the need for high-quality tomatoes to meet consumer and market standards criteria,have led to the need for an inline,accurate,reliable grading system during the post-harvest process.This study introduced a tomato grading machine vision system based on RGB images.The proposed system performed calyx and stalk scar detection at an average accuracy of 0.9515 for both defected and healthy tomatoes by histogramthresholding based on themean g-r value of these regions of interest.Defected regionswere detected by an RBF-SVMclassifier using the LAB color-space pixel values.Themodel achieved an overall accuracy of 0.989 upon validation.Four grading categories recognitionmodelswere developed based on color and texture features.The RBF-SVMoutperformed all the explored modelswith the highest accuracy of 0.9709 for healthy and defected category.However,the grading accuracy decreased as the number of grading categories increased.A combination of color and texture features achieved the highest accuracy in all the grading categories in image features evaluation.This proposed system can be used as an inline tomato sorting tool to ensure that quality standards are adhered to and maintained.
