Papaya(Carica papaya)is a tropical fruit having commercial importance because of its high nutritive and medicinal value.The packaging of papaya fruit as per its maturity status is an essential task in the fruit indust...Papaya(Carica papaya)is a tropical fruit having commercial importance because of its high nutritive and medicinal value.The packaging of papaya fruit as per its maturity status is an essential task in the fruit industry.The manual grading of papaya fruit based on human visual perception is time-consuming and destructive.The objective of this paper is to suggest a novel non-destructive maturity status classification of papaya fruits.The paper suggested two approaches based on machine learning and transfer learning for classification of papaya maturity status.Also,a comparative analysis is carried out with different methods of machine learning and transfer learning.The experimentation is carried out with 300 papaya fruit sample images which includes 100 of each three maturity stages.The machine learning approach includes three sets of features and three classifiers with their different kernel functions.The features and classifiers used in machine learning approaches are local binary pattern(LBP),histogram of oriented gradients(HOG),Gray Level Cooccurrence Matrix(GLCM)and k-nearest neighbour(KNN),support vector machine(SVM),Naı¨ve Bayes respectively.The transfer learning approach includes seven pretrained models such as ResNet101,ResNet50,ResNet18,VGG19,VGG16,GoogleNet and AlexNet.The weighted KNN with HOG feature outperforms other machine learningbased classification model with 100%of accuracy and 0.0995 s training time.Again,among the transfer learning approach based classification model VGG19 performs better with 100%accuracy and 1 min 52 s training time with consideration of early stop training.The proposed classification method for maturity classification of papaya fruits,i.e.VGG19 based on transfer learning approach achieved 100%accuracy which is 6%more than the existing method.展开更多
With papaya fruit ( Carica papaya ) as an experimental material, variations of its physiological indices were investigated through hypobaric hypoxia (HH, 10 kPa, 1.5 kPa O 2) treatment followed by fumigation with ...With papaya fruit ( Carica papaya ) as an experimental material, variations of its physiological indices were investigated through hypobaric hypoxia (HH, 10 kPa, 1.5 kPa O 2) treatment followed by fumigation with 1-methylcyclopropene (1-MCP), so as to discuss the effect of interaction between 1-MCP and internal ethylene on ripening of papaya fruit during postharvest storage. The results indicated that HH treatment significantly reduced internal ethylene concentration (IEC) by 57.6%. However, there were no remarkable differences in other physiological indices between various treatments and control (CK). The 1-MCP and HH+1-MCP treatments could significant postpone the softening process and color change of papaya fruit. The two treatments achieved the effects of significantly inhibiting the occurrence of fruit disease and the increase of pericarp cell membrane permeability, effectively delaying the variation of soluble solid and Vc contents, and better maintaining soluble solid and Vc contents in fruit, thereby better keeping nutritional substances and flavor quality in fruit in later storage period and prolonging the storage time of fruit.展开更多
基金the support the research grant under“Collaborative and Innovation Scheme”of TEQIP-Ⅲ with project title“Development of Novel Approaches for Recognition and Grading of Fruits using Image processing and Computer Intelligence”,with reference letter No.VSSUT/TEQIP/113/2020.
文摘Papaya(Carica papaya)is a tropical fruit having commercial importance because of its high nutritive and medicinal value.The packaging of papaya fruit as per its maturity status is an essential task in the fruit industry.The manual grading of papaya fruit based on human visual perception is time-consuming and destructive.The objective of this paper is to suggest a novel non-destructive maturity status classification of papaya fruits.The paper suggested two approaches based on machine learning and transfer learning for classification of papaya maturity status.Also,a comparative analysis is carried out with different methods of machine learning and transfer learning.The experimentation is carried out with 300 papaya fruit sample images which includes 100 of each three maturity stages.The machine learning approach includes three sets of features and three classifiers with their different kernel functions.The features and classifiers used in machine learning approaches are local binary pattern(LBP),histogram of oriented gradients(HOG),Gray Level Cooccurrence Matrix(GLCM)and k-nearest neighbour(KNN),support vector machine(SVM),Naı¨ve Bayes respectively.The transfer learning approach includes seven pretrained models such as ResNet101,ResNet50,ResNet18,VGG19,VGG16,GoogleNet and AlexNet.The weighted KNN with HOG feature outperforms other machine learningbased classification model with 100%of accuracy and 0.0995 s training time.Again,among the transfer learning approach based classification model VGG19 performs better with 100%accuracy and 1 min 52 s training time with consideration of early stop training.The proposed classification method for maturity classification of papaya fruits,i.e.VGG19 based on transfer learning approach achieved 100%accuracy which is 6%more than the existing method.
基金Supported by National Tropical Crop Germplasm Resource Platform Construction Project(2014-073)
文摘With papaya fruit ( Carica papaya ) as an experimental material, variations of its physiological indices were investigated through hypobaric hypoxia (HH, 10 kPa, 1.5 kPa O 2) treatment followed by fumigation with 1-methylcyclopropene (1-MCP), so as to discuss the effect of interaction between 1-MCP and internal ethylene on ripening of papaya fruit during postharvest storage. The results indicated that HH treatment significantly reduced internal ethylene concentration (IEC) by 57.6%. However, there were no remarkable differences in other physiological indices between various treatments and control (CK). The 1-MCP and HH+1-MCP treatments could significant postpone the softening process and color change of papaya fruit. The two treatments achieved the effects of significantly inhibiting the occurrence of fruit disease and the increase of pericarp cell membrane permeability, effectively delaying the variation of soluble solid and Vc contents, and better maintaining soluble solid and Vc contents in fruit, thereby better keeping nutritional substances and flavor quality in fruit in later storage period and prolonging the storage time of fruit.