Estimation model of soluble solids content in bagged and non-bagged apple fruits based on spectral data

Wang, Fengyun; Zhao, Yimin; Zheng, Jiangbin; Qi, Kangkang; Fan, Yangyang; Yuan, Xulin; Ruan, Huaijun

doi:10.1016/j.compag.2021.106492

Cited by 8 publications

(4 citation statements)

References 24 publications

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“…In recent years, apple, as a highly favored fruit, has shown continuous growth in both global production and consumption [ 1 ]. Apples are bagged during growth to prevent and remove fruit rust and surface blemishes, promote coloration, reduce pesticide residues, and improve storability [ 2 ]. Apples are removed from their protective bags about 14–20 days before the harvest period, which is very important for surface coloring and sugar conversion.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Nondestructive Detection Models of Apple Quality in Critical Harvest Period Based on Near-Infrared Spectroscopy and Intelligent Algorithms

Guo,

Chen,

Zhang

et al. 2024

Foods

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Apples are usually bagged during the growing process, which can effectively improve the quality. Establishing an in situ nondestructive testing model for in-tree apples is very important for fruit companies in selecting raw apple materials for valuation. Low-maturity apples and high-maturity apples were acquired separately by a handheld tester for the internal quality assessment of apples developed by our group, and the effects of the two maturity levels on the soluble solids content (SSC) detection of apples were compared. Four feature selection algorithms, like ant colony optimization (ACO), were used to reduce the spectral complexity and improve the apple SSC detection accuracy. The comparison showed that the diffuse reflectance spectra of high-maturity apples better reflected the internal SSC information of the apples. The diffuse reflectance spectra of the high-maturity apples combined with the ACO algorithm achieved the best results for SSC prediction, with a prediction correlation coefficient (Rp) of 0.88, a root mean square error of prediction (RMSEP) of 0.5678 °Brix, and a residual prediction deviation (RPD) value of 2.466. Additionally, the fruit maturity was predicted using PLS-LDA based on color data, achieveing accuracies of 99.03% and 99.35% for low- and high-maturity fruits, respectively. These results suggest that in-tree apple in situ detection has great potential to enable improved robustness and accuracy in modeling apple quality.

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Section: Introductionmentioning

confidence: 99%

Dynamic Nondestructive Detection Models of Apple Quality in Critical Harvest Period Based on Near-Infrared Spectroscopy and Intelligent Algorithms

Guo,

Chen,

Zhang

et al. 2024

Foods

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“…29−31 For apples, oranges, and other types of large fruits, the bagging technique is commonly used to avoid the retention of pesticides on the fruits; however, it is not applicable to Chinese wolfberry because its fruit is small and dense. 32,33 Researchers have found that using surfactants and oils adjuvants can increase the retention of liquids on hydrophobic surfaces, but on easily wetted surfaces, surfactant adjuvants will often cause excessive wetting, which leads to a decrease in retention instead. 34−36 Through the use of adjuvants can make droplets on different wetting properties of the surface to produce different changes, therefore, we expect to increase the retention of droplets on the leaf surfaces and reduce the retention on the fruit surfaces of Chinese wolfberry.…”

Section: Introductionmentioning

confidence: 99%

“…However, because the amount of pesticide retention on the surface is closely related to the pesticide residue, this often leads to an increase in the retention of pesticides on the nontarget surface (such as fruit, flower, etc. ), resulting in an increase in pesticide residues or even exceeding the limit. − For apples, oranges, and other types of large fruits, the bagging technique is commonly used to avoid the retention of pesticides on the fruits; however, it is not applicable to Chinese wolfberry because its fruit is small and dense. , …”

Section: Introductionmentioning

confidence: 99%

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Achieving High Efficacy and Low Safety Risk by Balancing Pesticide Deposition on Leaves and Fruits of Chinese Wolfberry (Lycium barbarum L.)

et al. 2023

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Pesticide residue has become the main technical barrier that restricts the export of Chinese wolfberry. Can we achieve high efficacy and low safety risk by balancing pesticide deposition on the leaves and fruits of Chinese wolfberry? In this research, the structural characteristics and wettability of leaves and fruits of Chinese wolfberry at different growth stages were studied. The adaxial and abaxial surfaces of leaves were hydrophobic, whereas the fruit surfaces were hydrophilic. Adding spray adjuvant could increase the retention of droplets on the leaf surfaces of Chinese wolfberry by 52.28–97.89% and reduce the retention on the fruit surfaces by 21.68–42.14%. A structural equation model analysis showed that the adhesion tension was the key factor affecting the retention of the solutions among various interface behaviors. When the concentrations of Silwet618, AEO-5, Gemini 31551, and 1227 were 2–5 times higher than their CMCs, the retention of pesticide solutions (pyraclostrobin and tylophorine) on Chinese wolfberry leaves significantly increased, and the control efficacies on aphids and powdery mildew also dramatically improved (65.90–105.15 and 41.18–133.06%, respectively). Meanwhile, the retention of pesticides on the fruit of Chinese wolfberry was reduced. This study provides new insights into increasing the utilization of pesticides in controlling pests and improving food safety.

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A novel hybrid variable selection strategy with application to molecular spectroscopic analysis

Zhu

Xin

Wang

et al. 2023

Chemometrics and Intelligent Laboratory Systems

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Estimation model of soluble solids content in bagged and non-bagged apple fruits based on spectral data

Cited by 8 publications

References 24 publications

Dynamic Nondestructive Detection Models of Apple Quality in Critical Harvest Period Based on Near-Infrared Spectroscopy and Intelligent Algorithms

Dynamic Nondestructive Detection Models of Apple Quality in Critical Harvest Period Based on Near-Infrared Spectroscopy and Intelligent Algorithms

Achieving High Efficacy and Low Safety Risk by Balancing Pesticide Deposition on Leaves and Fruits of Chinese Wolfberry (Lycium barbarum L.)

A novel hybrid variable selection strategy with application to molecular spectroscopic analysis

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