SSC and pH for sweet assessment and maturity classification of harvested cherry fruit based on NIR hyperspectral imaging technology

Liu, Yuanyuan; Wei, Yuzhen; Xu, Jie; Feng, Xuping; Wu, Feiyue; Zhou, Ruiqing; Jin, Juanjuan; Xu, Kaiwen; Yu, Xinjie; He, Yong

doi:10.1016/j.postharvbio.2018.05.003

Cited by 123 publications

(75 citation statements)

References 31 publications

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“…Xiao et al () applied CARS algorithm to select 40 key wavelengths from NIR spectroscopy for SSC prediction with r p 2 of 0.914 in grapes. Li et al () utilized GA and SPA algorithm to reduce the modeling complexity in SSC and pH prediction in cherry fruit by NIR hyperspectral imaging. Thus, the objectives of this study were to: (1) investigate the potential of Vis/NIR spectroscopy for on‐line discrimination of postharvest storage time and prediction of post‐harvest quality for strawberry fruit; and (2) explore the effectiveness of wavelengths selection for model simplification and performance promotion.…”

Section: Introductionmentioning

confidence: 99%

On‐line discrimination of storage shelf‐life and prediction of post‐harvest quality for strawberry fruit by visible and near infrared spectroscopy

Shen

Zhang

Cao

et al. 2018

J Food Process Engineering

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Quick assessment of storage time is important for the guarantee of fruit shelf‐life. On‐line discrimination of refrigerated storage time and prediction of post‐harvest quality for strawberry fruit was carried out by visible and near‐infrared (Vis/NIR) spectroscopy. For the classification of samples with storage time of 1, 3, 5, and 7 days, partial least square discriminant analysis (PLS‐DA) achieved correct classified rates of 93.3–97.4% in prediction based on selected wavelengths obtained by competitive adaptive reweighted sampling (CARS) at speeds of 0.05, 0.10, and 0.15 m/s. Moreover, for prediction of soluble solids content (SSC) in strawberry, the determination coefficient (rp2), root mean square error of prediction (RMSEP), and RPD value obtained by PLS coped with CARS at fruit moving speed of 0.10 m/s was 0.733, 0.699 °Brix and 1.96, respectively. Overall, this study indicates that Vis–NIR spectroscopy offers the potential as an on‐line tool for quality assurance of strawberry fruit. Practical applications Visible and near‐infrared (Vis/NIR) spectroscopy is a very attractive technique for nondestructive evaluation of quality of food products. Strawberry has an extremely short shelf‐life which is estimated to be less than 5 days. Rapid identification its postharvest storage time is essential for the evaluation of its shelf‐life. Based on the results reported here, Vis–NIR has the potential for on‐line monitoring of postharvest storage time and post‐harvest quality for strawberry fruit in real situation.

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Section: Introductionmentioning

confidence: 99%

On‐line discrimination of storage shelf‐life and prediction of post‐harvest quality for strawberry fruit by visible and near infrared spectroscopy

Shen

Zhang

Cao

et al. 2018

J Food Process Engineering

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“…The chemical and physical parameters that define intrinsic quality are often determined simultaneously thanks to the use of multicomponent calibrations. For this reason, various works report both data relating to direct index measurements (quantitative parameters) and indirect indices (pH, titratable acidity, texture characteristics, and sensory parameters) [40-63]: They are reported in Table 1 with the same legend group (P) [30,128,[146][147][148][149][150][151][152]. In order to get an idea of the predictive ability of a model, a number of statistical measures were used.…”

Section: Direct and Indirect Propertiesmentioning

confidence: 99%

Review: NIR Spectroscopy as a Suitable Tool for the Investigation of the Horticultural Field

Cattaneo

Stellari

2019

Agronomy

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The last 10 years of knowledge on near infrared (NIR) applications in the horticultural field are summarized. NIR spectroscopy is considered one of the most suitable technologies of investigation worldwide used as a nondestructive approach to monitoring raw materials and products in several fields. There are different types of approaches that can be employed for the study of key issues for horticultural products. In this paper, an update of the information collected from the main specific International Journals and Symposia was reported. Many papers showed the use of NIR spectroscopy in the horticultural field, and the literature data were grouped per year, per product, and per application, such as studies of direct (chemical composition) and indirect (physical and sensorial) properties (P), process control (PC), and authenticity and classification studies (AC). A mention was made of a recent innovative approach that considers the contribution of water absorption in the study of biological systems.

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“…The method starts at one wavelength and then calculates its projection at the unselected wavelength in each loop. The wavelength with the maximum projection vector is introduced into the wavelength combination (Li et al, 2018;Liu & Zhang, 2012). The x-loading weights (x-LW) method is based on the PLS modeling results.…”

Section: Effective Wavelength Selectionmentioning

confidence: 99%

“…In recent years, spectroscopy has been proposed as a nondestructive crispness detection technique. Some studies have explored spectroscopy as a method for the nondestructive analysis of other crops and fruits, research which has included apples (Dong & Guo, ; Kong, Zhang, Huang, Liu, & He, ; Li et al, ; Peng et al, ; Sun, Künnemeyer, Mcglone, & Rowe, ). Spectroscopy techniques were also used in other fields such as oil and soil detection (Feng et al, ; He et al, ; Nie, Dong, He, & Xiao, ).…”

Section: Introductionmentioning

confidence: 99%

Nondestructive detection of apple crispness via optical fiber spectroscopy based on effective wavelengths

Zhu

2019

Food Science & Nutrition

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Crispness is regarded as a significant quality index for apples. Currently, destructive sensory evaluation is the accepted method used to detect apple crispness, making it essential to develop a method that can detect apple crispness in a nondestructive manner. In this study, spectroscopy was proposed as the nondestructive technique for detecting apples' crispness, ultimately obtaining a spectral reflectance curve between 450 nm and 1,000 nm. In order to simplify and improve modeling efficiency, successive projections algorithm (SPA) and x‐loading weights (x‐LW) methods were used to select the most effective wavelengths. Partial least squares (PLS) algorithm, radial basis neural networks (RBNN), and multilayer perceptron neural networks (MLPNN) methods were used to establish the models and to predict the crispness of “Fuji” and “Qinguan” apple varieties. Based on the full wavelength (FW), the prediction accuracy of the PLS model for “Fuji” and “Qinguan” apple varieties was 92.05% and 95.87%, respectively. The effective wavelengths selected via SPA for the “Fuji” apple variety were 450.41 nm, 476.80 nm, 677.75 nm, and 750.72 nm, and the effective wavelengths selected via x‐LW for the “Qinguan” apple variety were 542.51 nm, 544.79 nm, 676.96 nm, and 718.29 nm. The prediction accuracy of the PLS model based on effective wavelengths for “Fuji” and “Qinguan” apple varieties reached 91.31% and 96.41%, respectively. Compared with the RBNN model, the MLPNN model achieved better prediction results for both “Fuji” and “Qinguan” apples, with the prediction accuracy reaching 97.8% and 99.9%, respectively. Based on the above findings, effective wavelength selection and MLPNN modeling were able to detect apple crispness with the highest accuracy. Overall, it can be concluded that the less effective wavelengths are conducive to developing an instrument for crispness detection.

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SSC and pH for sweet assessment and maturity classification of harvested cherry fruit based on NIR hyperspectral imaging technology

Cited by 123 publications

References 31 publications

On‐line discrimination of storage shelf‐life and prediction of post‐harvest quality for strawberry fruit by visible and near infrared spectroscopy

On‐line discrimination of storage shelf‐life and prediction of post‐harvest quality for strawberry fruit by visible and near infrared spectroscopy

Review: NIR Spectroscopy as a Suitable Tool for the Investigation of the Horticultural Field

Nondestructive detection of apple crispness via optical fiber spectroscopy based on effective wavelengths

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