Potential of Vis-NIR spectroscopy for detection of chilling injury in kiwifruit

Wang, Zhen; Künnemeyer, Rainer; McGlone, Andrew; Burdon, J.

doi:10.1016/j.postharvbio.2020.111160

Cited by 39 publications

(29 citation statements)

References 27 publications

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“…Therefore, the actual µ s ’ should be lower than the predicted µ s ’. Since ‘SunGold™’ kiwifruit have a more uniform shape and quality parameters, the difference in predicted µ s ’ was assumed to be due to the granular or water soaking tissue as these CI symptoms usually develop from the stylar end region [ 16 ].…”

Section: Resultsmentioning

confidence: 99%

“…For ‘SunGold™’ kiwifruit, a high classification accuracy of CI was observed for subsampled sound fruit and CI fruit using LBI parameters ( Table 4 ). Higher classification accuracy of CI was obtained using LBI taken at the stylar end region compared to images acquired at the equator, possibly because the kiwifruit stylar end is the likely location for initial CI development [ 16 ]. Using whole fruit LBI parameter information acquired from both locations, the classification accuracy of sound and moderate kiwifruit was slightly improved.…”

Section: Resultsmentioning

confidence: 99%

“…The CI assessment was carried out at the four locations matching the LBI measurement area. The severity score was obtained using a scale provided by Wang et al and was recorded as CI se and CI eq for the stylar end and equatorial section of kiwifruit, respectively [ 16 ].…”

Section: Methodsmentioning

confidence: 99%

“…Near infrared (NIR) spectroscopy has been applied earlier to detect CI in fruit and vegetables [ 15 ]. Wang et al segregated sound kiwifruit and kiwifruit with CI using NIR spectral information and reported a stronger separation at the stylar end compared to the analysis in the equatorial region [ 16 ]. Kemsley et al investigated NIR diffuse optical tomography at 689 nm and reported internal defect detection in potatoes [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

“…Since CI involves pigment changes for some crops, the capacity of spectral data in CI detection appears reasonable. In Wang et al’s study [ 16 ], kiwifruit were segregated in severe CI cases when discolouration had already occurred. Cen et al applied selected wavelengths and image features to detect CI symptoms of brown spots in cucumber and achieved 100% classification accuracy for a two-class classification [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

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Application of Absorption and Scattering Properties Obtained through Image Pre-Classification Method Using a Laser Backscattering Imaging System to Detect Kiwifruit Chilling Injury

Yang

Li²,

East³

et al. 2021

Foods

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Kiwifruit chilling injury (CI) damage occurs after long-term exposure to low temperature. A non-destructive approach to detect CI injury was tested in the present study, using a laser backscattering image (LBI) technique calibrated with 56 liquid phantoms for providing absorption coefficient (µa) and reduced scattering coefficient (µs’). Calibration of LBI resulted in a true-positive (TP) classification of 91.5% and 65.6% of predicted µs’ and µa, respectively. The optical properties of ‘SunGold™’and ‘Hayward’ kiwifruit were analysed at 520 nm with a two-step protocol capturing pre-classification according to the LBI parameters used in the calibration and estimation with the Farrell equation. Severely injured kiwifruit showed white corky tissue and water soaking, reduced soluble solids content and firmness measured destructively. Non-destructive classification results for ‘SunGold™’ showed a high percentage of TP for severe CI of 92% and 75% using LBI parameters directly and predicted µa and µs’ after pre-classification, respectively. The classification accuracy for severe CI ‘Hayward’ kiwifruit with LBI parameter was low (58%) and with µa and µs’ decreased further (35%), which was assumed to be due to interference caused by the long trichomes on the fruit surface.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of Absorption and Scattering Properties Obtained through Image Pre-Classification Method Using a Laser Backscattering Imaging System to Detect Kiwifruit Chilling Injury

Yang

Li²,

East³

et al. 2021

Foods

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Identification and classification of chill‐damaged versus sound kiwifruit using Raman spectroscopy and chemometrics

Samanali,

Burritt,

Burdon

et al. 2023

J Raman Spectroscopy

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The early detection of fruit disorders is crucial to maintaining a consistent, high‐quality kiwifruit product. Chilling injury is a physiological disorder found in kiwifruit that can be challenging to identify until it reaches a severe stage or the fruit is cut and opened. Considering this, Raman spectroscopy combined with chemometrics was investigated for sound and chill‐damaged ‘Zesy002’ kiwifruit. We carried out spectral analysis on fruit harvested in 2018 and 2019. Damaged and sound fruit samples were separated based on spectral signatures from phenyl propanoids and sugars. Furthermore, the 2018 fruit sample set was used to construct, validate, and test models using support vector machine, principal component analysis–linear discriminant analysis, and partial least squares–discriminant analysis. Additionally, the robustness of the model was assessed using the 2019 fruit sample set considering test set accuracy, sensitivity, and specificity. Support vector machine models were developed and resulted in a 93% accuracy, 85% sensitivity, and 100% specificity to differentiate the test set fruit (2018 season). Principal component analysis–linear discriminant analysis models and partial least squares–discriminant analysis model built with the same data set gave >83% and 93% test accuracy, respectively. Models showed robustness with samples from the 2019 season. This study provides insights into the potential of using Raman spectroscopy for identifying chilling injury in kiwifruit.

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Nondestructive discrimination of Potentilla anserina L. from different production areas based on near‐infrared spectroscopy

Ma,

Hai,

Zhang

et al. 2024

Phytochemical Analysis

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IntroductionThe traditional Chinese medicine (TCM) Potentilla anserina L. can use both as food and medicine. At present, the market mainly depends on experience to identify the species and determine the production areas of P. anserina. To ensure the quality of P. anserina, it is essential to improve the level of quality control.ObjectiveWe aimed to establish a rapid and nondestructive discrimination model to identify P. anserina from different production areas by near‐infrared spectroscopy.MethodsThe spectra of complete P. anserina medicinal materials and their powder of the same variety from four production areas were collected, and principal component analysis discriminant analysis and partial least squares discriminant analysis (PLS‐DA) were conducted based on different pretreatment methods and band selection methods. Then, the spectra of complete medicinal materials were converted into the spectra of medicinal powder for nondestructive identification.ResultsThe correct recognition rate (CRR) of the PLS‐DA discriminant model was the best after spectral preprocessing using autoscaling and competitive adaptive reweighted sampling for band selection. The CRRs of the calibration set and validation set were 100%, the CRRs of the external test set were 95%, 90%, 82%, and 88%, respectively, and the CRRs of the transfer external test set were 84%, 80%, 82%, and 86%, respectively.ConclusionWe realized the nondestructive and effective identification of P. anserina from different origins and laid a foundation for the industrialization and upgrading of TCM.

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Potential of Vis-NIR spectroscopy for detection of chilling injury in kiwifruit

Cited by 39 publications

References 27 publications

Application of Absorption and Scattering Properties Obtained through Image Pre-Classification Method Using a Laser Backscattering Imaging System to Detect Kiwifruit Chilling Injury

Application of Absorption and Scattering Properties Obtained through Image Pre-Classification Method Using a Laser Backscattering Imaging System to Detect Kiwifruit Chilling Injury

Identification and classification of chill‐damaged versus sound kiwifruit using Raman spectroscopy and chemometrics

Nondestructive discrimination of Potentilla anserina L. from different production areas based on near‐infrared spectroscopy

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