Optical non-destructive techniques for small berry fruits: A review

Li, Shuping; Luo, Hongpei; Hu, Menghan; Zhang, Miao; Feng, Jun; Liu, Yangtai; Dong, Qingli; Liu, Baolin

doi:10.1016/j.aiia.2019.07.002

Cited by 31 publications

(15 citation statements)

References 149 publications

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“…Firmtech II; Li et al., 2011 ; Giongo et al., 2019 ), laser induced method ( Li et al., 2011 ), hyperspectral imaging ( Hu et al., 2015 ), or Vis-NIR spectroscopy ( Hu et al., 2018 ). Application limits of these non-destructive techniques are still the need of a constant updated calibration of the predictive multivariate algorithm, and the low spatial and spectral resolution ( Li et al., 2019 ). Moreover, for the phenotyping pipeline that we proposed ( Figure 8 ) the destructive assessment of texture is not a limiting factor, since analysed fruit can be employed for the analysis of other quality traits, such as total soluble solids, titratable acidity, and VOCs.…”

Section: Discussionmentioning

confidence: 99%

Development of a Novel Phenotypic Roadmap to Improve Blueberry Quality and Storability

et al. 2020

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Improved fruit quality and prolonged storage capability are key breeding traits for blueberry (Vaccinium spp.) fruit. Until now, breeding selection was mostly oriented on the amelioration of agronomic traits, such as flowering time, chilling requirement, or plant structure. Up until now, however, the storage effect on fruit quality has not been extensively studied, mostly because objective and handy phenotyping tools to evaluate quality traits were not available. In this study we are proposing a novel phenotyping protocol to support breeding selection and quality control within the entire blueberry production chain. Volatile organic compounds (VOCs) and texture traits, were measured by Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS) and a texture analyzer respectively, taking into consideration the influence of prolonged storage. The exploitation of the genetic variability existing within the investigated blueberry germplasm collection (including both southern and northern highbush, hybrids, and rabbiteyes) allowed the identification of the best performing cultivars, based on texture and VOCs variability, to be used as superior parental lines for future breeding programs. The comprehensive characterization of blueberry aroma allowed the identification of a wide array of spectrometric features, mostly related to aldehydes, alcohols, terpenoids, and esters, that can be used as putative biomarkers to rapidly evaluate the blueberry aroma variations related to genetic differences and storability. In addition, this study revealed a lack of straightforward relationship between harvest and postharvest quality features, that might be genotype-dependent.

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Section: Discussionmentioning

confidence: 99%

Development of a Novel Phenotypic Roadmap to Improve Blueberry Quality and Storability

et al. 2020

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“…Therefore, to ensure the feasibility and robustness of the proposed technique, a closed box is necessary when we acquire the spectral reflectance of strawberry leaves in a field environment. Before spectra reflectance acquisition, the instrument was calibrated with a 99% reference whiteboard [27,28]. For each leaf sample measurement, the scan was repeated 32 times at the same position, and the mean spectral reflectance value was recorded as the raw reflectance of the leaf for subsequent analysis.…”

Section: B Spectral-reflectance Acquisitionmentioning

confidence: 99%

Nitrogen Status Assessment for Multiple Cultivars of Strawberries Using Portable FT-NIR Spectrometers Combined With Cultivar Recognition and Multivariate Analysis

Wu¹,

Jiang²,

Bai

et al. 2020

IEEE Access

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The nondestructive assessment of nitrogen status in strawberry was performed to analyze its growth and provide guidance for precise management of N fertilizer using Fourier transform near-infrared reflectance (FT-NIR) spectroscopy with leaf spectral reflectance. The leaf soil plant analysis development (SPAD) value is considered as an indicator that indirectly reflects the nitrogen status in strawberry. However, the variation of cultivars leads to differences in the cell structure and light scattering and/or reflection effects of strawberry leaves during strawberry N status assessment, which means, leaf SPAD threshold value and the specific N demand will vary with different cultivars. As a result, accurate measurement of SPAD values and N status in strawberries with multiple cultivars is still challenging. In this study, the individual-cultivar, hybrid-cultivar, and multi-cultivar models were developed for the determination of SPAD values, and the performance of the models in lessening the impact of cultivar variation was studied and compared. The individual-cultivar model was constructed on the basis of a single cultivar of strawberry leaf. The hybridcultivar model was developed by merging the spectrum reflectance data and SPAD values of all studied leaf samples, and a multi-cultivar model was built in combination with cultivar identification, individual-cultivar models, and model search strategy. The results indicated that the multi-cultivar model was superior to the other two models for SPAD value estimation of strawberry leaves from different cultivars, with the overall Rp and RMSEP values of 0.966 and 0.468, respectively. We demonstrate that the leaf N content of strawberry is profoundly affected by cultivar variation, and establishing a multi-cultivar model is useful in monitoring the nitrogen status and guiding N fertilization recommendations for different strawberry cultivars.

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“…The detector covered the spectral wavelength range between 340 and 1030 cm -1 , with a spectral resolution of 3.4 nm and a sampling interval of 1.4 nm. Before spectra reflectance acquisition, the instrument was calibrated with the 99% reference whiteboard [27,28]. For each leaf sample measurement, the scan was repeated 32 times at the same position and the mean spectral reflectance value was recorded as the raw reflectance of the leaf for subsequent analysis.…”

Section: Spectral Reflectance Acquisitionmentioning

confidence: 99%

Nitrogen status assessment for multiple cultivars of strawberries using portable NIR spectrometers combined with cultivar recognition and multivariate analysis

Jiang

Bai

et al. 2019

Preprint

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Background The assessment of nitrogen status non-destructively in strawberry was performed to indicate its growth and provide guidance for precise management of N fertilizer using near-infrared reflectance (NIR) spectroscopy with leaf spectral reflectance. The Leaf soil plant analysis development (SPAD) value was thought as an indicator data that indirectly reflects nitrogen status in strawberry. However, the variation of cultivars would lead to differences in the cell structure and light scattering and/or reflection effects of strawberry leaves when assessed strawberry N status, which caused that no single leaf SPAD threshold value or same N demand can be applied for all strawberry cultivars. As a result, accurate detection of SPAD values and N status in strawberries with multiple cultivars is still challenging.Results In this study, Individual-cultivar model, hybrid-cultivar model and multi-cultivar model were developed for the determination of SPAD values, and the performance of the models in lessening the impact of cultivar variation were studied and compared. Individual-cultivar model was constructed on the basis of the single cultivar of strawberry leaf; hybrid-cultivar model was developed by merging the spectrum reflectance data and SPAD values of all studied leaf samples, and multi-cultivar model was built in combination with cultivar identification, individual-cultivar models, and model search strategy.Conclusion The results indicated that multi-cultivar model was more superior to the other two models for SPAD values estimation of strawberry leaves from different cultivars, with the overall Rp and RMSEP value respectively being 0.966 and 0.468. We demonstrate that the leaf N content per strawberry is profoundly affected by cultivar variation, and establishing a multi-cultivar model might be more useful in monitoring nitrogen status and guiding N fertilization recommendations for different strawberry cultivars.

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Optical non-destructive techniques for small berry fruits: A review

Cited by 31 publications

References 149 publications

Development of a Novel Phenotypic Roadmap to Improve Blueberry Quality and Storability

Development of a Novel Phenotypic Roadmap to Improve Blueberry Quality and Storability

Nitrogen Status Assessment for Multiple Cultivars of Strawberries Using Portable FT-NIR Spectrometers Combined With Cultivar Recognition and Multivariate Analysis

Nitrogen status assessment for multiple cultivars of strawberries using portable NIR spectrometers combined with cultivar recognition and multivariate analysis

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