Literature DB >> 35244203

Non-destructive prediction of total soluble solids in strawberry using near infrared spectroscopy.

Ana Cristina Agulheiro-Santos1, Sara Ricardo-Rodrigues1, Marta Laranjo1, Catarina Melgão1, Rocío Velázquez2.   

Abstract

BACKGROUND: Near-infrared spectroscopy (NIRS) is considered to be a fast and reliable non-destructive technique for fruit analysis. Considering that consumers are looking for strawberries with good sweetness, texture, and appearance, producers need to effectively measure the ripeness stage of strawberries to guarantee their final quality. Therefore, the use of this technique can contribute to decreasing the high level of waste and delivering good ripe strawberries to consumers. The present study aimed to evaluate the predictive capacity of NIRS technology, as a possible alternative to conventional methodology, for the analysis of the main organoleptic parameters of strawberries (Fragaria × ananassa Duch.).
RESULTS: Spectroscopic measurements and physicochemical analyses [total soluble solids (TSS), titratable acidity, colour, texture] of 'Victory' strawberries were carried out. The predictive models developed for titratable acidity, colour and texture were not good enough to quantify those parameters. By contrast, in the NIRS quantitative prediction analysis of TSS, it was observed that the spectral pre-treatment with the highest predictive capacity was the first derivative 1-5-5. The coefficients of determination were: 0.9277 for the calibration model; 0.5755 for the validation model; and 0.8207 for the prediction model, using a seven-factor partial least squares multivariate regression analysis.
CONCLUSION: Therefore, these results demonstrate that NIR analysis could be used to predict the TSS in strawberry, and further work on sampling is desirable to improve the prediction obtained in the present study. It is shown that NIRS technology is a suitable tool for determining quality attributes of strawberry in a fast, economic, and environmentally friendly way.
© 2022 Society of Chemical Industry. © 2022 Society of Chemical Industry.

Entities:  

Keywords:  Fragaria × ananassa Duch.; NIRS; quality; ripeness; total soluble solids

Mesh:

Year:  2022        PMID: 35244203     DOI: 10.1002/jsfa.11849

Source DB:  PubMed          Journal:  J Sci Food Agric        ISSN: 0022-5142            Impact factor:   4.125


  1 in total

1.  Prediction of Total Soluble Solids and pH of Strawberry Fruits Using RGB, HSV and HSL Colour Spaces and Machine Learning Models.

Authors:  Jayanta Kumar Basak; Bolappa Gamage Kaushalya Madhavi; Bhola Paudel; Na Eun Kim; Hyeon Tae Kim
Journal:  Foods       Date:  2022-07-13
  1 in total

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