Nondestructive prediction of maturity of mango using near infrared spectroscopy

Jha, Shyam Narayan; Narsaiah, K.; Jaiswal, Pranita; Bhardwaj, Rishi; Gupta, Mansha; Kumar, Ramesh; Sharma, Rajiv

doi:10.1016/j.jfoodeng.2013.10.012

Cited by 72 publications

(33 citation statements)

References 24 publications

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“…NIR spectroscopy has been extensively adopted to measure the internal qualities of fruits such as apple (Bobelyn et al, 2010;Pissard et al, 2013), mango (Jha et al, 2014), orange (Antonucci et al, 2011;Liu et al, 2010a;Liu et al, 2010b;Magwaza et al, 2013;Sánchez et al, 2013;Wang et al, 2014;Xudong et al, 2009), and pear (Li et al, 2013). (Xudong et al, 2009) developed a portable NIR spectroscopy system for assessing the quality of Nanfeng mandarin fruit.…”

Section: Introductionmentioning

confidence: 99%

Determination of internal qualities of Newhall navel oranges based on NIR spectroscopy using machine learning

Liu

Yang

Deng

2015

Journal of Food Engineering

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Section: Introductionmentioning

confidence: 99%

Determination of internal qualities of Newhall navel oranges based on NIR spectroscopy using machine learning

Liu

Yang

Deng

2015

Journal of Food Engineering

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“…By using NIR, one mango can be examined in a short period of time without the preparation of sample or chemical application (Mahayothee et al, 2002). NIRS had been used on many varieties of mango (Schmilovitch et al, 2000;Jha et al, 2014;Saranwong et al, 2001;Saranwong et al, 2003). Short wavelength region (700 -1100 nm) was more appropriate for the quality evaluation of Thai mango, Namdokmai mango because its penetration depth into the flesh was higher than that of the long wavelength region (110-2500 nm) (Saranwong et al, 2001).…”

Section: Near Infrared Spectroscopic (Nir)mentioning

confidence: 99%

Quality evaluation of mango using non-destructive approaches: A review

2020

JAFE

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Mango (Mangifera indica L.) is one of the most popular and nutritionally rich fruits. It is also acknowledged as the king of fruits in India. Quality attributes of mango fruit depends on its appearances such as size, shape, skin colour, flesh colour, flavour, sweetness, and aroma. Over the recent years, non-destructive techniques have been garnering the interest of researchers as potential technologies that can be used for quality assessment of fruits in a part of postharvest processing. The present patterns of non-destructive techniques are more efficient, inexpensive, yield faster and accurate results. This mini review paper focuses on some of the previous applications of non-destructive techniques in quality evaluation of mango, focusing specifically on the non-destructive technique based on quality parameters. The future trend of using non-destructive techniques for quality evaluation is also discussed in this review paper.

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“…Classic studies on portable NIR spectrometers to estimate quality parameters in mangoes were reported by Mahayothee et al (), Saranwong et al (), and Subedi, Walsh, and Owens (). More recently, a portable Luminar 5030 NIR was used by Jha et al () to assess a maturity index estimated based on SSC, DM, and TA in seven mango varieties. Rungpichayapichet, Mahayothee, Nagle, Khuwijitjaru, and Müller () used a portable VIS‐NIR photo‐diode array spectrometer (HandySpec Field 1000, tec5AG) to study mango fruit quality and maturity and good results were reported for SSC prediction, standard error of prediction (SEP) of 1.2% and a correlation coefficient ( R 2 ) of 0.90, for firmness prediction (SEP of 4.22 N and R 2 of 0.82), and for TA prediction (SEP of 0.38% and R 2 of 0.74).…”

Section: Introductionmentioning

confidence: 99%

Cold storage of ‘Palmer’ mangoes sorted based on dry matter content using portable near infrared (VIS-NIR) spectrometer

Neto

Leite

Oliveira

et al. 2018

J Food Process Preserv

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The objective of this study was to use dry matter (DM) calibration models to sort ‘Palmer’ mangoes prior cold storage and to evaluate the physiological and chemical changes during the storage period. PLS model developed with fruit from 2015/2016 season was not adequate to predict DM content in fruit from 2016/2017 (not adjusted R2). Therefore, VIS‐NIR spectra from 2016/2017 season were incorporated into data set and a new model was developed (RMSEcv of 10.5 g.kg−1, RnormalP2 of 0.75). With the new model, ‘Palmer’ mangoes were sorted into two maturity stages (150 g.kg−1 and 110 g.kg−1) which resulted in quality differences mainly in relation to DM and SSC. Portable VIS‐NIR spectrometer can be used to sort fruit according to maturity stages based on DM content and this classification affect fruit quality during cold storage as fruit with higher DM (150 g.kg−1) presented better quality than fruit with lower DM (110 g.kg−1). Practical applications Although results can be found regarding the use of portable NIR spectrometers to estimate maturity in mango fruit, there are no studies stating the use of this method to sort fruit prior cold storage. Our results highlight that portable VIS‐NIR spectrometer can be used to sort fruit according to maturity stages based on dry matter (DM) content and this classification affects fruit quality during cold storage as fruit with higher DM (150 g.kg−1) presented better quality than fruit with lower DM (110 g.kg−1) at the end of the storage period.

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Nondestructive prediction of maturity of mango using near infrared spectroscopy

Cited by 72 publications

References 24 publications

Determination of internal qualities of Newhall navel oranges based on NIR spectroscopy using machine learning

Determination of internal qualities of Newhall navel oranges based on NIR spectroscopy using machine learning

Quality evaluation of mango using non-destructive approaches: A review

Cold storage of ‘Palmer’ mangoes sorted based on dry matter content using portable near infrared (VIS-NIR) spectrometer

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