Determination of soluble solids and firmness of apples by Vis/NIR transmittance

SummaryThe objective of this study is to investigate the eff ects of irradiation from light-emitt ing diodes (LEDs) on several fruits during storage. To improve storage and increase the contents of some bioactive compounds, apple, tomato and red bell pepper fruits were exposed to yellow light emitt ed from the diodes at 590 nm. The contents of ascorbic acid, total phenolics, total fl avonoids and several pigments were investigated, along with the antioxidant potential. The colour parameters (L*, a* and b*) and fi rmness of the fruit were also determined. Aft er 7 days of LED light irradiation, there was signifi cantly higher total phenolic content and antioxidant potential in apple peel extracts. The irradiated fruit of tomato had signifi cantly higher levels of total phenolic compounds, and the fruit of red bell pepper had signifi cantly higher antioxidant potential. LED light had no eff ects on the colour parameters, although there was a tendency to accelerate colour development. Apple fruit irradiated with LED light was signifi cantly less fi rm. Among twelve analysed pigments, signifi cantly more β-carotene was detected in LED light-irradiated apple and bell pepper fruit, more α-tocopherol and γ-tocopherol in bell pepper fruit, and more lutein in apple peel and bell pepper fruit. The applied LED light slightly accelerated the ripening of the studied fruit, and aff ected the synthesis of some of the secondary metabolites.

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“…Firmness is an important factor for postharvest storage, and it is also important from a nutritional point of view (45). Fig.…”

Section: Resultsmentioning

confidence: 99%

Influence of Yellow Light-Emitting Diodes at 590 nm on Storage of Apple, Tomato and Bell Pepper Fruit

Kokalj

Hribar

Cigić

et al. 2016

Food Technol. Biotechnol.

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“…The number of tested melon fruits was 16, and the sensory index of each fruit was represented by the average score of each panelist. A 0-10 scale was used to rate the acceptability, [10,8) represents satisfactory, [8,6) average and [6, 0) dissatisfactory. The surrounded tissues of each evaluated position were crushed in a pressware and the resulting juice was assessed for SSC value Fruit¯rmness was measured by a hand-held penetrometer (GY-1, China) with a 3.5 mm diameter plunger.…”

Section: Sensory Evaluationmentioning

confidence: 99%

“…This inaccuracy was probably because the physical characteristic such as rmness plus the chemical compositions that contribute to¯rmness such as pectin, hemicellulose are not that high in concentration, meanwhile the quite subjective testing value got by hand-held penetrometer. 6 To improve the accuracy of nondestructive detection of melon mesocarp¯rmness, an appropriate reference analysis method should be considered.…”

Section: Modelingmentioning

confidence: 99%

“…It has already been tested for nondestructive evaluation of¯rmness, acidity, soluble solids and other physiological properties of many fruits including apple, 5,6 kiwi, 7 Satsuma mandarin, 8 watermelon 9 and mango. 10 In melon, the very¯rst publication was reported by Dull et al 11 in assessing the SSC of intact cantaloupe with a root mean square error of prediction (RMSEP) of 2.18, by using the two wavelengths 896 and 860 nm in 1989.…”

Section: Introductionmentioning

confidence: 99%

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Nondestructive determination of soluble solids and firmness in mix-cultivar melon using near-infrared CCD spectroscopy

Lü

Liu

et al. 2015

J. Innov. Opt. Health Sci.

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Nondestructive evaluation of melon quality is in great need of comprehensive study. Soluble solids content (SSC) and¯rmness are the two indicators of melon internal quality that mostly a®ect consumer acceptance. To provide guidance for fruit classi¯cation, internal quality standards was preliminarily established through sensory test, as: Melon with SSC over 12 Brix, rmness 4-5.5 kgf Á cm À2 were considered as satisfactory class sample; and SSC over 10 Brix, rmness 3.5-6.5 kgf Á cm À2 as average class sample. The near infrared (NIR) nondestructive detection program was set as spectra collected from the stylar-end, Brix expressed by the average SSC of inner and outer mesocarp, each cultivar of melon was detected with its own optimum integration time, and the second derivative algorithm was used to equalize them. Using wavelength selected by genetic algorithms (GA), a robust SSC model of mix-cultivar melon was established, the root mean standard error of cross-validation (RMSECV) was 0.99 and the ratio performance deviation (RPD) nearly reached 3.0, which almost could meet the accuracy requirement of 1.5 Brix. Firmness model of mix-cultivar melon was acceptable but inferior.

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“…Infrared spectroscopy has been widely used to evaluate the internal quality (SSC, pH, acidity and firmness et al) of fruits such as apple (Bobelyn et al 2010;Fan et al 2009), pear (Paz et al 2009;Sun et al 2009), orange (Liu et al 2010a;Liu et al 2010b), grape (Cao et al 2010), peach (Kurz et al 2010;Ziosi et al 2008), and kiwifruit (Clark et al 2004;Moghimi et al 2010) et al. The first attempts to establish the relationship between sensory texture and NIRS measurements were made by Mehinagic et al (2003) who reported good correlations between penetrometry and sensory texture but poor correlations between NIR and sensory data were found.…”

Section: Introductionmentioning

confidence: 99%

Non-destructive measurement of fracturability and chewiness of apple by FT-NIRS

Ren

et al. 2013

J Food Sci Technol

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In order to assess quickly and non-destructively the fracturability and chewiness of apple fruit by FT-NIR spectra in the wavelength range of 4000 cm −1 -12000 cm −1 , multivariate models were built using multiple linear regression (MLR), partial least squares regression (PLSR), and principal component regression (PCR). Fracturability and chewiness reference data were instrumentally measured using a Texture Profile Analysis (TPA) test. The effects of various pre-processing methods of the spectroscopic data on the performance of the multivariate models were analyzed. Standard normal variate transformation (SNV), multiplicative scatter correction (MSC), Min-Max normalization(MMN) and first derivative (FD) were tested. The performance of the fracturability prediction models was better for the PLSR model (R 2 =0.91, RMSEP=101.90) than for the PCR and MLR models. With regard to chewiness, the performance of the PCR model (R 2 =0.88, RMSEP=13.46) was similar to the one of the PLSR model but better than the one of the MLR model. The results demonstrated that NIR spectra together with stoichiometry could determine precisely fracturability and chewiness of apple, and the predictive ability of the models developed by other methods may be improved in the future.

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Determination of soluble solids and firmness of apples by Vis/NIR transmittance

Cited by 109 publications

References 17 publications

Influence of Yellow Light-Emitting Diodes at 590 nm on Storage of Apple, Tomato and Bell Pepper Fruit

Influence of Yellow Light-Emitting Diodes at 590 nm on Storage of Apple, Tomato and Bell Pepper Fruit

Nondestructive determination of soluble solids and firmness in mix-cultivar melon using near-infrared CCD spectroscopy

Non-destructive measurement of fracturability and chewiness of apple by FT-NIRS

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