Optical Techniques to Estimate the Ripeness of Red-Pigmented Fruits

Bodria, L.; Fiala, Marco; Guidetti, R.; Oberti, R.

doi:10.13031/2013.16077

Cited by 28 publications

(22 citation statements)

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“…Furthermore, this acquisition technique was proved to be suitable for a direct use to monitor quality parameters, SSC in particular, and good correlations were obtained (Beghi et al, 2013). Using vis/NIR technique, it was possible to estimate changes in the firmness and SSC of stored Red Delicious apples undergoing no detectable change in skin colour (Bodria et al, 2004).…”

Section: Introductionmentioning

confidence: 94%

“…In completely red-pigmented cultivars of fruits such as apples and peaches this process is not visible, being masked by the anthocyanins in the skin. Optical systems were developed to assess the chlorophyll content in these fruits in a non-destructive manner, to estimate ripeness, and to optimise harvesting and postharvest management (Bodria et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

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Characterisation of olive fruit for the milling process by using visible/near infrared spectroscopy

Beghi

Giovenzana

Civelli

et al. 2013

J Agricult Engineer

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Increasing consumption of olive oil and table olives has recently determined an expansion of olive tree cultivation in the world. This trend is supported by the documented nutritional value of the Mediterranean diet. The aim of this work was to test a portable visible/near infrared (vis/NIR) system (400-1000 nm) for the analysis of physical-chemical parameters, such as olive soluble solid content (SSC) and texture before the olive oil extraction process. The final goal is to provide the sector with post-harvest methods and sorting systems for a quick evaluation of important properties of olive fruit. In the present study, a total of 109 olives for oil production were analysed. Olive spectra registered with the optical device and values obtained with destructive analysis in the laboratory were analysed. Specific statistical models were elaborated to study correlations between optical and laboratory analysis, and to evaluate predictions of reference parameters obtained through the analysis of the visible-near infrared range. Statistical models were processed using chemometric techniques to extract maximum data information. Principal component analysis (PCA) was performed on vis/NIR spectra to examine sample groupings and identify outliers, while partial least square (PLS) regression algorithm was used to correlate samples spectra and physical-chemical properties. Results are encouraging. PCA showed a significant sample grouping among different ranges of SSC and texture. PLS models gave fairly good predictive capabilities in validation for SSC (R 2 =0.67 and RMSECV%=7.5%) and texture (R 2 =0.68 and RMSECV%=8.2%).

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Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Characterisation of olive fruit for the milling process by using visible/near infrared spectroscopy

Beghi

Giovenzana

Civelli

et al. 2013

J Agricult Engineer

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“…Song et al (1997) studied chlorophyll fluorescence for apple fruit during the harvest season and showed that fluorescence may have some practical use in sorting apples or other chlorophyll-containing fruits or vegetables on commercial packing lines. Bodria et al (2004) used a fluorescence imaging system equipped with a UVblue actinic light to obtain fluorescence images of fruit in which the gray level of pixels with the firmness of fresh apples. They reported that the R/IR index, defined as the ratio of the signal measured in red and near-infrared bands, was correlated with the chlorophyll content of the fruits, regardless of fruit species and anthocyanin presence, and this index could be used to track the postharvest ripening process for fresh peaches harvested at different maturity stages.…”

Section: Introductionmentioning

confidence: 99%

UV/blue Light-induced Fluorescence for Assessing Apple Quality

Noh¹,

Lu²

2010

Journal of Biosystems Engineering

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Chlorophyll fluorescence has been researched for assessing fruit post-harvest quality and condition. The objective of this preliminary research was to investigate the potential of fluorescence spectroscopy for measuring apple fruit quality. Ultraviolet (UV) and blue light was used as an excitation source for inducing fluorescence in apples. Fluorescence spectra were measured from 'Golden Delicious' (GD) and 'Red Delicious' (RD) apples using a visible/near-infrared spectrometer after one, three, and five minutes of continuous UV/blue light illumination. Standard destructive tests were performed to measure fruit firmness, skin and flesh color, soluble solids and acid content from the apples. Calibration models for each of the three illumination time periods were developed to predict fruit quality indexes. The results showed that fluorescence emission decreased steadily during the first three minutes of UV/blue light illumination and was stable within five minutes. The differences were minimal in the model prediction results based on fluorescence data at one, three or five minutes of illumination. Overall, better predictions were obtained for apple skin chroma and hue and flesh hue with values for the correlation coefficient of validation between 0.80 and 0.90 for both GD and RD. Relatively poor predictions were obtained for fruit firmness, soluble solids content, titrational acid, and flesh chroma. This research has demonstrated that fluorescence spectroscopy is potentially useful for assessing selected quality attributes of apple fruit and further research is needed to improve fluorescence measurements so that better predictions of fruit quality can be achieved.

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“…Song and coworker 18 used this technique to assess apple fruit quality during the harvest season and they suggested that chlorophyll fluorescence may have potential for sorting and grading apples. Bodria et al 19 obtained fluorescence images of fruit using an imaging system, and they reported that the ratio of the fluorescence signal measured in red and near-infrared wavebands correlated with the fruit chlorophyll content. Ariana et al 20 used a multispectral imaging system in three imaging modes (reflectance, visible light induced fluorescence, and UV induced fluorescence) to classify different types of apple disorder.…”

Section: Introductionmentioning

confidence: 99%

Integrating fluorescence and interactance measurements to improve apple maturity assessment

Noh

2006

SPIE Proceedings

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Fluorescence and reflectance (or interactance) are promising techniques for measuring fruit quality and condition. Our previous research showed that a hyperspectral imaging technique integrating fluorescence and reflectance could improve predictions of selected quality parameters compared to single sensing techniques. The objective of this research was to use a low cost spectrometer for rapid acquisition of fluorescence and interactance spectra from apples and develop an algorithm integrating the two types of data for predicting skin and flesh color, fruit firmness, starch index, soluble solids content, and titratable acid. Experiments were performed to measure UV light induced transient fluorescence and interactance spectra from 'Golden Delicious' apples that were harvested over a period of four weeks during the 2005 harvest season. Standard destructive tests were performed to measure maturity parameters from the apples. Principal component (PC) analysis was applied to the interactance and fluorescence data. A back-propagation feedforward neural network with the inputs of PC data was used to predict individual maturity parameters. Interactance mode was consistently better than fluorescence mode in predicting the maturity parameters. Integrating interactance and fluorescence improved predictions of all parameters except flesh chroma; values of the correlation coefficient for firmness, soluble solids content, starch index, and skin and flesh hue were 0.77, 0.77, 0.89, 0.99, and 0.96 respectively, with the corresponding standard errors of 6.93 N, 0.90%, 0.97 g/L, 0.013 rad, and 0.013 rad. These results represented 4.1% to 23.5% improvements in terms of standard error, in comparison with the better results from the two single sensing methods. Integrating interactance and fluorescence can better assess apple maturity and quality.

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Optical Techniques to Estimate the Ripeness of Red-Pigmented Fruits

Cited by 28 publications

References 0 publications

Characterisation of olive fruit for the milling process by using visible/near infrared spectroscopy

Characterisation of olive fruit for the milling process by using visible/near infrared spectroscopy

UV/blue Light-induced Fluorescence for Assessing Apple Quality

Integrating fluorescence and interactance measurements to improve apple maturity assessment

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