Monitoring the ripeness progress until the harvest is a crucial issue since fruit quality is closely related to it. Therefore, the research for non-destructive methods which could explore many samples and give a rapid and comprehensive overview of ripening would be helpful. Moreover, the evaluation of the postharvest quality, e.g. senescence of ready-to-eat vegetables, could be greatly helped by new analytical methods that are rapid and integrated into the production process to meet consumer demand. The aim of the research was to design, build and test prototypes of miniaturised low-cost and userfriendly devices envisaged mainly to support small-scale growers both in pre-harvest and in postharvest monitoring. The systems were tested on two case studies: (i) to monitor the ripening of wine grape until harvest and (ii) to evaluate the postharvest life of fresh-cut salad to discriminate freshness levels during the shelf life. Pre-prototypes of fully integrated, stand-alone optical device incorporating MEMS sensors (tuned photodiode arrays, interference filters, LEDS, optics) were designed and built. Two systems equipped with digital 6-channel sensors each for spectral identification in the visible and SW-NIR. The sensors cover 12 independent on-device optical filters from 400 nm to 860 nm. Optical analyses were collected on grape bunches and on leaves of fresh-cut salad using the two prototypes. Reference parameters (i.e. soluble solids content and titratable acidity for grape, and colour and senescence classes for fresh-cut salad) were analysed on each sample for the calculation of predictive models using MLR regression technique. The correlation between the optical data and the parameters were explored and the results were encouraging underlining a small loss of information comparing data from the prototypes to models from more expensive commercial vis/NIR devices.

Testing of optical prototypes for the fruit and vegetable sector : case studies from pre- to post-harvest / R. Beghi, V. Giovenzana, A. Tugnolo, A. Casson, R. Guidetti. ((Intervento presentato al convegno Biosystem Engineering for sustainable agriculture, forestry and food production : International Mid-Term Conference of the Italian Association of Agricultural Engineering (AIIA) tenutosi a Matera nel 2019.

Testing of optical prototypes for the fruit and vegetable sector : case studies from pre- to post-harvest

R. Beghi
Primo
;
V. Giovenzana
Secondo
;
A. Tugnolo;A. Casson
Penultimo
;
R. Guidetti
Ultimo
2019

Abstract

Monitoring the ripeness progress until the harvest is a crucial issue since fruit quality is closely related to it. Therefore, the research for non-destructive methods which could explore many samples and give a rapid and comprehensive overview of ripening would be helpful. Moreover, the evaluation of the postharvest quality, e.g. senescence of ready-to-eat vegetables, could be greatly helped by new analytical methods that are rapid and integrated into the production process to meet consumer demand. The aim of the research was to design, build and test prototypes of miniaturised low-cost and userfriendly devices envisaged mainly to support small-scale growers both in pre-harvest and in postharvest monitoring. The systems were tested on two case studies: (i) to monitor the ripening of wine grape until harvest and (ii) to evaluate the postharvest life of fresh-cut salad to discriminate freshness levels during the shelf life. Pre-prototypes of fully integrated, stand-alone optical device incorporating MEMS sensors (tuned photodiode arrays, interference filters, LEDS, optics) were designed and built. Two systems equipped with digital 6-channel sensors each for spectral identification in the visible and SW-NIR. The sensors cover 12 independent on-device optical filters from 400 nm to 860 nm. Optical analyses were collected on grape bunches and on leaves of fresh-cut salad using the two prototypes. Reference parameters (i.e. soluble solids content and titratable acidity for grape, and colour and senescence classes for fresh-cut salad) were analysed on each sample for the calculation of predictive models using MLR regression technique. The correlation between the optical data and the parameters were explored and the results were encouraging underlining a small loss of information comparing data from the prototypes to models from more expensive commercial vis/NIR devices.
set-2019
Settore AGR/09 - Meccanica Agraria
Italian Association of Agricultural Engineering
Università della Basilicata
Testing of optical prototypes for the fruit and vegetable sector : case studies from pre- to post-harvest / R. Beghi, V. Giovenzana, A. Tugnolo, A. Casson, R. Guidetti. ((Intervento presentato al convegno Biosystem Engineering for sustainable agriculture, forestry and food production : International Mid-Term Conference of the Italian Association of Agricultural Engineering (AIIA) tenutosi a Matera nel 2019.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/676290
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