Abstract
This study aims to utilize non-destructive sensing based on Vis-NIR spectroscopy and acoustic to predict firmness of avocado fruit. The study has three aims,the first aim was to find the best reference firmness measurement technique for calibrating Vis-NIR spectroscopy data related to avocado ripeningi.e., acoustic firmness (AF), limited compression (LC) and penetrometer max force (Fmax). The second aim was to study the generalizability of Vis-NIR models with respect to the dehydration level of avocado fruits. Dehydration of outer skinduring storage is common and may causemodel failureas the Vis-NIR signal is dominated by signal corresponding to high moisture in fresh fruit. The third aim was to fuse the Vis-NIR spectroscopy and acoustic information to improve the prediction of the LC and Fmax, otherwise unattainable with a single technique. The results showed that the best models for firmness prediction were obtained with LC as the reference. Theavocado skindehydrationnegatively affected the performance of Vis-NIR models to predict firmness. Further, a fusion of Vis-NIR spectroscopy and acoustic information improved prediction (reduced error by 21%) of firmness in avocado. Assessing avocado firmness in a multi-sensor framework can allow to precisely access the ripeness stage of avocados.
Highlights
Rapid non-destructive estimation of fruit quality allows the best management of fruit supply chain, starting from harvest up to the con sumer [1][2]
A summary of reference measurements for samples treated under two different relative humidity (RH) (45 and 90%) conditions is shown in Table 2 and a further ANOVA analysis for each measured trait is supplied as supplementary
Different RH treatments were given to fruit samples to cause dehydration of the samples for testing generalizability of Vis-NIR models
Summary
Rapid non-destructive estimation of fruit quality allows the best management of fruit supply chain, starting from harvest up to the con sumer [1][2] Fruit quality parameters such as dry matter (DM), soluble solids content (SSC) and firmness are of key importance and supply in direct access to fruit maturity and quality levels [3]. Some techniques can be found in relation to non-destructive firmness prediction of avo cado fruit such as acoustics [17,18], low mass impact sensor [19], portable NIR spectroscopy [20] and laser doppler vibrometer (LDV) [21] All these techniques supply an estimation of avocado firmness but are still too limited in their performance to be integrated with real-life commercial sorting line scenario or for routine analysis of avocado firmness in a non-destructive way
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