Abstract
This study aims to test the hypothesis that skin dehydration can cause the development of cork-like layers in the avocado fruit skin which may negatively affect Vis-NIR spectroscopy. To test this, dehydration treatment was applied on avocado fruit by storing them at low relative humidity (RH) during ripening treatment. Furthermore, to demonstrate that the hypothesis was not only valid for a single instrument and in general valid for any type of Vis-NIR instrument the avocados were also measured with two different spectrometers i.e., lab-based, and hand-held. Since the two instruments have two different measurement geometries i.e., diffuse reflection and interaction, the study also tests which geometry was best for the measurement of DMC in dehydrated avocados. The results showed that the dehydration of avocado fruit negatively affects the performance of Vis-NIR calibrations compared to the non-dehydrated fruit. The root mean squared error of cross-validation (RMSEcv) on internal test set for dehydrated and non-dehydrated fruit were up to 1.49 % dw/fw and 1.02 % dw/fw, respectively. The hypothesis was true for both lab-based and hand-held instruments, and the root mean squared error of prediction on internal test set were up to 28 % higher for dehydrated fruits. The performance of interaction measurement mode was better (RMSEcv = 0.98 % dw/fw) than the diffuse reflection mode (RMSEcv = 1.21 % dw/fw) for non-dehydrated fruit, however, both modes achieved similar performance (RMSEcv = ∼1.42 % dw/fw) for dehydrated fruit. The poorer performance of Vis-NIR models on dehydrated avocado fruit can be accepted as a limitation of Vis-NIR spectroscopy for avocado fruit analysis.
Highlights
Avocados are one of the most commercially important widely traded fruit across the world (Rodríguez-Lopez et al, 2017)
NIR analysis of intact fruit (‘Hass’) attained RMSEP = 1.8 % (Clark et al, 2003), NIR analysis on avocados (‘Hass’) ripened after water and ABA infusion attained SEP = 1.8 % (Blakey et al, 2009), NIR model developed based on data (‘Hass’) from 3 consecutive years of harvest attained RMSEP = 1.43 % (Wedding et al, 2013), a global model combining data from three different cultivars i.e., ‘Fuerte’, ‘Hass’, and ‘Carmen’, attained root mean squared error of cross-validation (RMSEcv) = 2.94 % (Blakey, 2016), and NIR analysis performed for avocado (‘Sepherd’ and ‘Hass’) with skin and without skin attained
There are already evidences that the skin in avocados causes a detrimental effect on the performance of dry matter content (DMC) models for avocados, for example, the lower RMSEcv attained in an earlier study for NIR analysis performed on skin removed fruit compared to the high RMSEcv for NIR analysis performed on fruit with skin, suggest that the contribution of the skin to the NIR models is large (Subedi and Walsh, 2020)
Summary
Avocados are one of the most commercially important widely traded fruit across the world (Rodríguez-Lopez et al, 2017). The avocado maturity stage is a key quality indicator that helps in decision making at several stages of the avocado supply chain such as during the harvest, grading of fruits during the packaging and during the storage at ware houses to facilitate year-round fruit availability (Li et al, 2018; Subedi and Walsh, 2020). A major indicator of avocado fruit maturity is the oil content (Ozdemir and Topuz, 2004; Rodríguez-Lopez et al, 2017). Measurement of oil content requires complex wet chemistry analysis which, from a time and cost perspective, is not an optimal so lution (Clark et al, 2003). Since DMC measurement is easier (weighing – drying – weighing) and lower in cost compared to the oil content analysis, it is widely used to assess the avocado maturity during various stages of the supply chain (Wedding et al, 2013). Nowadays even different non-destructive techniques are explored to predict the DMC in real-time to support rapid decision making (Li et al, 2018; Subedi and Walsh, 2020)
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