Abstract
Bruise damage is a very commonly occurring defect in apple fruit which facilitates disease occurrence and spread, leads to fruit deterioration and can greatly contribute to postharvest loss. The detection of bruises at their earliest stage of development can be advantageous for screening purposes. An experiment to induce soft bruises in Golden Delicious apples was conducted by applying impact energy at different levels, which allowed to investigate the detectability of bruises at their latent stage. The existence of bruises that were rather invisible to the naked eye and to a digital camera was proven by reconstruction of hyperspectral images of bruised apples, based on effective wavelengths and data dimensionality reduced hyperspectrograms. Machine learning classifiers, namely ensemble subspace discriminant (ESD), k-nearest neighbors (KNN), support vector machine (SVM) and linear discriminant analysis (LDA) were used to build models for detecting bruises at their latent stage, to study the influence of time after bruise occurrence on detection performance and to model quantitative aspects of bruises (severity), spanning from latent to visible bruises. Over all classifiers, detection models had a higher performance than quantitative ones. Given its highest speed in prediction and high classification performance, SVM was rated most recommendable for detection tasks. However, ESD models had the highest classification accuracy in quantitative (>85%) models and were found to be relatively better suited for such a multiple category classification problem than the rest.
Highlights
Bruise damage in fruit is very common and known to be one of the most contributing factors to degradation and loss of quality in fruit [1,2]
The results suggest that support vector machine (SVM) is recommendable for latent bruise detection tasks while for quantitative models, ensemble subspace discriminant (ESD) and linear discriminant analysis (LDA) would be a better fit to achieve high accuracy
Bruise damages were established on Golden Delicious apples, which have a bright green epidermis allowing for clear visibility of external defects, such as bruises
Summary
Bruise damage in fruit is very common and known to be one of the most contributing factors to degradation and loss of quality in fruit [1,2]. A wide range of preharvest and postharvest factors contributing to fruit bruising susceptibility and incidence have been reported [3,4,5]; bruise damage continues to occur due to inherent susceptibility of produce and inadequate application of control measures. The presence of bruising leads to reduced market acceptability of fresh produce and postharvest loss along horticultural value chain due to downgrading or outright rejection, thereby contributing to wastage and associated negative socio-economic and environmental impacts [6,7]. Bruised fruit undergo accelerated ripening and senescence, which necessitate the need for further detection and control measures [12]
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