Towards sweetness classification of orange cultivars using short-wave NIR spectroscopy

Abstract

The global orange industry constantly faces new technical challenges to meet consumer demands for quality fruits. Instead of traditional subjective fruit quality assessment methods, the interest in the horticulture industry has increased in objective, quantitative, and non-destructive assessment methods. Oranges have a thick peel which makes their non-destructive quality assessment challenging. This paper evaluates the potential of short-wave NIR spectroscopy and direct sweetness classification approach for Pakistani cultivars of orange, i.e., Red-Blood, Mosambi, and Succari. The correlation between quality indices, i.e., Brix, titratable acidity (TA), Brix: TA and BrimA (Brix minus acids), sensory assessment of the fruit, and short-wave NIR spectra, is analysed. Mix cultivar oranges are classified as sweet, mixed, and acidic based on short-wave NIR spectra. Short-wave NIR spectral data were obtained using the industry standard F-750 fruit quality meter (310–1100 nm). Reference Brix and TA measurements were taken using standard destructive testing methods. Reference taste labels i.e., sweet, mix, and acidic, were acquired through sensory evaluation of samples. For indirect fruit classification, partial least squares regression models were developed for Brix, TA, Brix: TA, and BrimA estimation with a correlation coefficient of 0.57, 0.73, 0.66, and 0.55, respectively, on independent test data. The ensemble classifier achieved 81.03% accuracy for three classes (sweet, mixed, and acidic) classification on independent test data for direct fruit classification. A good correlation between NIR spectra and sensory assessment is observed as compared to quality indices. A direct classification approach is more suitable for a machine-learning-based orange sweetness classification using NIR spectroscopy than the estimation of quality indices.

Harvesting Maturity Assessment of Newly Developed Citrus Hybrids (Citrus maxima Merr. × Citrus sinensis (L.) Osbeck) for Optimum Juice Quality

“…In addition to the above parameters, BrimA (Brix minus Acid) is a relatively new proposed maturity standard and is also accepted for commercial citrus fruit harvesting in different citrus growing areas [20,26,28]. It was calculated as BrimA = Brix − k(TA), where the value of the k constant is taken as three, as Obenland et al [24] suggested for different fruit stages in all the new hybrid genotypes.…”

“…This index has been adopted for commercial harvesting determination in citrus-growing areas of New Zealand, Australia, and California. It is known by various names, as the New Zealand Navel Orange Grade Standard, the Australian Citrus Standard (ACS), and the citrus industry index, respectively [26][27][28].…”

Detection of Internal Browning Disorder in ‘Greensis’ Pears Using a Portable Non-Destructive Instrument

“…The non-destructive techniques utilize transmittance wavelengths ranging from 380 to 700 nm within the visible light spectrum and from 780 to 2500 nm within the near-infrared (NIR) spectrum to predict the internal characteristics of fruits, such as soluble solids concentration (SSC), acidity, and firmness [18,19]. Predictive models of internal fruit damage, especially in small fruits such as pears, apples, peaches, and oranges, are established with different data processing methods using transmittance spectral curves [20,21]. Mogollon et al [22] referred to the 100-1100 nm semi-transmittance spectrum as early as 90 days after storage to predict the occurrence of internal browning in 'Cripps Pink' apples, which occurred approximately 150 days after low-temperature storage.…”