Daniels Andries J, Poblete-Echeverría Carlos, Nieuwoudt Hélène H, Botha Nicolene, Opara Umezuruike Linus
Department of Viticulture and Oenology, Faculty of AgriSciences, Stellenbosch University, Stellenbosch, South Africa.
ARC Infruitec-Nietvoorbij, Stellenbosch, South Africa.
Front Plant Sci. 2021 Oct 29;12:768046. doi: 10.3389/fpls.2021.768046. eCollection 2021.
Table grape browning is a complex physiological disorder that occurs during cold storage. There is a need to investigate novel and innovative ways to manage the problem that hampers the progressive and sustainable growth of table grape industries. Given the complex nature of the browning phenomenon, techniques such as near-infrared (NIR) spectroscopy can be utilized for the non-destructive classification of different browning phenotypes. In this study, NIR coupled with partial least squares discriminant analysis (PLS-DA) and artificial neural networks (ANN) were used to classify bunches as either clear or as having chocolate browning and friction browning based on the spectra obtained from intact 'Regal Seedless' table grape bunches that were cold-stored over different periods. Friction browning appears as circular spots close to the pedicel area that are formed when table grape berries move against each other, and chocolate browning appears as discoloration, which originates mostly from the stylar-end of the berry, although the whole berry may appear brown in severe instances. The evaluation of the models constructed using PLS-DA was done using the classification error rate (CER), specificity, and sensitivity and for the models constructed using ANN, the kappa score was used. The CER for chocolate browning (25%) was better than that of friction browning (46%) for weeks 3 and 4 for both class 0 (absence of browning) and class 1 (presence of browning). Both the specificity and sensitivity of class 0 and class 1 for friction browning were not as good as that of chocolate browning. With ANN, the kappa score was tested to classify table grape bunches as clear or having chocolate browning or friction browning and showed that chocolate browning could be classified with a strong agreement during weeks 3 and 4 and weeks 5 and 6 and that friction browning could be classified with a moderate agreement during weeks 3 and 4. These results open up new possibilities for the development of quality checks of packed table grape bunches before export. This has a significant impact on the table grape industry for it will now be possible to evaluate bunches non-destructively during packaging to determine the possibility of these browning types being present when reaching the export market.
鲜食葡萄褐变是一种在冷藏过程中出现的复杂生理病害。有必要研究新颖且创新的方法来解决这一阻碍鲜食葡萄产业持续健康发展的问题。鉴于褐变现象的复杂性,诸如近红外(NIR)光谱技术可用于对不同褐变表型进行无损分类。在本研究中,利用近红外光谱结合偏最小二乘判别分析(PLS - DA)和人工神经网络(ANN),根据不同冷藏期完整的‘皇家无核’鲜食葡萄果串所获得的光谱,将果串分类为无褐变、巧克力色褐变或摩擦性褐变。摩擦性褐变表现为靠近果梗区域的圆形斑点,是鲜食葡萄果实相互摩擦时形成的;巧克力色褐变表现为变色,主要起源于果实的花柱端,不过在严重情况下整个果实可能呈现褐色。使用PLS - DA构建的模型通过分类错误率(CER)、特异性和敏感性进行评估,而对于使用ANN构建的模型,则使用kappa分数进行评估。对于0类(无褐变)和1类(有褐变),在第3周和第4周,巧克力色褐变的CER(25%)优于摩擦性褐变的CER(46%)。摩擦性褐变的0类和1类的特异性和敏感性都不如巧克力色褐变。对于ANN,通过kappa分数对鲜食葡萄果串进行分类,判断其为无褐变、有巧克力色褐变或有摩擦性褐变,结果表明在第3周和第4周以及第5周和第6周,巧克力色褐变能够以高度一致性进行分类,在第3周和第4周,摩擦性褐变能够以中等一致性进行分类。这些结果为出口前包装鲜食葡萄果串的质量检测开发开辟了新的可能性。这对鲜食葡萄产业具有重大影响,因为现在有可能在包装过程中对果串进行无损评估,以确定到达出口市场时出现这些褐变类型的可能性。