Macadamia nut industry is increasingly gaining more space in the food market and the success of the industry and the quality are largely due to the selection of cultivars through macadamia nut breeding programs. Thus, the objective of this study was to investigate the feasibility NIRS coupled to chemometric classification methods, to build a rapid and non-invasive analytical procedure to classify different macadamia cultivars based on intact nuts. Intact nuts of five different macadamia cultivars (HAES 246, IAC 4-20, IAC 2-23, IAC 5-10, and IAC 8-17) were harvested in 2017. Two NIR reflectance spectra were collected per nut, and the mean spectra were used to chemometrics analysis. Principal component analysis-linear discriminant analysis (PCA-LDA) and genetic algorithm-linear discriminant analysis (GA-LDA) were used to develop the classifications models. The GA-LDA approach resulted in accuracy higher than 94.44%, with spectra preprocessed with Savitzky-Golay smoothing. Thus, this approach can be implemented in the macadamia industry, allowing the selection of cultivars based on intact nuts. However, it is recommended that more experimentation to include more data variability in order to increase the classification accuracy to 100%.
The objective of this study was to use dry matter (DM) calibration models to sort ‘Palmer’ mangoes prior cold storage and to evaluate the physiological and chemical changes during the storage period. PLS model developed with fruit from 2015/2016 season was not adequate to predict DM content in fruit from 2016/2017 (not adjusted R2). Therefore, VIS‐NIR spectra from 2016/2017 season were incorporated into data set and a new model was developed (RMSEcv of 10.5 g.kg−1,
RnormalP2 of 0.75). With the new model, ‘Palmer’ mangoes were sorted into two maturity stages (150 g.kg−1 and 110 g.kg−1) which resulted in quality differences mainly in relation to DM and SSC. Portable VIS‐NIR spectrometer can be used to sort fruit according to maturity stages based on DM content and this classification affect fruit quality during cold storage as fruit with higher DM (150 g.kg−1) presented better quality than fruit with lower DM (110 g.kg−1).
Practical applications
Although results can be found regarding the use of portable NIR spectrometers to estimate maturity in mango fruit, there are no studies stating the use of this method to sort fruit prior cold storage. Our results highlight that portable VIS‐NIR spectrometer can be used to sort fruit according to maturity stages based on dry matter (DM) content and this classification affects fruit quality during cold storage as fruit with higher DM (150 g.kg−1) presented better quality than fruit with lower DM (110 g.kg−1) at the end of the storage period.
SummaryDue to the importance of banana consumption in developing countries and producing zinc‐rich foods, the objective of this study was to evaluate the feasibility of banana bunch sprays and bunch stalk feeding with Zn aiming to biofortify this fruit. Zn sprays were carried out with a dose of 80 g ha−1 using ZnCl2 and ZnCl2 combined with a chelating agent in two banana cultivars (‘Maravilha’ and ‘FHIA 18’). Bunch stalk feeding with Zn was carried out by fixing plastic bags on the stem end containing solutions of ZnSO4 (0, 0.5, 1.0 and 2.0 g L−1) in two banana cultivars (‘Williams’ and ‘Prata Anã’). Both strategies resulted in a maximum fruit Zn content of 0.14 mg 100 g−1. Although it was possible to increase the Zn content in banana fruit from ‘FHIA 18’ and ‘Prata Anã’ cultivars, both strategies did not result in biofortified banana fruit with a Zn level which would fulfil the Zn dietary reference intake (DRI) of 2 mg dia−1 for children. Banana bunch sprays with Zn did not affect the fruit quality, but bunch stalk feeding with Zn resulted in fruits with lower ratio, pH and ascorbic acid content.
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