Reducing chilling injury in 'Palmer' mangoes submitted to quarantine cold treatment.

BACKGROUND: Treatment with low temperatures can be used to quarantine mangoes against fruit-fly infestation. However, mangoes can develop chilling injury (CI) when stored at temperatures below 13 °C. We demonstrated that the immersion in polyol solutions can alleviate CI symptoms in 'Palmer' mangoes stored at 8 °C. These suggest that polyols can be used to reduce CI in mangoes during quarantine at low temperatures. Thus, we investigated the efficacy of applying 0.1% (v/v) glycerol, propylene glycol, or sorbitol to 'Palmer' mangoes subjected to cold treatment (1.0 °C) for 28 days. Mangoes were then ripened at 23 °C for 7 days. RESULTS: Among these polyols, sorbitol was the most effective in alleviating CI for up to 14 days of cold treatment. Mangoes treated with sorbitol showed lower levels of malondialdehyde (MDA) and hydrogen peroxide (H2 O2 ), and reduced polyphenol oxidase (PPO) activity. These fruit also had elevated levels of ascorbate (AsA), especially in the epicarp, and increased superoxide dismutase (SOD), catalase (CAT), and ascorbate peroxidase (APX) activity. CONCLUSION: Sorbitol can reduce the CI, but to an unsatisfying level, and it should be combined with other treatments storage at low temperature. © 2022 Society of Chemical Industry.

Prediction of meat quality traits in Nelore cattle by near-infrared reflectance spectroscopy.

The main definition for meat quality should include factors that affect consumer appreciation of the product. Physical laboratory analyses are necessary to identify factors that affect meat quality and specific equipment is used for this purpose, which is expensive and destructive, and the analyses are usually time consuming. An alternative method to performing several beef analyses is near-infrared reflectance spectroscopy (NIRS), which permits to reduce costs and to obtain faster, simpler, and nondestructive measurements. The objective of this study was to evaluate the feasibility of NIRS to predict shear force [Warner-Bratzler shear force (WBSF)], marbling, and color (*a = redness; b* = yellowness; and L* = lightness) in meat samples of uncastrated male Nelore cattle, that were approximately 2-yr-old. Samples of longissimus thoracis (n = 644) were collected and spectra were obtained prior to meat quality analysis. Multivariate calibration was performed by partial least squares regression. Several preprocessing techniques were evaluated alone and in combination: raw data, reduction of spectral range, multiplicative scatter correction, and 1st derivative. Accuracies of the calibration models were evaluated using the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), coefficient of determination in the calibration (R2C), and prediction (R2P) groups. Among the different preprocessing techniques, the reduction of spectral range provided the best prediction accuracy for all traits. The NIRS showed a better performance to predict WBSF (RMSEP = 1.42 kg, R2P = 0.40) and b* color (RMSEP = 1.21, R2P = 0.44), while its ability to accurately predict L* (RMSEP = 1.98, R2P = 0.16) and a* (RMSEP = 1.42, R2P = 0.17) was limited. NIRS was unsuitable to predict subjective meat quality traits such as marbling in Nelore cattle.

Predicting soluble solid content in intact jaboticaba [Myrciaria jaboticaba (Vell.) O. Berg] fruit using near-infrared spectroscopy and chemometrics.

The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIR) as a rapid and non-destructive method to determine soluble solid content (SSC) in intact jaboticaba [Myrciaria jaboticaba (Vell.) O. Berg] fruit. Multivariate calibration techniques were compared with pre-processed data and variable selection algorithms, such as partial least squares (PLS), interval partial least squares (iPLS), a genetic algorithm (GA), a successive projections algorithm (SPA) and nonlinear techniques (BP-ANN, back propagation of artificial neural networks; LS-SVM, least squares support vector machine) were applied to building the calibration models. The PLS model produced prediction accuracy (R(2)=0.71, RMSEP=1.33 °Brix, and RPD=1.65) while the BP-ANN model (R(2)=0.68, RMSEM=1.20 °Brix, and RPD=1.83) and LS-SVM models achieved lower performance metrics (R(2)=0.44, RMSEP=1.89 °Brix, and RPD=1.16). This study was the first attempt to use NIR spectroscopy as a non-destructive method to determine SSC jaboticaba fruit.

Postharvest changes and respiratory pattern of bacuri fruit (Platonia insignis Mart) at different maturity stages during ambient storage

O bacuri (Platonia insignis, Mart.) é um dos mais importantes entre os frutos da Amazônia. Todavia, pouco se sabe sobre sua fisiologia pós-colheita, bem como, estádio de maturação, mudanças durante o armazenamento sob condições ambientais e padrão respiratório. Os frutos foram colhidos em três estádios de maturação baseados na coloração do epicarpo: verde-escuro, verde-claro e "de vez" (50% amarelo), com o objetivo de se determinar as modificações de coloração e padrão respiratório durante armazenamento sob condições de ambiente (25,2 ºC, 75,1 % UR). Os frutos de todos os estádios de maturação apresentaram, a partir do terceiro dia de colheita, comportamento respiratório não climatérico, com os frutos "de vez" apresentando maior taxa de produção de CO2 até o quarto dia de armazenamento (177,63 mg CO2.kg-1.h-1). O amarelecimento aumentou durante o armazenamento e foi relacionado com a diminuição da luminosidade (L), cromaticidade e ângulo hue. Os frutos "de vez" podem ser armazenados sob condições de ambiente por até 10 dias sem nenhuma perda da qualidade comercial.