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Nectarines, a popular pit fruit closely related to peaches, are renowned for their nutritional value and associated health benefits. However, challenges arise in maintaining optimal organoleptic properties during harvest and handling, eventually leading to production waste and heterogeneous quality in the fruit that arrives to the consumer. This study investigates the impact of nectarine position on trees during the whole ripening process using non‐destructive near‐infrared (NIR) spectroscopy. Nectarines exposed to more sunlight mature faster and this influences sugar content and acidity, emphasising the significance of considering height, prominence and orientation in ripening dynamics of the fruit. Different data unfolding strategies were compared, using ANOVA‐Simultaneous Component Analysis (ASCA) to reveal the significance of in‐tree position factors at different ripening stages, and observing high significance at harvest. This underscores the necessity for growers and handlers to consider these factors for reducing waste. NIR spectroscopy, with adequate data analysis, is a valuable tool for the holistic analysis of fruit ripening, providing crucial insights for maintaining optimal fruit organoleptic properties from harvest to consumer. This study explores how the position of nectarines on trees affects ripening, using near‐infrared (NIR) spectroscopy. Nectarines exposed to more sunlight mature faster, impacting sugar content and acidity. ANOVA‐Simultaneous Component Analysis (ASCA) revealed significant in‐tree position effects at harvest, highlighting the importance of height, prominence, and orientation on different stages of the ripening. The findings stress the need for growers to consider these factors to reduce waste, with NIR spectroscopy proving useful for ensuring optimal fruit quality. [ABSTRACT FROM AUTHOR]

Spatially offset Raman spectroscopy (SORS) is a non-invasive analytical technique that allows the analysis of samples through a container. This makes it an effective tool for studying food and beverage products, as it can measure the sample without being affected by the packaging or the container. In this study, a portable SORS equipment was used for the first time to analyse the alcoholic fermentation process of white wine. Different sample measurement arrangements were tested in order to determine the most effective method for monitoring the fermentation process and predicting key oenological parameters. The best results were obtained when the sample was directly measured through the glass container in which the fermentation was occurring. This allowed for the accurate monitoring of the process and the prediction of density and pH with a root mean square error of cross-validation (RMSECV) of 0.0029 g·L−1 and 0.04, respectively, and R2 values of 0.993 and 0.961 for density and pH, respectively. Additionally, the sources of variability depending on the measurement arrangements were studied using ANOVA-Simultaneous Component Analysis (ASCA). [ABSTRACT FROM AUTHOR]