Search

This study focused on optimizing a cold water extraction method to obtain bioactive compounds from chamomile (Matricaria chamomilla L.), addressing increasing consumer demand for natural products and nutraceuticals. A full-factorial design was employed to evaluate the effects of temperature, time, and chamomile amount on the polyphenolic profile of extracts. The samples were characterized by HPLC-DAD and UV-Vis coupled with chemometrics; the analysis showed that extraction time negatively affected extract quality, as did the interaction between time and temperature. In addition, a significant positive quadratic effect for temperature and a positive coefficient for chamomile amount was found. ASCA was used to assess the UV-Vis profile, offering an alternative untargeted method for understanding the variable effects. The optimal extraction conditions (25 °C, 32 min, and 2.5 g of chamomile) produced samples high in hydroxybenzoic and hydroxycinnamic acids and flavanol derivatives. Using A face-centered design, this study also monitored antioxidant activity via a DPPH scavenging assay, confirming that the optimal conditions yielded samples within the range of maximum antioxidant activity in the studied experimental domain. [ABSTRACT FROM AUTHOR]

Studying the evolution of seed morphology and, in turn, the evolution of cultivars across time and space is of fundamental importance to agriculture and archaeology. The identification of ancient and modern grapevine (Vitis vinifera L.) cultivars is essential for understanding the historical evolution of grape cultivation. Grape seed morphology provides valuable information to explore the evolution of grape cultivars over time and space. The main aim of our study was to build a comprehensive regional database of grape seed morphological traits from modern and archaeological wine cultivars and wild grape species. We aimed to identify which seeds of modern grape cultivars exhibited morphological similarities to archaeological cultivars. This study focused on fifteen distinct modern types of seeds and two archaeological samples from the Byzantine-to-Early Medieval period. We acquired digital images of seeds using a flatbed scanner. For each sample, 100 seeds were randomly selected, and morphometric data on each seed were gathered using ImageJ. Differences among the seed cultivars were investigated using linear discriminant analysis. Archaeological seeds were found to be more similar to cultivated V. vinifera cultivars rather than V. sylvestris populations. Among the cultivated cultivars, Sangiovese and Tosta antica resulted to be cultivars most similar cultivars to the archaeological ones. The morphometric analysis of grape seeds proved to be a valuable resource for investigating the evolution of vine cultivars throughout history. Combining image analysis techniques with genetic data will open new perspectives for studying the origins of and variations in grape cultivars, contributing to the conservation and enhancement of viticultural heritage. [ABSTRACT FROM AUTHOR]

Celery (Apium graveolens L.) is a well- known plant and at the basis of the culinary tradition of different populations. In Italy, several celery ecotypes, presenting unique peculiarities, are grown by small local producers, and they need to be characterized, in order to be protected and safeguarded. The present work aims at developing a fast and non-destructive method for the discrimination of a common celery (the "Elne" celery) from a typical celery of Abruzzo (Central Italy). The proposed strategy is based on the use of an e-eye tool which allows the collection of images used to infer colorgrams. Initially, a principal component analysis model was used to investigate the trends and outliers in the data. Then, the classification between the common celery (Elne class) and celery from Torricella Peligna (Torricella class) was achieved by a discriminant analysis, conducted by sequential preprocessing through orthogonalization (SPORT) and sequential and orthogonalized covariance selection (SO-CovSel) and by a class-modelling method called soft independent modelling of class analogies (SIMCAs). Among these, the highest accuracy was provided by the strategies, based on the discriminant classifiers, both of which provided a total accuracy of 82% in the external validation. [ABSTRACT FROM AUTHOR]