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The tomato as a raw material for processing is globally important and is pivotal in dietary and agronomic research due to its nutritional, economic, and health significance. This study explored the potential of machine learning (ML) for predicting tomato quality, utilizing data from 48 cultivars and 28 locations in Hungary over 5 seasons. It focused on °Brix, lycopene content, and colour (a/b ratio) using extreme gradient boosting (XGBoost) and artificial neural network (ANN) models. The results revealed that XGBoost consistently outperformed ANN, achieving high accuracy in predicting °Brix (R² = 0.98, RMSE = 0.07) and lycopene content (R² = 0.87, RMSE = 0.61), and excelling in colour prediction (a/b ratio) with a R² of 0.93 and RMSE of 0.03. ANN lagged behind particularly in colour prediction, showing a negative R² value of -0.35. Shapley additive explanation's (SHAP) summary plot analysis indicated that both models are effective in predicting °Brix and lycopene content in tomatoes, highlighting different aspects of the data. SHAP analysis highlighted the models' efficiency (especially in °Brix and lycopene predictions) and underscored the significant influence of cultivar choice and environmental factors like climate and soil. These findings emphasize the importance of selecting and fine-tuning the appropriate ML model for enhancing precision agriculture, underlining XGBoost's superiority in handling complex agronomic data for quality assessment.

Managing crop yields and optimizing water use is a global challenge, as fresh water supply decreases rapidly and demand remains high. Therefore, understanding how plants react to varying water levels is crucial for efficient water usage. This study evaluates how tomato plants adapt to varying water levels (100%, 50% of crop evapotranspiration, and non-irrigated control) over two growing seasons in 2020 and 2021. Root images were captured weekly during an 8-week monitoring period in 2020 and 6 weeks in 2021 using a non-destructive CI-600 in-situ root imager at depths between 10 and 70 cm. Under water stress, plants developed deeper, more extensive root systems to maximize water uptake, consistent with prior research. Root depth and architecture varied with soil depth and the severity of water stress. Year-to-year variations were also found, likely due to changes in irrigation levels and environmental conditions such as temperature. SPAD values were higher under control conditions, especially in the 2021 growing season, suggesting reduced chlorophyll degradation, while no significant differences were observed in chlorophyll fluorescence (Fv/Fm) between treatments, suggesting stable photosynthetic efficiency under varied water stress conditions. These findings contribute to our understanding of root zone optimization and drought-resilient cultivar breeding, contributing to more sustainable agricultural practices.

Tomato-based products are significant components of vegetable consumption. The processing tomato industry is unquestionably in need of a rapid definition method for measuring soluble solids content (SSC) and lycopene content. The objective was to find the best chemometric method for the estimation of SSC and lycopene content from visible and near-infrared (Vis-NIR) absorbance and reflectance data so that they could be determined without the use of chemicals in the process. A total of 326 Vis-NIR absorbance and reflectance spectra and reference measurements were available to calibrate and validate prediction models. The obtained spectra can be manipulated using different preprocessing methods and multivariate data analysis techniques to develop prediction models for these two main quality attributes of tomato fruits. Eight different method combinations were compared in homogenized and intact fruit samples. For SSC prediction, the results showed that the best root mean squared error of cross-validation (RMSECV) originated from raw absorbance (0.58) data and with multiplicative scatter correction (MSC) (0.59) of intact fruit in Vis-NIR, and first derivatives of reflectance ( R 2 = 0.41) for homogenate in the short-wave infrared (SWIR) region. The best predictive ability for lycopene content of homogenate in the SWIR range ( R 2 = 0.47; RMSECV = 17.95 mg kg -1 ) was slightly lower than that of Vis-NIR ( R 2 = 0.68; 15.07 mg kg -1 ). This study reports the suitability of two Vis-NIR spectrometers, absorbance/reflectance spectra, preprocessing methods, and partial least square (PLS) regression to predict SSC and lycopene content of intact tomato fruit and its homogenate., Competing Interests: GáP, GaP, and PS were employed by Univer Product PLC. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Égei, Takács, Palotás, Palotás, Szuvandzsiev, Daood, Helyes and Pék.)

The results showed that soil electrical conductivity, (EC2: 7 dS/m) increased soluble solids, lycopene content, total phenolic content, hydrophilic and lipophilic radical scavenging activities (HRSA and LRSA) by 14.2, 149, 20, 46.4, and 19.0%, respectively, compared with control. Under 0.5% spent engine oil (SEO), flavonoid content decreased by 21.7% compared with the control. HRSA and LRSA of fruits subjected to EC2/SEO1 treatment were, respectively, 45.9 and 35.5% lower than control. The a * /b * ratio was positively and significantly ( P < 0.01) correlated with β-carotene (R = 0.78), lycopene (R = 0.68), total vitamin C (R = 0.71), α-tocopherol (R = 0.83), γ-tocopherol (R = 0.66), HRSA (R = 0.93), LRSA (R = 0.80), and soluble solids (R = 0.84) suggesting that it may be a promising indicator of fruit quality in areas affected by such constraints. The research revealed that combined stresses induce responses markedly different from those of individual treatments, which strain the need to focus on how the interaction between stresses may affect the functional quality of tomato fruits., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ilahy, Tlili, Pék, Montefusco, Daood, Azam, Siddiqui, R'him, Durante, Lenucci and Helyes.)

The increasing popularity of pomegranate ( Punica granatum L.), driven by the awareness of its nutraceutical properties and excellent environmental adaptability, is promoting a global expansion of its production area. This investigation reports the variability in the weight, moisture, pH, total soluble solids, carbohydrates, organic acids, phenolic compounds, fatty acids, antioxidant activities, and element composition of different fruit parts (juices, peels, and kernels) from four (Ako, Emek, Kamel, and Wonderful One) of the most widely cultivated Israeli pomegranate varieties in Salento (South Italy). To the best of our knowledge, this is the first systematic characterization of different fruit parts from pomegranate cultivars grown simultaneously in the same orchard and subjected to identical agronomic and environmental conditions. Significant genotype-dependent variability was observed for many of the investigated parameters, though without any correlation among fruit parts. The levels of phenols, flavonoids, anthocyanins, and ascorbic and dehydroascorbic acids of all samples were higher than the literature-reported data, as was the antioxidant activity. This is likely due to positive interactions among genotypes, the environment, and good agricultural practices. This study also confirms that pomegranate kernels and peels are, respectively, rich sources of punicic acid and phenols together, with several other bioactive molecules. However, the variability in their levels emphasizes the need for further research to better exploit their agro-industrial potential and thereby increase juice-production chain sustainability. This study will help to assist breeders and growers to respond to consumer and industrial preferences and encourage the development of biorefinery strategies for the utilization of pomegranate by-products as nutraceuticals or value-added ingredients for custom-tailored supplemented foods.

Owing to several presumed health-promoting biological activities, increased attention is being given to natural plant chemicals, especially those frequently entering the human diet. Glucosinolates (GLs) are the main bioactive compounds found in broccoli ( Brassica oleracea L. var. italica Plenck). Their regular dietary assumption has been correlated with reduced risk of various types of neoplasms (lung, colon, pancreatic, breast, bladder, and prostate cancers), some degenerative diseases, such as Alzheimer's, and decreased incidence of cardiovascular pathologies. GL's synthesis pathway and regulation mechanism have been elucidated mainly in Arabidopsis . However, nearly 56 putative genes have been identified as involved in the B . oleracea GL pathway. It is widely recognized that there are several pre-harvest (genotype, growing environment, cultural practices, ripening stage, etc.) and post-harvest (harvesting, post-harvest treatments, packaging, storage, etc.) factors that affect GL synthesis, profiles, and levels in broccoli. Understanding how these factors act and interact in driving GL accumulation in the edible parts is essential for developing new broccoli cultivars with improved health-promoting bioactivity. In this regard, any systematic and comprehensive review outlining the effects of pre- and post-harvest factors on the accumulation of GLs in broccoli is not yet available. Thus, the goal of this paper is to fill this gap by giving a synoptic overview of the most relevant and recent literature. The existence of substantial cultivar-to-cultivar variation in GL content in response to pre-harvest factors and post-harvest manipulations has been highlighted and discussed. The paper also stresses the need for adapting particular pre- and post-harvest procedures for each particular genotype in order to maintain nutritious, fresh-like quality throughout the broccoli value chain., (Copyright © 2020 Ilahy, Tlili, Pék, Montefusco, Siddiqui, Homa, Hdider, R'Him, Lajos and Lenucci.)

This study was conducted to analyze carotenoids from tomatoes by high-performance liquid chromatography using reversed-phase C18 silica having cross-linked end-capping with diode array and mass spectrometric detection. An efficient gradient elution system was developed to achieve good and reliable separation of both major and minor carotenoids as well as their isomers. Resolution of lycopene, β-carotene and their isomers was 0.91-3.97 and 1.02-2.86 with cross-linked and conventional C18 column, respectively. The % recovery for zeaxanthin, lycopene and β-carotene was found to be in the range of 89-97%. Limits of detection and quantification of 19.44 and 64.79 ng/mL for zeaxanthin, 15.6 and 52.4 ng/mL for lycopene and 8.28 and 27.61 ng/mL for β-carotene were determined. More carotenoid compounds could be separated and detected with the new method as compared with conventional C18 column. Hyphenation of HPLC with photodiode array and mass spectrometry detectors assisted in detection of tetra-dehydrocarotenoid and fatty acid diesters of xanthophylls in tomato products. Content of all-trans-lycopene, β-carotene and total carotenoid in different industrial tomatoes tested was found to range between 41.87 and 84.65, 0.89 and 1.50 and 53.22 and 112.60 µg/g fresh weight, respectively., (© The Author [2013]. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)