Fruit Soluble Solids Content Research Articles

Effect of lemongrass and chili pepper oils on the quality of ripe tomato fruits stored under tropical ambient temperature

Postharvest quality of tomato (Solanum lycopersicum L.) fruits treated with lemongrass (Cymbopogon citratus L.) and chili pepper (Capsicum annuum L.) oil was evaluated. Tomato variety Roma fruits of uniform size and weight at the red stage of ripening were overlaid with lemongrass oil only (L1P0), chili pepper oil only (L0P1), or mixtures in a ratio 1:1 (L1P1), and 1:2 (L1P2 and L2P1). Control (L0P0) was not treated with any oil. Treated and untreated fruits were stored at 280±20C and 46%±2 RH for 12 days. Treatments L1P0 and L2P1 oil inhibited postharvest tomato fruit rot for 12 days, whereas L1P2, L0P1, and L1P1 oil and the control showed rot within the range of 86.6% - 100% in 12 days. L1P0 and L2P1 also slowed fruit softening and significantly reduced weight loss, though L1P0 was the most protective. Total soluble solid content of fruit was not affected by both L1P0 and L2P1 throughout storage, but the parameter reduced significantly (p<0.05) in fruits treated with L1P1, L1P2, L0P1 and in control. Reduction in titratable acidity during storage was least in fruits treated with L1P0 followed by L2P1, compared to that in other treatments and the control. This study showed that lemongrass oil applied as surface coating preserved tomato fruit quality in tropical ambient storage conditions for 12 days.

Determination of the Effects of Aminoethoxyvinilglycine (AVG) and Gibberellic Acid (GA3) Applications on Pre-Harvest Fruit Drop Amount and Fruit Quality in Hakko Pear Cultivar

This study was conducted to determine the effects of pre-harvest Aminoethoxyvinylgylcine (AVG) and Gibberellic acid (GA3) applications on the pre-harvest fruit drop amount and fruit quality in the 'Hakko' pear (Pyrus pyrifolia) cultivar grafted on BA29 rootstock in a private orchard in the Bala district of Ankara in 2021-2022. It was conducted in an orchard belonging to a producer. 50-100-150 mg/l AVG and 25-50-75 mg/l GA3 were applied 4 weeks before the estimated harvest date. Fruits are harvested at full maturity date; Pomological properties such as cumulative drop percentage, yield, fruit weight, fruit width and length, fruit stem width and length, fruit flesh firmness, fruit color, and chemical properties such as soluble solids content (SSC), pH and titratable acidity (TA) were evaluated. It was observed that all doses of AVG and GA3 during the harvest period reduced the cumulative casting rate compared to the control application (6.78%). In general, the yield per tree was found to be high in GA3 applications. In both AVG and GA3 applications, its effects on fruit weight, fruit width and length, fruit flesh firmness, SSC and pH were found to be statistically significant. It was observed that in both AVG and GA3 applications, the amount of fruit drop pre-harvest decreased and fruit quality characteristics were better than the control.

Sustained-release composite films incorporated with cinnamon essential oil: Characterization, release kinetics and application for cherry tomato preservation

Food spoilage waste accelerated the development of bio-based active food packaging. Sustained-release composite films based on oxidized corn starch/ pullulan were prepared by incorporating cinnamon essential oil (CEO) nanoemulsion. The SEM, ATR-FTIR and XRD results showed that CEO was successfully encapsulated in film matrixes. The composite films exhibited the increase of thermal stability, UV-shielding, flexibility and water vapor resistance properties. The films containing CEO nanoemulsion (≥10%) showed excellent antimicrobial activities against S. aureus, E. coli and B. cinerea (the maximum inhibition zones achieving 27.23 ± 2.31 mm). The release kinetics results showed sustained release of CEO from the films with high content of CEO nanoemulsion, and the dominant release mechanism was Fickian diffusion. The composite films effectively maintained cell structure, weight, firmness and total soluble solids content of fruits during storage. Therefore, the sustained-release composite films could be a prospective packaging material for fruits preservation.

Development of a unified framework of low-rank approximation and deep neural networks for predicting the spatial variability of SSC in `Spania' watermelons using vis/NIR hyperspectral imaging

Soluble Solids Content (SSC) is an important quality attribute that represents the internal quality of fruits. Visible and near-infrared (Vis/NIR) combined with chemometric algorithms are now popular methods for non-invasive measurement and visualization of SSC. However, in fruits with a thick rind and a large flesh volume, such as watermelon, SSC is not evenly distributed across the fruit. The variability in SSC across the fruit flesh may have an adverse effect on the accuracy of quality analysis algorithms. Thus, this paper presents an accurate and efficient approach for predicting the spatial variation of SSC in watermelons using a combined framework of low-rank approximation and deep neural networks. Watermelon ‘Spania’ was selected for this study, and hyperspectral images of each watermelon were taken from various views, including the top, bottom, and two lateral views. The low-rank property is employed as a constraint in this approach to eliminate the unwanted variations in the spectral data. The low-rank component of the spectral data, free of unwanted variations, is then fed into a fully connected neural network (FNN) for the prediction of watermelon SSC values. The proposed approach obtained optimal performance in calibration and prediction with RC2=0.982, RMSEP = 0.132, and RP2=0.945, RMSEP = 0.195 respectively. Further, the prediction outcomes of the proposed method were compared with state-of-the-art such as Partial Least Square Regression (PLSR), Support Vector Regression (SVR), Multiple Linear Regression (MLR), Decision Tree (DT), and Random Forest (RF). The overall results showed that combining HSI data with a low-rank and deep neural network framework is an efficient method for accurately predicting SSC in watermelons as well as correctly predicting spatial variability of SSC in individual fruits.

Enhancing fruit SSC detection accuracy via a light attenuation theory-based correction method to mitigate measurement orientation variability

Nondestructive online detection and sorting for fruit quality has gradually attracted attention in the global agro-product industry. However, the detection accuracy is influenced by many factors, such as fruit orientation, fruit shape, and environmental fluctuations. This study aimed to explore the impact of measurement orientation variation on spectra and soluble solids content (SSC) detection in apples and propose a correction method to mitigate the effect. Firstly, the visible/near-infrared (Vis/NIR) spectra ranging from 550 to 950 nm were collected in four orientations. Then, calibration models were developed for each orientation separately (local models) and all orientations corporately (global models) to evaluate and compensate for the effect of orientation. After that, the novel method based on the light attenuation theory was introduced to correct the acquired raw spectra and establish corrected orientation models. Results showed that measurement orientation significantly altered spectral intensity due to variations in surface curvature and optical path, thus declining models’ predictive power and robustness. Global models proved to be less susceptible to orientation variation compared with local models. The performance of both local and global models considerably improved post-orientation correction, attributed to the decrease of spectral distribution difference, with their average Rp2 and RPD increased by 93.38 % and 8.11 %, 10.56 % and 10.57 %, respectively, while the average RMSEP decreased by 16.01 % and 10.78 %, respectively. Overall, this work provides a more cost-effective and universal approach to impair the influence of measurement orientation and improve the accuracy and reliability of fruit quality online detection.

Behavior of ponkan mandarin tree canopy grafted onto rangpur lime and flying dragon rootstocks

The Rangpur lime rootstock was the basis of Brazilian citrus growing for many years. However, this rootstock has been gradually replaced due to the occurrence of Citrus Sudden Death. The Flying Dragon rootstock has stood out as one of the options for replacement as it has different characteristics, such as reducing the size of the plant. There is no information in the literature about the behavior of Flying Dragon as a rootstock for Ponkan mandarin. Therefore, the objective of this study was to evaluate the behavior of Ponkan mandarin tree canopy grafted onto Rangpur lime and Flying Dragon rootstocks concerning physiological, agronomic, and fruit quality parameters. In the experiment, productivity, soil moisture, water potential, plant height, fruit diameter, fruit length, fruit mass, fruit pH, soluble solids content, titratable acidity, and ratio were evaluated. The Flying Dragon rootstock was responsible for the decrease in average productivity in the Ponkan mandarin culture. Greater plant heights were obtained when canopies were grafted on Rangpur lime. The soluble solids content of fruits from scions grafted on Flying Dragon was higher, but the degree of uniformity of the soluble solids values obtained from the Rangpur lime tree was higher.

Modulation of cherry tomato performances in response to molybdenum biofortification and arbuscular mycorrhizal fungi in a soilless system

Molybdenum (Mo) is a crucial microelement for both, humans and plants. The use of agronomic biofortification techniques can be an alternative method to enhance Mo content in vegetables. Concomitantly, arbuscular mycorrhizal fungi (AMF) application is a valuable strategy to enhance plant performances and overcome plant abiotic distresses such as microelement overdose. The aim of this research was to estimate the direct and/or indirect effects of Mo supply at four doses [0.0, 0.5 (standard dose), 2.0 or 4.0 μmol L−1], alone or combined with AMF inoculation, on plant performances. In particular, plant height and first flower truss emission, productive features (total yield, marketable yield and average marketable fruit weight) and fruit qualitative characteristics (fruit dry matter, soluble solids content, titratable acidity, ascorbic acid, lycopene, polyphenol, nitrogen, copper, iron and molybdenum) of an established cherry tomato genotype cultivated in soilless conditions were investigated. Moreover, proline and malondialdehyde concentrations, as well as Mo hazard quotient (HQ) in response to experimental treatments were determined. A split-plot randomized experimental block design with Mo dosages as plots and +AMF or -AMF as sub-plots was adopted. Data revealed that AMF inoculation enhanced marketable yield (+50.0 %), as well as some qualitative traits, such as fruit soluble solids content (SSC) (+9.9 %), ascorbic acid (+7.3 %), polyphenols (+2.3 %), and lycopene (+2.5 %). Molybdenum application significantly increased SSC, polyphenols, fruit Mo concentration (+29.0 % and +100.0 % in plants biofortified with 2.0 and 4.0 μmol Mo L−1 compared to those fertigated with the standard dose, respectively) and proline, whereas it decreased N (−25.0 % and −41.6 % in plants biofortified with 2.0 and 4.0 μmol Mo L−1 compared to those fertigated with the standard dose, respectively). Interestingly, the application of AMF mitigated the detrimental effect of high Mo dosages (2.0 or 4.0 μmol L−1). A pronounced advance in terms of plant height 45 DAT, fruit lycopene concentration and fruit Fe, Cu and Mo concentrations was observed when AMF treatment and Mo dosages (2.0 or 4.0 μmol Mo L−1) were combined. Plants inoculated or not with AMF showed an improvement in the hazard quotient (HQ) in reaction to Mo application. However, the HQ - for a consumption of 200 g day−1 of biofortified cherry tomato - remained within the safety level for human consumption. This study suggests that Mo-implementation (at 2.0 or 4.0 μmol L−1) combined with AMF inoculation could represent a viable cultivation protocol to enhance yield, produce premium quality tomato fruits and, concomitantly, improve Mo dose in human diet. In the light of our findings, further studies on the interaction between AMF and microelements in other vegetable crops are recommended.

Evaluation of the Pollination Efficiency of Apple Trees by Osmia excavata Alfken (Hymenoptera: Megachilidae).

The mason bee Osmia excavata Alfken is an apple pollinating insect widely distributed in northern China, in order to effectively utilize the mason bee and improve the pollination rate of apples, there is a need to evaluate the pollination efficiency of the bees. This study evaluated the pollination efficiency of the mason bee on apple orchards in Jinan and Yantai, Shandong Province, China. The study compared natural pollination areas and pollination areas with different release densities of O. excavata in terms of the effects of bee density, timing of pollination, and distance effects on fruit set rate, fruit shape index, fruit shape skewness, fruit soluble solids content, and fruit firmness. The optimal release density of bees was 6000 cocoons per hectare, resulting in the highest fruit setting rate of apple lateral flowers. From 07:00 to 14:00 was the best time for bee pollination. The optimal distance of hives from apple trees for pollination by O. excavata was 60m. Single fruit weight was significantly higher and fruit unsymmetrical rate, partial slope and hardness were all significantly lower at the release densities of 6000 or 12000 cocoons per hectare compared with 3000 cocoons per hectare or under natural pollination conditions. There was no significant difference in the content of soluble solids under different release densities. Thus, the radius of 60m from the hive was the effective pollination range and 6000 cocoons per hectare of mason bees could ensure the fruit quality of apple.

Visible/near-infrared Spectroscopy and Hyperspectral Imaging Facilitate the Rapid Determination of Soluble Solids Content in Fruits

Visible/near-infrared Spectroscopy and Hyperspectral Imaging Facilitate the Rapid Determination of Soluble Solids Content in Fruits

Improving SSC detection accuracy of cherry tomatoes by feature synergy and complementary spectral bands combination

The visible/near-infrared (VIS/NIR) spectroscopy technique has been extensively employed for the non-destructive detection of soluble solids content (SSC) in fruit. However, some existing algorithms and modeling optimization methods for improving the detection accuracy of SSC may be applicable to specific conditions and not universal. To break through this bottleneck problem, we propose a potentially universal strategy based on feature synergy and spectral bands combination of multiple detection modes. Firstly, compared with the commonly used halogen lamp, the xenon lamp was utilized to cover the ultraviolet (UV) range and match the characteristic information of different sugars (glucose, fructose, and sucrose). Furthermore, the spectral fusion method was employed to combine the reflectance and transmittance spectra to improve the cherry tomatoes SSC prediction accuracy with comprehensive data in the UV/VIS/NIR region. Finally, the best results were achieved by the partial least square regression (PLSR) model with spectral bands fusion, yielding the results of R2p, RMSEP, and RPD as 0.9653, 0.1998%, and 5.31, respectively. The same conclusion can also be verified when predicting the SSC in strawberries. Overall, this strategy is potentially universal to improve the prediction accuracy of SSC in fruit by matching light source spectra with characteristic absorption, as well as utilizing comprehensive spectral information in the 200–1100 nm range, providing valuable insights for the practical application of nondestructive detection of fruit internal quality.

Predicting Soluble Solids Concentration of ‘Geneva 3’ Kiwiberries Using Near Infrared Spectroscopy

Near infrared (NIR) spectroscopy can be applied to nondestructively assess soluble solids concentration (SSC) of ripening, physiologically mature ‘Geneva 3’ kiwiberries (Actinidia arguta). Spectrographic signatures were captured using a handheld NIR produce quality meter to build predictive models of internal fruit quality for ‘Geneva 3’ kiwiberries that had been held under cold storage (CS) conditions (0 to 1 °C, >90% relative humidity) as well as those not subjected to CS. The CS model, constructed using scans of 133 berries following 4 to 6 weeks in CS, predicts SSC using NIR wavelengths in the range of 729 to 975 nm. A total of 507 berries fresh from the vine were used to construct a predictive model for SSC of non-CS fruit using the same wavelength range. In each case, model predictive performance was investigated using split-half cross-validation, resulting in mean absolute error (MAE) values of 1.2% and 0.8% SSC for the CS and non-CS model, respectively. Each full model was then used to predict SSC of kiwiberries subjected to the alternative CS condition. The non-CS model maintained a low MAE (1.6% SSC) when applied to CS fruit, but the MAE of the CS model applied to non-CS fruit rose considerably (4.5% SSC). The performance of a combined model was tested against both CS and non-CS models, and a benefit to using tailored, CS-specific models was found, particularly in light of cross-seasonal results. As it has proven in many crops, NIR spectroscopy appears to be a promising tool for nondestructively assessing SSC in ‘Geneva 3’ kiwiberry fruit, with accuracy being enhanced by training models specific to postharvest regimes and/or defined ranges of SSC.

Research on Quality Detection of Jujube (Ziziphus jujuba Mill.) Fruit Based on UAV Multi-Spectrum

To enhance the accuracy of multispectral detection using unmanned aerial vehicles (UAVs), multispectral data of jujube fruit with different soluble solids content (SSC) and moisture content (MC) were obtained under different relative azimuth angles. Prediction models for SSC and MC of jujube fruit were established using partial least squares regression (PLSR) and support vector machines (SVM), respectively. The findings revealed that the MC of jujube fruit had the best prediction effect when the relative azimuth angle was 90°, while the SSC of the jujube fruit had the best prediction effect at an azimuth angle of 180°. Then, the spectral reflectance data corresponding to the eight relative azimuth angles were used as input variables to establish a jujube fruit quality detection model. The results showed that the prediction model for MC and SSC, established using the angle fusion method, had higher detection accuracy compared to the prediction model established at a single angle. This research provides a technical reference for improving the accuracy of outdoor jujube fruit quality detection using spectral technology.

Optimization of Online Soluble Solids Content Detection Models for Apple Whole Fruit with Different Mode Spectra Combined with Spectral Correction and Model Fusion.

Soluble solids content (SSC) is one of the main quality indicators of apples, and it is important to improve the precision of online SSC detection of whole apple fruit. Therefore, the spectral pre-processing method of spectral-to-spectral ratio (S/S), as well as multiple characteristic wavelength member model fusion (MCMF) and characteristic wavelength and non-characteristic wavelength member model fusion (CNCMF) methods, were proposed for improving the detection performance of apple whole fruit SSC by diffuse reflection (DR), diffuse transmission (DT) and full transmission (FT) spectra. The modeling analysis showed that the S/S- partial least squares regression models for all three mode spectra had high prediction performance. After competitive adaptive reweighted sampling characteristic wavelength screening, the prediction performance of all three model spectra was improved. The particle swarm optimization-extreme learning machine models of MCMF and CNCMF had the most significant enhancement effect and could make all three mode spectra have high prediction performance. DR, DT, and FT spectra all had some prediction ability for apple whole fruit SSC, with FT spectra having the strongest prediction ability, followed by DT spectra. This study is of great significance and value for improving the accuracy of the online detection model of apple whole fruit SSC.

Non-Destructive Detection of Golden Passion Fruit Quality Based on Dielectric Characteristics

This study pioneered a non-destructive testing approach to evaluating the physicochemical properties of golden passion fruit by developing a platform to analyze the fruit’s electrical characteristics. By using dielectric properties, the method accurately predicted the soluble solids content (SSC), Acidity and pulp percentage (PP) in passion fruit. The investigation entailed measuring the relative dielectric constant (ε′) and dielectric loss factor (ε″) for 192 samples across a spectrum of 34 frequencies from 0.05 to 100 kHz. The analysis revealed that with increasing frequency and fruit maturity, both ε′ and ε″ showed a declining trend. Moreover, there was a discernible correlation between the fruit’s physicochemical indicators and dielectric properties. In refining the dataset, 12 outliers were removed using the Local Outlier Factor (LOF) algorithm. The study employed various advanced feature extraction techniques, including Recursive Feature Elimination with Cross-Validation (RFECV), Permutation Importance based on Random Forest Regression (PI-RF), Permutation Importance based on Linear Regression (PI-LR) and Genetic Algorithm (GA). All the variables and the selected variables after screening were used as inputs to build Extreme Gradient Boosting (XGBoost) and Categorical Boosting (Cat-Boost) models to predict the SSC, Acidity and PP in passion fruit. The results indicate that the PI-RF-XGBoost model demonstrated superior performance in predicting both the SSC (R2 = 0.9240, RMSE = 0.2595) and the PP (R2 = 0.9092, RMSE = 0.0014) of passion fruit. Meanwhile, the GA-CatBoost model exhibited the best performance in predicting Acidity (R2 = 0.9471, RMSE = 0.1237). In addition, for the well-performing algorithms, the selected features are mainly concentrated within the frequency range of 0.05–6 kHz, which is consistent with the frequency range highly correlated with the dielectric properties and quality indicators. It is feasible to predict the quality indicators of fruit by detecting their low-frequency dielectric properties. This research offers significant insights and a valuable reference for non-destructive testing methods in assessing the quality of golden passion fruit.

La2O3 Nanoparticles Can Cause Cracking of Tomato Fruit through Genetic Reconstruction.

La2O3 nanoparticles (NPs) have shown great potential in agriculture, but cracking of plant sensitive tissue could occur during application, resulting in a poor appearance, facilitating entry for insects and fungi, and increasing economic losses. Herein, exocarp cracking mechanisms of tomato (Solanum lycopersicum L.) fruit in response to La2O3 NPs were investigated. Tomato plants were exposed to La2O3 NPs (0-40 mg/L, 90 days) by a split-root system under greenhouse condition. La2O3 NPs with high concentrations (25 and 40 mg/L) increased the obvious cracking of the fruit exocarp by 20.0 and 22.7%, respectively. After exposure to 25 mg/L La2O3 NPs, decreased thickness of the cuticle and cell wall and lower wax crystallization patterns of tomato fruit exocarp were observed. Biomechanical properties (e.g., firmness and stiffness) of fruit exocarp were decreased by 34.7 and 25.9%, respectively. RNA-sequencing revealed that the thinner cuticle was caused by the downregulation of cuticle biosynthesis related genes; pectin remodeling, including the reduction in homogalacturonan (e.g., LOC101264880) and rhamnose (e.g., LOC101248505), was responsible for the thinner cell wall. Additionally, genes related to water and abscisic acid homeostasis were significantly upregulated, causing the increases of water and soluble solid content of fruit and elevated fruit inner pressure. Therefore, the thinner fruit cuticle and cell wall combined with the higher inner pressure caused fruit cracking. This study improves our understanding of nanomaterials on important agricultural crops, including the structural reconstruction of fruit exocarp contributing to NPs-induced cracking at the molecular level.

Prediction of Soluble-Solid Content in Citrus Fruit Using Visible-Near-Infrared Hyperspectral Imaging Based on Effective-Wavelength Selection Algorithm.

Citrus fruits were sorted based on external qualities, such as size, weight, and color, and internal qualities, such as soluble solid content (SSC), acidity, and firmness. Visible and near-infrared (VNIR) hyperspectral imaging techniques were used as rapid and nondestructive techniques for determining the internal quality of fruits. The applicability of the VNIR hyperspectral imaging technique for predicting the SSC in citrus fruits was evaluated in this study. A VNIR hyperspectral imaging system with a wavelength range of 400-1000 nm and 100 W light source was used to acquire hyperspectral images from citrus fruits in two orientations (i.e., stem and calyx ends). The SSC prediction model was developed using partial least-squares regression (PLSR). Spectrum preprocessing, effective wavelength selection through competitive adaptive reweighted sampling (CARS), and outlier detection were used to improve the model performance. The performance of each model was evaluated using the coefficient of determination (R2) and root mean square error (RMSE). In the present study, the PLSR model was developed using only a citrus cultivar. The SSC prediction CARS-PLSR model with outliers removed exhibited R2 and RMSE values of approximatively 0.75 and 0.56 °Brix, respectively. The results of this study are expected to be useful in similar fields such as agricultural and food post-harvest management, as well as in the development of an online system for determining the SSC of citrus fruits.

The analysis of approaches to assessing the sugar content of fruit and vegetable products

The relevance of this study is due to the growing interest of modern consumers in healthy eating, where fruit and vegetables play an important role, which should not only be aesthetically pleasing but also have high taste potential. The purpose of the article is to analyse and compare different approaches to assessing the sugar content of fruit and vegetable products, their effectiveness, and to substantiate areas for improvement. For this purpose, the author analysed the literature and regulatory and technical documents. Traditional methods for determining the sugar content are considered: total content, soluble solids content, and total soluble solids content. It has been established that the soluble solids content and the total soluble solids content of fruits cannot be equated and should be adjusted using an appropriate coefficient based on the percentage of sugars. It has been shown that the content of total soluble substances does not always correctly reflect the sugar content and does not correlate with the taste of sweetness of fruit and vegetables. The necessity of taking into account acidity, which significantly affects the perception of sweet taste, has been established. High acidity can inhibit the sweet taste of fruit and vegetables, even with a very high sugar content. It is proposed to use the ratio of sugar content to titratable acidity for a comprehensive assessment of the sugar content and taste of products. The necessity of using the BrimA and sweetness indices, which combine the indicators of sugars and acidity, as well as reflect the contribution of a single carbohydrate to the total sugar content of the product, is substantiated. These indices allow for a comprehensive assessment of sugar content and predict the sensory perception of fruit and vegetable raw materials. The absence of a single standardised approach and the need for comparative analysis to select optimal methods for measuring the sugar content of fruit and vegetable products are noted, so there is an urgent need to standardise such approaches to improve data comparison. The results of the article can be used to select the most informative methods of sugar content analysis. This will optimise quality control procedures and standardisation of measurements in the food industry

Soluble solids content monitoring and shelf life analysis of winter jujube at different maturity stages by Vis-NIR hyperspectral imaging

Visible and near infrared (Vis-NIR) hyperspectral imaging was used for soluble solids content (SSC) monitoring and shelf life analysis of winter jujube at different maturity stages. Relationships between SSC of mid-ripe and ripe fruit and their spectral data were investigated using support vector regression (SVR) and partial least squares regression (PLSR) models. The best determination coefficient and residual predictive deviation of the external validation set were 0.837 and 2.47 for mid-ripe winter jujube, and 0.806 and 2.28 for ripe winter jujube, respectively. This implied that the more effective prediction performances for SSC emerged from SVR model using the effective wavelengths screened by successive projections algorithm (SPA). A significant correlation between the spatial distribution of SSC and maturity and shelf life was found in the prediction maps. Furthermore, shelf life was analyzed using a library for support vector machines (LIBSVM) with an accuracy of 89% and 91% for mid-ripe and ripe fruit in the external validation set, respectively. These results indicate the great potential of hyperspectral imaging for quality monitoring and shelf life analysis of postharvest winter jujube.

Tomato plants expressing a stilbene synthase gene display genotype‐depending alterations in metabolome profile and antioxidant system

AbstractIn the present work, we report a study on tomato Micro‐Tom lines expressing the Vitis vinifera StSy1 cDNA encoding stilbene synthase under the control of a CaMV 35S promoter. Transgenic lines (T1 plants) were evaluated in terms of vegetative and reproductive development, fruit production, the activity of the main antioxidant enzymes, and the metabolome profile in both leaves and fruit juices. Trans‐resveratrol and glycosylated derivates accumulated in some of the transgenic lines generated, the concentration of both compounds being higher in the leaves than in the fruit juices. Vegetative development was enhanced by transformation, whereas fruit production decreased, and fruit soluble solids content (°Bx) increased. Remarkably, trans‐resveratrol content in leaves and fruit juices showed no correlation with the expression levels of StSy1. An alteration of the metabolome profile and antioxidant enzyme activities was recorded in most of the transgenic lines. In tomato fruit juices, the variation between the wild type and transgenic lines was attributed to a major number of differentially expressed metabolites as compared to that observed in the leaves. In this sense, the major changes corresponded to an induction of phenylpropanoid pathway‐related compounds in the lines accumulating trans‐resveratrol. Transgenic lines producing resveratrol showed, overall, an imbalanced antioxidant metabolism characterized by higher superoxide dismutase (H2O2‐producing enzyme) activity and lower H2O2‐scavenging enzyme activities. This work contributes to deciphering the biochemical consequences of StSy1 introduction in tomato and opens up prospects for further characterization of the transformants.

CALITATEA FRUCTELOR UNOR SOIURI DE CIREȘ ÎN RAPORT CU CERINŢELE CONSUMATORULUI

The fruit quality is a complex of characteristics and traits, such as: fruit size, the content of sugar, acids, flesh consistence and succulence, flavour, etc. The objective of this study was to analyze fruit quality of sweet cherry cultivars in correlation with consumer preferences. The study was carried out at Genetic and Breeding Department of Research Institute of Fruit Growing Pitesti, Romania on 13 Romanian genotypes (‘Daria’, ‘Maria’, ‘Radu’, ‘Izverna’, ‘Tentant’, ‘Colina’, ‘Superb’, ‘Rubin’, ‘Simbol’, ‘Severin’, ‘H 04-4-38’, ‘H 06-3-77’, ‘H 06-11-57’) and 11 foreign cultivars (‘Kordia’, ‘Regina’, ‘Sweetheart’, ‘Karina’, ‘Vanda’, ‘Hertfort’, ‘Areko’, ‘Lapins’, ‘Penny’, ‘Folfer’, ‘Bigarreau Burlat’), in 2021 and 2022 years. The following determinations were carried out: fruit size by weighing, flesh firmness with penetrometer non-destructive Qualitest, soluble solids content with digital refractometer and pH with Hanna HI 84532 minititrator, such as sensory evaluation of fruits using a scale from 1 (very low) to 9 (very good). The results showed that the foreign cultivars were superior to the Romanian genotypes from the point of view of the size and fruits quality. Thus, on foreign cvs., the average fruit weight was 9.31 g, while on Romanian ones of 8.39 g. The soluble solids content of fruits was higher on foreign cvs. compared to the Romanian ones (15,59% Brix respectively 14.75% Brix). On the other hand, after the sensory evaluation of the fruits, the total score was slightly higher for the Romanian genotypes (51.20) compared to the foreign ones (51.08). For Romanian consumers the most important characteristics when choosing the cherry fruits are: taste - which must be sweet or medium sweet; size - which must be large and very large; colour – red and dark red; firmness – firm and very firm fruits. These results could be useful to breeders for selection the cultivars as genitors in controlled hybridization, to farmers for correct selection of cultivars on establishing new orchards, and to the fruit market for fresh consumption.