Film mulching counteracts the adverse effects of mild moisture deficiency, and improves the quality and yield of Cyperus esculentus. L grass and tuber in the oasis area of Tarim Basin.

Introduction: Plastic film mulching (PFM) and deficit irrigation (DI) are vital water-saving approaches in arid agriculture. Cyperus esculentus is a significant crop in dry zones. However, scant data exists on the impacts of these water-saving methods on C. esculentus yield and quality. Method: Using randomized block experiment design. Three irrigation strategies were tested: CK (standard irrigation), RW20 (20% water reduction), and RW40 (40% water reduction). Mulchin treatments included film mulching (FM) and no film mulching (NFM). Results: Results revealed substantial effects of film mulching and drip irrigation on soil nutrients and physical properties, with minor influence on grass, root, and tuber stoichiometry. PF treatment, DI treatments, and their interaction significantly affected C. esculentus forage and tuber yields. Initially, grass and tuber yields increased and then decreased with reduced irrigation. The highest yields were under RW20 (3716.31 and 4758.19 kg/ha). FM increased grass and tuber yield by 17.99% and 8.46%, respectively, over NFM. The water reduction augmented the biomass distribuiton of the leaf and root, while reducing the tuber biomass in NFM. FM significantely impacted grass ether extract content, while reduced water influenced grass and tuber crude protein and tuber ether extract content. Mild water stress increased ether extract, crude protein, and soluble matter in grass and tubers, while excessive RW decreased them. Conclusion: Integrating soil traits, nutrients, yield, and quality, findings indicate C. esculentus yield and quality primarily hinge on soil water content, pond hydrogenase, and electrical conductivity. Based on this results, the recommended strategy is to reduce irrigation by 20% for cultivating C. esculentus in this area.

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.

Climate changes altered the citrus fruit quality: A 9-year case study in China.

Global climate change has significantly impacted the production of various crops, particularly long-term fruit-bearing plants such as citrus. This study analyzed the fruit quality of 12 citrus orchards (Citrus Sinensis L.Osbeck cv. Bingtang) in a subtropical region in Yunnan, China from 2014 to 2022. The results indicated that high rainfall (>220 mm) and low cumulative temperature (<3150 °C) promoted increases in titratable acidity (>1.8 %) in young fruits. As the fruits further expanded (with a horizontal diameter increasing from 50 to 65 mm), excessive rainfall (300-400 mm), lower cumulative temperature (<2400 °C), and a reduced diurnal temperature range (<10 °C) hindered decreases in titratable acidity. Conversely, low rainfall (<220 mm), high cumulative temperature (>3150 °C), and a high diurnal temperature range (>14 °C) promoted the accumulation of soluble solids in young fruits (9 %) at 120 days after flowering (DAF). Furthermore, low rainfall (<100 mm) favored the accumulation of soluble solids (1.5 %) during fruit expansion (195-225DAF). To quantify the relationship between fruit acidity and climate variables at 120 DAF, we developed a regression model, which was further validated by actual measurements and accurately predicted fruit acidity in 2023. Our findings have the potential to assist citrus growers in optimizing cultivation techniques for the production of high-quality citrus under increasingly variable climatic conditions.

Determination of soluble solids content of multiple varieties of tomatoes by full transmission visible-near infrared spectroscopy.

Introduction: Soluble solids content (SSC) is a pivotal parameter for assessing tomato quality. Traditional measurement methods are both destructive and time-consuming. Methods: To enhance accuracy and efficiency in SSC assessment, this study employs full transmission visible and near-infrared (Vis-NIR) spectroscopy and multi-point spectral data collection techniques to quantitatively analyze SSC in two tomato varieties ('Provence' and 'Jingcai No.8' tomatoes). Preprocessing of the multi-point spectra is carried out using a weighted averaging approach, aimed at noise reduction, signal-to-noise ratio improvement, and overall data quality enhancement. Taking into account the potential influence of various detection orientations and preprocessing methods on model outcomes, we investigate the combination of partial least squares regression (PLSR) with two orientations (O1 and O2) and two preprocessing techniques (Savitzky-Golay smoothing (SG) and Standard Normal Variate transformation (SNV)) in the development of SSC prediction models. Results: The model achieved the best results in the O2 orientation and SNV pretreatment as follows: 'Provence' tomato (Rp = 0.81, RMSEP = 0.69°Brix) and 'Jingcai No.8' tomatoes (Rp = 0.84, RMSEP = 0.64°Brix). To further optimize the model, characteristic wavelength selection is introduced through Least Angle Regression (LARS) with L1 and L2 regularization. Notably, when λ=0.004, LARS-L1 produces superior results ('Provence' tomato: Rp = 0.95, RMSEP = 0.35°Brix; 'Jingcai No.8' tomato: Rp = 0.96, RMSEP = 0.33°Brix). Discussion: This study underscores the effectiveness of full transmission Vis-NIR spectroscopy in predicting SSC in different tomato varieties, offering a viable method for accurate and swift SSC assessment in tomatoes.

Integrating Smart Greenhouse Cover, Reduced Nitrogen Dose and Biostimulant Application as a Strategy for Sustainable Cultivation of Cherry Tomato.

Fruit yield and quality of greenhouse tomatoes are strongly influenced by light conditions and nitrogen (N) availability, however, the interaction between these factors is still unclear. We evaluated the effects on cherry tomatoes of two tunnel plastic covers with different optical properties and three N doses, also in combination with a biostimulant treatment. We compared a diffuse light film (Film1) and a conventional clear film (Film2), and three N levels, corresponding to 50% (N50), 75% (N75) and 100% (N100) of the optimal dose, with and without a microbial plus a protein hydrolysed biostimulant, compared to a non-treated control. The three experimental treatments significantly interacted on several yield and quality parameters. In control plants (untreated with biostimulants), the early yield was higher at reduced N doses compared to N100, with greater increments under the diffusive Film1 compared to the clear Film2 (+57.7% and +37.0% vs. +31.7% and +16.0%, in N50 and N75 respectively). Film1 boosted the total fruit production at all the N rates and with or without biostimulants, compared to Film2, with stronger effects under sub-optimal N (+29.4% in N50, +21.2% in N75, and +7.8% in N100, in plants untreated with biostimulant). Total yield decreased with decreasing N levels, while it always increased with the application of biostimulants, which counterbalanced the detrimental effects of N shortage. Quality traits were mainly affected by the cover film and the biostimulant treatment. The diffusive film increased the content of carotenoids, lycopene and total phenols compared to the clear one, and the biostimulants increased texture, soluble solids, phenols and ascorbic acid compared to the untreated control. It is worth noting that in plants fertilized at 75% of the reference N dose, the biostimulants determined higher yield than the N100 untreated control, under both the covers (+48% in Film1 and +20% in Film2). In conclusion, the diffusive film improved the fruit yield and quality of greenhouse tomatoes in the spring-summer period, presumably avoiding plant stress due to high-intensity direct light. Reduced N rates limited the plant productivity, however, the biostimulant application was effective in compensating for the detrimental effects of sub-optimal supply of N synthetic fertilizers.

Detection of peach soluble solids based on near-infrared spectroscopy with High Order Spatial Interaction network.

BACKGROUND: Due to the scalability of deep learning technology, researchers have applied it to the non-destructive testing of peach internal quality. In addition, the soluble solids content (SSC) is an important internal quality indicator that determines the quality of peaches. Peaches with high SSC have a sweeter taste and better texture, making them popular in the market. Therefore, SSC is an important indicator for measuring peach internal quality and making harvesting decisions. RESULTS: This article presents the High Order Spatial Interaction Network (HOSINet), which combines the Position Attention Module (PAM) and Channel Attention Module (CAM). Additionally, a feature wavelength selection algorithm similar to the Group-based Clustering Subspace Representation (GCSR-C) is used to establish the Position and Channel Attention Module-High Order Spatial Interaction (PC-HOSI) model for peach SSC prediction. The accuracy of this model is compared with traditional machine learning and traditional deep learning models. Finally, the permutation algorithm is combined with deep learning models to visually evaluate the importance of feature wavelengths. Increasing the order of the PC-HOSI model enhances its ability to learn spatial correlations in the dataset, thus improving its predictive performance. CONCLUSION: The optimal model, PC-HOSI model, performed well with an order of 3 (PC-HOSI-3), with a root mean square error of 0.421 °Brix and a coefficient of determination of 0.864. Compared with traditional machine learning and deep learning algorithms, the coefficient of determination for the prediction set was improved by 0.07 and 0.39, respectively. The permutation algorithm also provided interpretability analysis for the predictions of the deep learning model, offering insights into the importance of spectral bands. These results contribute to the accurate prediction of SSC in peaches and support research on interpretability of neural network models for prediction. © 2024 Society of Chemical Industry.

Non-destructive assessment of soluble solids content in kiwifruit using hyperspectral imaging coupled with feature engineering.

The maturity of kiwifruit is widely gauged by its soluble solids content (SSC), with accurate assessment being essential to guarantee the fruit's quality. Hyperspectral imaging offers a non-destructive alternative to traditional destructive methods for SSC evaluation, though its efficacy is often hindered by the redundancy and external disturbances of spectral images. This study aims to enhance the accuracy of SSC predictions by employing feature engineering to meticulously select optimal spectral features and mitigate disturbance effects. We conducted a comprehensive investigation of four spectral pre-processing and nine spectral feature selection methods, as components of feature engineering, to determine their influence on the performance of a linear regression model based on ordinary least squares (OLS). Additionally, the stacking generalization technique was employed to amalgamate the strengths of the two most effective models derived from feature engineering. Our findings demonstrate a considerable improvement in SSC prediction accuracy post feature engineering. The most effective model, when considering both feature engineering and stacking generalization, achieved an RMSEp of 0.721, a MAPEp of 0.046, and an RPDp of 1.394 in the prediction set. The study confirms that feature engineering, especially the careful selection of spectral features, and the stacking generalization technique are instrumental in bolstering SSC prediction in kiwifruit. This advancement enhances the application of hyperspectral imaging for quality assessment, offering benefits that extend across the agricultural industry.

Inter seasonal validation of non-contact NIR spectroscopy for measurement of total soluble solids in high tunnel strawberries.

Autonomous field robots are being developed for picking of fruit, where each fruit needs to be individually graded and handled. There is therefore a need for rapid and non-destructive sensing to measure critical fruit quality parameters. In this article we report how total soluble solids (TSS), a measure for total sugar content, can be measured in strawberries in the field by non-contact near-infrared (NIR) interaction spectroscopy. A specially designed prototype system working in the wavelength range 760-1080 nm was tested for this purpose. This novel instrument was compared with a commercial handheld NIR reflection instrument working in the range 900-1600 nm. The instruments were calibrated in the lab using data collected from 200 strawberries of two varieties and tested in a strawberry field on 50 berries in 2022 and 100 berries in 2023. Both systems performed well during calibration with root mean square errors of cross validation for TSS around 0.49 % and 0.57 %, for interaction and reflection, respectively. For prediction of TSS in new berries in 2023, the interaction system was superior, with a prediction error of 1.0 % versus 8.1 % for the reflection system, most likely because interaction probes deeper into the berries. The results suggest that interaction measurements of average TSS are more robust and would most likely require less calibration maintenance compared to reflection measurements. The non-contact feature is important since it reduces the spread of diseases and physical damage to the berries.

Quality Characteristics, Sensory Profiles and Ethylene Production of Stored 'Abate Fetel' Pears Sorted at Harvest by Time-Resolved Reflectance Spectroscopy.

Time-resolved reflectance spectroscopy (TRS), a nondestructive technique, can help the industry to provide high-quality fruit to encourage pear consumption. The absorption coefficient measured by TRS at 670 nm (µa670) represents a maturity index for pear fruit, with less mature pears high µa670 and more mature low µa670. The aim of this work was to study the quality characteristics, the sensory profiles and the ethylene production of 'Abate Fetel' pears sorted at harvest in different TRS maturity classes and stored in different atmospheres. At harvest, 540 pears were measured by TRS for µa670, ranked by µa670 in three maturity classes (less-LeM, medium-MeM and more-MoM mature) and randomized in nine samples according to 1-MCP treatment (treated, control), storage time (4-6 months) and atmosphere (air-NA; CA: 8-12 kPa O2, 1 kPa CO2). Fruits were examined at harvest and after 7 days of poststorage shelf life for skin color, firmness, soluble solids, acidity and ethylene production and were submitted to sensory analysis. At harvest and after storage, MoM pears were less green and showed a higher SSC content than LeM ones. After storage, MoM pears produced less ethylene and were perceived to be firmer (especially in 1-MCP-treated pears), more astringent and less juicy (when stored for 6 months) than LeM ones.

Physiological response, phytochemicals, antioxidant, and enzymatic activity of date palm (Phoenix dactylifera L.) cultivated under different storage time, harvesting Stages, and temperatures.

The quality of date palm is highly influenced by postharvest techniques, storage, and processing effects. Fruits stored at room temperature result in dehydration, whereas higher temperatures accelerate the enzymatic browning of fruit. This study aimed to enhance postharvest quality of date palms through improved harvesting and storage techniques. The fruits of date palm (Phoenix dactylifera L. cv. Dhakki) were harvested at khalal (mature, firm), rutab (fully ripe), or tamar (dry) stages and stored at different temperatures (12, 18, or 24 °C) for 0, 15, 30, or 45 days. The analysis of the data showed that the studied attributes significantly different at various ripening stages and storage temperatures. The fruits harvested at Khalal stage proved to be the best in retaining moisture content (23.16%), total soluble solids (20.36 oBrix), fruit juice pH (4.97), ascorbic acid (24.65 mg 100 g-1), non-reducing sugars (26.84%), percent acidity (0.39%), antioxidant activity (211.0 mg 100 g-1), total phenolic (40.07 mg100g-1), flavonoids (45.8 mg 100 g-1), tannin (70.7 mg100g-1), catalase (1.82 U g-1), peroxidase (1.4 U g-1), soluble protein (38.2 mg kg-1), brightness (29.9), chroma (16.4), hue angle (34.9), color (16.8), and with minimum weight loss (8.48%) as compared to fruit harvested at Rutab and Tamar stage. Regarding the means for storage temperature, the fruits stored at 12 ± 3 °C retained the highest moisture content (23.2%), total soluble solids (13.5 oBrix), fruit juice pH (5.42), percent acidity (0.29%), ascorbic acid (24.4 mg100g-1), reducing sugars (31.1%), non-reducing sugars (26.5%), antioxidant activity (214.6 mg100g-1), total phenolic (41.6 mg100 g-1), flavonoids (44.7 mg100 g-1), tannin (71.7 mg 100 g-1), catalase (1.56 U g-1), peroxidase (1.21 U g-1), soluble protein (31.8 mg kg-1), brightness (28.8), chroma (15.3), hue angle (29.6), color (16.2),with minimum weight loss (9.91%). It was concluded that for quality fruit production of date palm cv. Dhakki could be harvested at Khalal stage and stored at a temperature of 12 ± 3 °C.

QTL Mapping and Genome-Wide Association Study Reveal Genetic Loci and Candidate Genes Related to Soluble Solids Content in Melon.

Melon (Cucumis melo L.) is an economically important Cucurbitaceae crop grown around the globe. The sweetness of melon is a significant factor in fruit quality and consumer appeal, and the soluble solids content (SSC) is a key index of melon sweetness. In this study, 146 recombinant inbred lines (RILs) derived from two oriental melon materials with different levels of sweetness containing 1427 bin markers, and 213 melon accessions containing 1,681,775 single nucleotide polymorphism (SNP) markers were used to identify genomic regions influencing SSC. Linkage mapping detected 10 quantitative trait loci (QTLs) distributed on six chromosomes, seven of which were overlapped with the reported QTLs. A total of 211 significant SNPs were identified by genome-wide association study (GWAS), 138 of which overlapped with the reported QTLs. Two new stable, co-localized regions on chromosome 3 were identified by QTL mapping and GWAS across multiple environments, which explained large phenotypic variance. Five candidate genes related to SSC were identified by QTL mapping, GWAS, and qRT-PCR, two of which were involved in hydrolysis of raffinose and sucrose located in the new stable loci. The other three candidate genes were involved in raffinose synthesis, sugar transport, and production of substrate for sugar synthesis. The genomic regions and candidate genes will be helpful for molecular breeding programs and elucidating the mechanisms of sugar accumulation.

Pre-Harvest Salicylic Acid Application Affects Fruit Quality and Yield under Deficit Irrigation in Aristotelia chilensis (Mol.) Plants.

Salicylic acid (SA) application is a promising agronomic tool. However, studies under field conditions are required, to confirm the potential benefits of SA. Thus, SA application was evaluated under field conditions for its effect on abscisic acid levels, antioxidant related-parameters, fruit quality, and yield in Aristotelia chilensis subjected to different levels of irrigation. During two growing seasons, three-year-old plants under field conditions were subjected to full irrigation (FI: 100% of reference evapotranspiration (ETo), and deficit irrigation (DI: 60% ETo). During each growth season, a single application of 0.5 mM SA was performed at fruit color change by spraying fruits and leaves of both irrigation treatments. The results showed that DI plants experienced moderate water stress (-1.3 MPa), which increased ABA levels and oxidative stress in the leaves. The SA application facilitated the recovery of all physiological parameters under the DI condition, increasing fruit fresh weight by 44%, with a 27% increase in fruit dry weight, a 1 mm increase in equatorial diameter, a 27% improvement in yield per plant and a 27% increase in total yield, with lesser oxidative stress and tissue ABA levels in leaves. Also, SA application significantly increased (by about 10%) the values of fruit trait variables such as soluble solids, total phenols, and antioxidant activity, with the exceptions of titratable acidity and total anthocyanins, which did not vary. The results demonstrated that SA application might be used as an agronomic strategy to improve fruit yield and quality, representing a saving of 40% regarding water use.

Optimization of sonication time, edible coating concentration, and osmotic solution °Brix for the dehydration process of quince slices using response surface methodology.

The goal of this work was to examine the effects of sonication time, edible coating concentration (with guar gum), and °Brix (sucrose solution) on the osmotic dehydration (OD) parameters (mass reduction, water loss, soluble solids gain, and rehydration ratio) and the appearance properties (color indices and surface area) of quince slices using a response surface methodology (RSM) approach based on the central composite design (CCD), for the optimization of the process. The process parameters, sonication treatment time (5-10 min; 40 kHz and 150 W), edible coating concentration using guar gum (0.05%-0.15%, w/w), and osmotic concentration using sucrose solution (20%-50%, w/w), were investigated and optimized for OD of quince slices. After each OD process, the quince slices were dehydrated in an oven at 70°C for 240 min. Results demonstrated a good correlation between empirical data with the linear model. Using the optimization method, optimum input operating conditions were determined to be a sonication time of 5 min, guar gum concentration of 0.05%, and sucrose concentration of 37.19°Brix. At this optimum point, the OD process of quince slices reached the optimal mass reduction (17.74%), water loss (25.77%), soluble solids gain (8.03%), rehydration ratio (206.19%), lightness (77.6), redness (0.60), yellowness (34.84), total color change (ΔE) (8.92), and area changes (7.59%).

Fine Mapping of fw6.3, a Major-Effect Quantitative Trait Locus That Controls Fruit Weight in Tomato.

Tomato (Solanum lycopersicum) is a widely consumed vegetable, and the tomato fruit weight is a key yield component. Many quantitative trait loci (QTLs) controlling tomato fruit weight have been identified, and six of them have been fine-mapped and cloned. Here, four loci controlling tomato fruit weight were identified in an F2 population through QTL seq.; fruit weight 6.3 (fw6.3) was a major-effect QTL and its percentage of variation explanation (R2) was 0.118. This QTL was fine-mapped to a 62.6 kb interval on chromosome 6. According to the annotated tomato genome (version SL4.0, annotation ITAG4.0), this interval contained seven genes, including Solyc06g074350 (the SELF-PRUNING gene), which was likely the candidate gene underlying variation in fruit weight. The SELF-PRUNING gene contained a single-nucleotide polymorphism that resulted in an amino acid substitution in the protein sequence. The large-fruit allele of fw6.3 (fw6.3HG) was overdominant to the small-fruit allele fw6.3RG. The soluble solids content was also increased by fw6.3HG. These findings provide valuable information that will aid the cloning of the FW6.3 gene and ongoing efforts to breed tomato plants with higher yield and quality via molecular marker-assisted selection.

Quality Assessment and Ripeness Prediction of Table Grapes Using Visible-Near-Infrared Spectroscopy.

Ripeness significantly affects the commercial values and sales of fruits. In order to monitor the change of grapes' quality parameters during ripening, a rapid and nondestructive method of visible-near-infrared spectral (Vis-NIR) technology was utilized in this study. Firstly, the physicochemical properties of grapes at four different ripening stages were explored. Data evidenced increasing color in redness/greenness (a*) and Chroma (C*) and soluble solids (SSC) content and decreasing values in color of lightness (L*), yellowness/blueness (b*) and Hue angle (h*), hardness, and total acid (TA) content as ripening advanced. Based on these results, spectral prediction models for SSC and TA in grapes were established. Effective wavelengths were selected by the competitive adaptive weighting algorithm (CARS), and six common preprocessing methods were applied to pretreat the spectra data. Partial least squares regression (PLSR) was applied to establish models on the basis of effective wavelengths and full spectra. The predictive PLSR models built with full spectra data and 1st derivative preprocessing provided the best values of performance parameters for both SSC and TA. For SSC, the model showed the coefficients of determination for calibration (RCal2) and prediction (RPre2) set of 0.97 and 0.93, respectively, the root mean square error for calibration set (RMSEC) and prediction set (RMSEP) of 0.62 and 1.27, respectively; and the RPD equal to 4.09. As for TA, the optimum values of RCal2, RPre2, RMSEC, RMSEP and RPD were 0.97, 0.94, 0.88, 1.96 and 4.55, respectively. The results indicated that Vis-NIR spectroscopy is an effective tool for the rapid and non-destructive detection of SSC and TA in grapes.

Application of near-infrared spectroscopy for the estimation of volatile compounds in Tempranillo Blanco grape berries during ripening.

BACKGROUND: The knowledge of volatile compounds concentration in grape berries is very valuable information for the winemaker, since these compounds are strongly involved in the final wine quality, and in consumer acceptance. In addition, it would allow to set the harvest date according to aromatic maturity, to classify grape berries according to their quality and to make wines with different characteristics, among other implications. However, so far, there are no tools that allow the volatile composition to be measured directly on intact berries, either in the vineyard or in the winery. RESULTS: In this work, the use of near-infrared (NIR) spectroscopy to estimate the aromatic composition and total soluble solids (TSS) of Tempranillo Blanco grape berries during ripening was evaluated. For this purpose, the spectra in the NIR range (1100-2100 nm) of 240 intact berry samples were acquired in the laboratory. From these same samples, the concentration of volatile compounds was analyzed by thin film-solid-phase microextraction-gas chromatography-mass spectrometry (TF-SPME-GC-MS), and the TSS were quantified by refractometry. These two methods were used as reference methods for model building. Calibration, cross-validation and prediction models were built from spectral data using partial least squares (PLS). Determination coefficients of cross-validation (R2 CV ) above 0.5 were obtained for all volatile compounds, their families, and TSS. CONCLUSIONS: These findings support that NIR spectroscopy can be successfully use to estimate the aromatic composition as well as the TSS of intact Tempranillo Blanco berries in a non-destructive, fast, and contactless form, allowing simultaneous determination of technological and aromatic maturities. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Multi-year field trials provide a massive repository of trait data on a highly diverse population of tomato and uncover novel determinants of tomato productivity.

Tomato (Solanum lycopersicum) is a prominent fruit with rich genetic resources for crop improvement. By using a phenotype-guided screen of over 7900 tomato accessions from around the world, we identified new associations for complex traits such as fruit weight and total soluble solids (Brix). Here, we present the phenotypic data from several years of trials. To illustrate the power of this dataset we use two case studies. First, evaluation of color revealed allelic variation in phytoene synthase 1 that resulted in differently colored or even bicolored fruit. Secondly, in view of the negative relationship between fruit weight and Brix, we pre-selected a subset of the collection that includes high and low Brix values in each category of fruit size. Genome-wide association analysis allowed us to detect novel loci associated with total soluble solid content and fruit weight. In addition, we developed eight F2 biparental intraspecific populations. Furthermore, by taking a phenotype-guided approach we were able to isolate individuals with high Brix values that were not compromised in terms of yield. In addition, the demonstration of novel results despite the high number of previous genome-wide association studies of these traits in tomato suggests that adoption of a phenotype-guided pre-selection of germplasm may represent a useful strategy for finding target genes for breeding.

Chitosan-based layer-by-layer edible coatings application for the preservation of mandarin fruit bioactive compounds and organic acids.

The layer-by-layer application of biopolymeric coatings to mandarin fruits as a postharvest treatment to improve fruit coating efficacy has been reported. A single 1 % (w/v) chitosan application was evaluated, and polyelectrolyte complexes such as 1.5 % (w/v) alginate/chitosan, 1 % (w/v) hydroxypropyl methylcellulose/chitosan, and 0.2 % (w/v) locust bean gum/chitosan were applied to mandarin fruits. The quality of coated mandarin fruits was observed at temperatures: 20 ± 2 °C (up to 10 days) and 5 °C (up to 28 days). Changes in the fruit metabolism were observed by evaluating bioactive compounds (polyphenolic compounds and flavonoids), antioxidant activity, and organic acids during the preservation of mandarin fruits. All of the tested combinations of layer-by-layer coatings significantly impacted the quality of mandarin fruits throughout storage, both at room temperature and cold storage, respectively. The overall best performance was observed for a layer-by-layer hydroxypropyl methylcellulose/chitosan coating in terms of visual aspects, bioactive compounds, antioxidant activity, and organic acids content.

Performance of Sweet Cherry Cultivars and Advanced Selections on Gisela 5 Rootstock in Young Orchards.

Six sweet cherry cultivars and two advanced selections of Gisela 5 rootstock were tested in 2015-2021 at the Institute of Horticulture, Lithuanian Research Centre for Agriculture and Forestry. Fruit trees were planted at distances of 4.5 × 2.5 m and trained as spindles. Orchard floor management included frequently mown grass in alleyways with herbicide strips along tree rows. Cultivars 'Mindauge' and 'Irema BS' were the most vigorous at the end of the seventh leaf. Their trunk diameter achieved 11.6 cm. The 'Merchant' cultivar had the smallest trunk diameter-9.3 cm. The average yield in 2018-2021 ranged from 2.75 t/ha for 'Vega' to 8.73 t/ha for 'Regina'. Cultivars 'Regina', 'Sunburst', 'Irema BS' and 'Merchant' had the highest cumulative yield efficiency of 0.440-0.503 kg/cm2 with respect to the trunk cross-section area (TCSA). The least productive cultivar 'Vega' produced fruits of the highest average weight-9.9 g. Fruits of 'Regina' and 'Sunburst' were large as well-8.8-9.1 g. 'Irema BS' fruits had the highest soluble solids content (SSC)-20.2%. The lowest SSC was recorded in 'Merchant' and 'Sunburst' fruits-14.7-15.8%. The yield of advanced selection, No. 102, equaled to the yield of cv. 'Regina'. No. 102 had a high fruit weight, and fruits were distinguished by attractiveness and taste.

Melatonin Treatments Reduce Chilling Injury and Delay Ripening, Leading to Maintenance of Quality in Cherimoya Fruit.

Spain is the world's leading producer of cherimoya, a climacteric fruit highly appreciated by consumers. However, this fruit species is very sensitive to chilling injury (CI), which limits its storage. In the present experiments, the effects of melatonin applied as dipping treatment on cherimoya fruit CI, postharvest ripening and quality properties were evaluated during storage at 7 °C + 2 days at 20 °C. The results showed that melatonin treatments (0.01, 0.05, 0.1 mM) delayed CI, ion leakage, chlorophyll losses and the increases in total phenolic content and hydrophilic and lipophilic antioxidant activities in cherimoya peel for 2 weeks with respect to controls. In addition, the increases in total soluble solids and titratable acidity in flesh tissue were also delayed in melatonin-treated fruit, and there was also reduced firmness loss compared with the control, the highest effects being found for the 0.05 mM dose. This treatment led to maintenance of fruit quality traits and to increases in the storage time up to 21 days, 14 days more than the control fruit. Thus, melatonin treatment, especially at 0.05 mM concentration, could be a useful tool to decrease CI damage in cherimoya fruit, with additional effects on retarding postharvest ripening and senescence processes and on maintaining quality parameters. These effects were attributed to a delay in the climacteric ethylene production, which was delayed for 1, 2 and 3 weeks for 0.01, 0.1 and 0.05 mM doses, respectively. However, the effects of melatonin on gene expression and the activity of the enzymes involved in ethylene production deserves further research.