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In Colombia, blackberry (Rubus spp.) is one of the crops with the most significant geographic coverage, and the ecotype “Castilla” (Rubus glaucus) is the most extensively commercialized. Despite the importance of the crop, there are no registered varieties or hybrids specifically adapted to the diverse growing conditions of the country’s various production areas. The purpose of this study was to evaluate and select advanced genotypes of Castilla blackberry based on yield attributes and physicochemical quality of the fruits. Data from five genotypes and one regional check were recorded in the municipality of Silvania, Cundinamarca, during 2022 and 2023. The yield traits, including the number of fruits per kg and the weight of the fruits harvested, were evaluated, as well as the physicochemical variables: fruit diameter, fruit weight, firmness, acidity, total soluble solids, pH, juice and pulp weights, and maturity index. The data were statistically processed using a generalized linear model, principal component and cluster analysis, and Ward’s minimum variance clustering method. A selection index based on the traits of production, total soluble solids, fruit weight, and firmness, relevant to the crop, was used. Significant differences were observed between genotypes for the yield traits, total soluble solids, pH, acidity, and maturity index. The results suggested that genotypes G1, G4, and G3 were outstanding in terms of yield and fruit quality. However, genotype G1 led the index selection, outperforming the other genotypes under evaluation. En Colombia, la mora (Rubus spp.) es uno de los cultivos con mayor cobertura geográfica, siendo el ecotipo \"Castilla\" (Rubus glaucus) el más comercializado. Pese a la importancia del cultivo, no hay registro de variedades o híbridos específicamente adaptados a las diversas condiciones de crecimiento de las diferentes zonas productoras del país. El propósito de este trabajo fue evaluar y seleccionar genotipos avanzados de mora de Castilla por atributos de rendimiento y calidad fisicoquímica de fruto. Se registraron datos de cinco genotipos y un testigo regional en Silvania, Cundinamarca, durante los años 2022 y 2023. Se evaluaron los atributos de rendimiento: número de frutos por kg y peso de los frutos cosechados, así como las variables fisicoquímicas: diámetros de fruta, peso de fruto, firmeza, acidez, contenido de sólidos solubles totales, pH, pesos de jugo y pulpa, e índice de madurez. Los datos fueron estadísticamente procesados mediante un modelo lineal generalizado, análisis de componentes principales y conglomerados, y el método de agrupamiento de varianza mínima de Ward. Se usó un índice de selección basado en las características: producción, sólidos solubles totales, peso de fruto y firmeza, relevantes para el cultivo. Se observaron diferencias significativas entre los genotipos para las características de rendimiento, sólidos solubles totales, pH, acidez e índice de madurez. Los resultados sugirieron que los genotipos G1, G4 y G3 fueron los sobresalientes en rendimiento y calidad de fruto. Sin embargo, el genotipo G1 lideró la selección por el índice, superando a los otros genotipos en evaluación.

Honey is one of the most valuable food products, which, in addition to its nutritional value, also has therapeutic properties. In our study, the physicochemical (Brix, viscosity, free acid content, pH, moisture, diastase activity, 5-hydroxymethylfurfural (HMF), proline content, sugars content, and reducing sugars content) and microbial (mold and yeast content) characteristics and 15 element contents (As, Cd, K, Al, Pb, Hg, Ba, Ni, Na, Ca, Mg, Fe, Mn, Zn, and Se) of the samples were evaluated. Among the essential elements, the maximum mean was related to K (630 ± 50.8 mg/kg), and the minimum mean was related to Se that was lower than the limit of detection. Also, among all toxic elements, the maximum mean was related to Ni (234 ± 54.7 µg/kg), and the minimum mean was related to Hg that was lower than the limit of detection. Furthermore, the mean of free acidity, pH, °Brix, moisture, diastase content, HMF, and proline content was 35.4 ± 1.27 meq/kg, 4.61 ± 0.21, 82.2 ± 3.08, 16.3 ± 0.33%, 9.10 ± 1.14 DN, 21.1 ± 2.65 mg/kg, and 482 ± 18.1 mg/kg, respectively. Also, the mean percentage of fructose, glucose, and sucrose was 32.4 ± 1.07% (27.5–40.0%), 27.2 ± 0.85% (23.5–31.7%), and 2.28 ± 0.70% (0.72–4.11%), respectively. Finally, the mean of mold and yeast in all samples was 14.2 ± 0.37 CFU/g. Also, the principal component analysis and heat map allowed us to determine a more accurate distinction between the physicochemical characteristics of bee honey. The results of our findings showed that in most cases, the results obtained were within the standard range, which indicates the good quality of Iranian honeys.

Background Fruit quality traits such as fruit weight, firmness, total soluble solids content, and color strongly influence consumer acceptance, market value, postharvest shelf life, and processing efficiency in tomato. Therefore, these traits are central to breeding programs but remain challenging to dissect due to their polygenic and pleiotropic nature. Results We evaluated 167 accessions from the Varitome collection, encompassing Solanum pimpinellifolium , Solanum lycopersicum var. cerasiforme , and Solanum lycopersicum var. lycopersicum . The Varitome collection represents a rich source of genetic and phenotypic diversity, making it a powerful resource for mapping complex traits. Genome-wide association studies (GWAS) were conducted using the FarmCPU and Blink models, utilizing a dataset of 3,879,252 SNPs, 831,152 INDELs, and 11,447 structural variants (SVs). Six fruit-quality traits were phenotyped: fruit weight, firmness, total soluble solids, lightness ( L* ), chroma ( C* ), and hue ( h° ). Our multi-variant GWAS uncovered both known and novel determinants of fruit quality. Known loci such as PSY1 and fw11.3/CSR were validated, while robust new signals were detected on chromosomes 1, 4, 6, 8, and 12 for °Brix and on chromosome 7 for fruit weight. Several pleiotropic hotspots were identified, particularly on chromosomes 1, 5, 6, and 8 for fruit color, supported by convergent SNP, INDEL, and SV associations. Candidate genes included biosynthetic enzymes ( PSY homologs , LIN5 ), sugar transporters (SWEETs, SUTs, and sugar facilitator proteins), transcriptional regulators (MADS-box, bHLH, TCP, NAC, and MYB families), and genes linked to plastid remodeling, light signaling, and oxidative turnover. Integration of INDELs and SVs across models improved mapping resolution and robustness, enabling the detection of loci that would remain hidden in SNP-only scans. Conclusions This study demonstrates the multilayered genetic networks governing tomato fruit quality and expands the catalog of loci contributing to polygenic traits. By using SNPs, INDELs, and SVs with FarmCPU and Blink models, we provide validated and novel targets for marker-assisted breeding, genomic selection, and functional validation. These findings establish a framework for accelerating the development of tomato cultivars with enhanced fruit weight, sweetness, firmness, and color, thereby supporting both market competitiveness and nutritional quality.

Background Brix refractometry can be used to assess colostral immunoglobulin G (IgG) concentration, but studies identifying Brix percentages to detect high‐ and low‐IgG colostrum are lacking for beef cows and interlaboratory agreement is unknown. Objectives Evaluate Brix refractometer performance and interlaboratory agreement for assessing beef cow colostrum IgG concentration, including determination of thresholds to identify colostrum containing IgG concentrations <100 g/L and ≥150 g/L. Animals Beef cows (n = 416) from 11 cow‐calf operations in Alberta, Canada. Methods Colostral IgG concentrations were measured using radial immunodiffusion (RID) and estimated by Brix refractometry for this retrospective study. Spearman correlation coefficients were assessed between RID and Brix refractometry. Likelihood ratios and misclassification cost‐term analysis were used to determine optimal Brix percentages for detecting colostrum containing IgG concentrations <100 g/L and ≥150 g/L. Concordance correlation coefficient (CCC) and Bland‐Altman analyses were performed for Brix percentages obtained at 3 different laboratories. Results Brix percentages obtained at 3 laboratories were positively correlated with IgG results (r = 0.72, 0.68, and 0.76, respectively). Colostrum Brix percentages of <24% and ≥30% were optimal for indicating IgG concentrations of <100 g/L and ≥150 g/L, respectively. Interlaboratory agreement was substantial, with CCC ranging from 0.89 to 0.96 and Bland‐Altman analysis showing small mean differences (−1.2% to 0.09% Brix) and narrow limits of agreements (−4.8% to 2.4% Brix) among laboratories. Conclusions and Clinical Importance Brix refractometry shows good potential for reliably estimating IgG concentrations in beef cow colostrum across multiple laboratories and can be recommended to aid colostrum management decisions on farms.

Quality assessment of fruits, vegetables, or beverages involves classifying the products according to the quality traits such as, appearance, texture, flavor, sugar content. The measurement of sugar content, or Brix, as it is commonly known, is an essential part of the quality analysis of the agricultural products and alcoholic beverages. The Brix monitoring of fruit and vegetables by destructive methods includes sensory assessment involving sensory panels, instruments such as refractometer, hydrometer, and liquid chromatography. However, these techniques are manual, time-consuming, and most importantly, the fruits or vegetables are damaged during testing. On the other hand, the traditional sample-based methods involve manual sample collection of the liquid from the tank in fruit/vegetable juice making and in wineries or breweries. Labour ineffectiveness can be a significant drawback of such methods. This review presents recent developments in different destructive and nondestructive Brix measurement techniques focused on fruits, vegetables, and beverages. It is concluded that while there exist a variety of methods and instruments for Brix measurement, traits such as promptness and low cost of analysis, minimal sample preparation, and environmental friendliness are still among the prime requirements of the industry.

This study aimed to evaluate the influence of cladode pruning on apical dominance in the production and post-harvest of pitaya fruits. The experiment was carried out at the Sítio das Pitaya do Pará, which is in the city of Tomé-Açu, State of Pará, Brazil. A randomized block design (RBD) in a 3 x 2 factorial scheme was used, with four replications for each treatment. Treatments consisted of three stand positions in the field (beginning, middle, and end of row) and two pruning regimes (with and without pruning). The interaction of factors Pruning and Stand position (P*SP) inhibited sprouting, while the Pruning factor provided heavier fruits and with a better pulp/peel ratio. Thus, cladode pruning provided benefits to plant management, production parameters, and post-harvest quality.

Exported fresh intact pineapples must fulfill the minimum internal quality requirement of 12 degree brix. Even though near-infrared (NIR) spectroscopic approaches are promising to non-destructively and rapidly assess the internal quality of intact pineapples, these approaches involve expensive and complex NIR spectroscopic instrumentation. Thus, this research evaluates the performance of a proposed pre-dispersive NIR light sensing approach in non-destructively classifying the Brix of pineapples using K-fold cross-validation, holdout validation, and sensitive analysis. First, the proposed pre-dispersive NIR sensing device that consisted of a light sensing element and five NIR light emitting diodes with peak wavelengths of 780, 850, 870, 910, and 940 nm, respectively, was developed. After that, the diffuse reflectance NIR light of intact pineapples was non-destructively acquired using the developed NIR sensing device before their Brix values were conventionally measured using a digital refractometer. Next, an artificial neural network (ANN) was trained and optimized to classify the Brix values of pineapples using the acquired NIR light. The results of the sensitivity analysis showed that either one wavelength that was near to the water absorbance or chlorophyll band was redundant in the classification. The performance of the trained ANN was tested using new pineapples with the optimal classification accuracy of 80.56%. This indicates that the proposed pre-dispersive NIR light sensing approach coupled with the ANN is promising to be an alternative to non-destructively classifying the internal quality of fruits.

In this Research Communication we assessed factors affecting colostrum quality of dairy Lacaune ewes using the Brix-refractometer. Colostrum from 536 lambings from one commercial intensive dairy Lacaune farm were analysed for the following factors with potential influence in colostrum quality: (1) ewe parity (n = 84–132), (2) length of previous dry period (PDP) (n = 23–214), (3) age at first lambing (AFL) of primiparous ewes (n = 9–88), (4) lambing season (n = 192 or 344), and (5) year (2011–2013, n = 142–203). Parity significantly affected colostrum quality, with primiparous ewes showing the highest Brix refractometer values (22·6 ± 5·6%, P < 0·0001), though values were similar among multiparous ewes. PDP length also significantly affected colostrum quality: ewes with the shortest PDP showed the worst quality (16·8 ± 4·2%, P < 0·0001), with quality gradually rising with PDP length. Colostrum quality was significantly higher in 2011 (21·0 ± 5·2%) than in 2012 or 2013 (P < 0·0001); this likely reflects the several-fold greater proportion of animals with long PDP in 2011. In contrast, neither AFL nor lambing season significantly affected colostrum quality. These results suggest that parity and PDP length can substantially affect ovine colostrum quality of dairy ewes under intensive management conditions and they further show the usefulness of the Brix refractometer for providing a rough estimation of colostrum quality on-farm. However, further studies are needed to determine a validated cut-off Brix value for identifying good-quality colostra in ovine species.

This article is to study the criteria of dehydration model, and to establish the Brixter index. Coffee cherries (Coffea arabica L. var. catimor) were selected from two different farms in Pangkhon village, Chiang Rai province, which are in the northern part of Thailand: Farm A, and Farm B. The low air temperatures (18–30 °C) and low relative humidities (65–30%) technique (LTLH) was gradiently applied, to dehydrate the coffee bean, leading to higher sugar concentration. The applicability of the various measurements, such as physicochemical properties, dehydration kinetic, Brix boosting parameters, and their correlations were investigated. The level of soluble solids (°Brix) and acid concentrations in coffee samples were analyzed, to determine the °Brix/acid and oBrix*pH2 ratios. The qualities of coffee cherries changes depending on the decreasing level of moisture content during the dehydration process. The °Brix degree reveals that by the end of the dehydration process, the sugar concentration of coffee cherries has increased by 1.5 times that of its initial. The °Brix/acid, and oBrix*pH2 ratios highly correlated to the amount of soluble solids (r2 = 0.923 and 0.972, respectively) within coffee cherries. The most suitable timing to select dehydrating coffee cherries for the fermentation process is when the coffee cherries have attained °Brix/acid ratio of > 10 to 33, and oBrix*pH2 ratio of > 400 to 850. These ratios can be used as an efficient instrument to determine the optimum Brix boosting stage of coffee cherry in the LTLH system.