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Increased consumer demand for healthier product options and looming regulation have prompted many consumer goods brands to adjust the amount of sugar content in their product lines, including adding products with reduced sugar content or smaller package sizes. Even as brands adopt such practices, little guidance exists for how they should do so to protect or enhance their brand performance. This research studies whether and when sugar reduction strategies affect sales. The analysis of almost 130,000 product additions by nearly 80 brands over 11 years in the U.S. soda category shows that, on average, products with sugar content reductions perform comparably to similar products without reduced sugar content, while smaller package sizes perform better. Importantly, these effects depend substantially on product labeling, branding, and packaging decisions. By accounting for these contingent effects, this study establishes win–win conditions, in which brands realize higher volume sales while category-level sugar sales decrease. In doing so, the study sheds light on how marketing can bridge brands' sales objective with society's health focus, doing well and doing good simultaneously. [ABSTRACT FROM AUTHOR]

Copyright of Glasnik Zastite Bilja is the property of Zadruzna Stampa D.D. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to produce a low-calorie ice cream with a higher nutritional value using red beetroot (Beta vulgaris L.). Four kinds of ice cream containing 5%, 10 % and 15% sucrose and single red beetroot (RB) ratio 15% and control (15% sucrose+ RB free) encoded as RB5, RB10, RB15 and C were produced respectively. The addition of RB increased pH and decreased the acidity (LA) and dry matter contents compared to control. Ash content was decreased depending on the sucrose ratio. While the lowest overrun value was determined in the RB10 sample (23.08%), the highest was in sample C (39.18%). The increasing of sucrose ratio generally increased the first dropping time and decreased the total melting time. The addition of sucrose reduced the viscosity and the highest viscosity values were observed in the sample RB5. While the lowest total phenolic content (TPC) was observed in the control sample (329.69 GAE mg/kg), the highest TPC was found in the RB5 sample (558.55 GAE mg/kg). Also, the lowest DPPH value was determined in the control sample (13.66% inhibition), the highest DPPH value was determined in the RB10 sample (27.98% inhibition). While fructose and glucose values decreased, sucrose values increased in the ice cream samples depending on the increasing of sucrose ratio.

[Objective] To improve the accuracy of online measurement of sugar content of grapefruit by near infrared spectroscopy. [Methods] The pomelo online non-destructive testing equipment developed by ourselves was used to collect diffuse transmission spectrum data of pomelo in three light regions. In the wavelength range of 650~950 nm, orthonormal variable transformation （SNV）, multiple scattering correction （MSC）, Normalize, Savitzky-Golay first order derivative, SG-1st preprocessed the original data, used the adaptive weighting algorithm （CARS） to screen the spectral characteristics of the grapefruit sugar content, and established a partial least squares regression （PLSR） model. 30 grapefruit samples that were not involved in the modeling were used for online verification. [Results] The modeling effect of light region C combined with SNV-CARS-PLSR method was the best. The coefficient of determination of the prediction set was 0.95 and the root-mean-square error was 0.30 °Brix. In online verification, the coefficient of determination was 0.90 and the root mean square error was 0.58 °Brix. The model had a strong ability to detect the sugar content of grapefruit on line. [Conclusion] The prediction model based on the spectral data collected under the condition that the light spot diameter is 70 mm and the light region C is 20 mm above the equator of the grapefruit can realize the online prediction of the sugar content of the grapefruit more effectively.

Abstract This research assessed the quantitative and qualitative reactions of commercially grown sugar beets to four different harvest dates and their yield stability. The study followed a split-plot design within a randomized complete block design over 3 years. The main plot involved 10 sugar beet cultivars, while the subplot involved four harvest dates: August 13 (HD1), September 7 (HD2), October 3 (HD3), and November 12 (HD4). The study found that environmental conditions, genotypes, and harvest dates significantly affected various traits of sugar beet. Yearly environmental variations and their interactions with genotypes and harvest dates had substantial impacts on all measured traits at the 1% probability level. Additive main effect and multiplicative interaction analysis based on white sugar yield indicated that genotype and environment's additive effects, as well as the genotype–environment interaction, were significant at 1% probability level. Shokoufa and Arya, which exhibit high white sugar yield (WSY) and low first interaction principal component (IPC1) values, are identified as desirable due to their stability across different environments. Among the harvest dates in different years, the fourth and third dates showed a higher yield than the total average. Perfekta and Ekbatan exhibited high specific adaptability. According to the multi-trait stability index, Arta, Arya and Sina were recognized as stable and superior across all measured traits.

Camellia drupifera, a significant woody oil crop in southern China, produces oil from its fruit seeds. Understanding sugar metabolism enzyme regulation is crucial for sugar accumulation and oil synthesis in fruit organs. This study examines the dynamic changes in sugar metabolism across four developmental stages of C. drupifera fruits, from rapid fruit enlargement to oil conversion. We analyzed sugar content, enzyme activity, and transcriptomic data to identify key periods and mechanisms involved in sugar metabolism. Our findings indicate that photosynthetic products are rapidly transported from leaves to fruit organs after synthesis, with transport efficiency decreasing significantly after 48 hours. September was identified as a critical period for oil conversion, during which the highest sucrose levels and SuSy-II enzyme activity were detected in the kernels. A positive correlation was found between high expression of ten genes related to sugar metabolism enzymes and sugar transport proteins and sucrose content. Notably, the expression levels of c158337.graph_c0 (SPS), c166323.graph_c0 (SuSy), c159295.graph_c0 (SUC2-like), and c156402.graph_c0 (SUC2-like) significantly increased during the oil conversion phase.These findings provide a crucial theoretical foundation for elucidating the molecular mechanisms of sugar metabolism in C. drupifera fruits, offering insights that could enhance its economic yield. [ABSTRACT FROM AUTHOR]

This research assessed the quantitative and qualitative reactions of commercially grown sugar beets to four different harvest dates and their yield stability. The study followed a split-plot design within a randomized complete block design over 3 years. The main plot involved 10 sugar beet cultivars, while the subplot involved four harvest dates: August 13 (HD1), September 7 (HD2), October 3 (HD3), and November 12 (HD4). The study found that environmental conditions, genotypes, and harvest dates significantly affected various traits of sugar beet. Yearly environmental variations and their interactions with genotypes and harvest dates had substantial impacts on all measured traits at the 1% probability level. Additive main effect and multiplicative interaction analysis based on white sugar yield indicated that genotype and environment's additive effects, as well as the genotype–environment interaction, were significant at 1% probability level. Shokoufa and Arya, which exhibit high white sugar yield (WSY) and low first interaction principal component (IPC1) values, are identified as desirable due to their stability across different environments. Among the harvest dates in different years, the fourth and third dates showed a higher yield than the total average. Perfekta and Ekbatan exhibited high specific adaptability. According to the multi-trait stability index, Arta, Arya and Sina were recognized as stable and superior across all measured traits. [ABSTRACT FROM AUTHOR]

Cercosporiosis is currently the most important disease of sugar beet leaf apparatus. The yield and sugar content losses it causes can vary greatly depending on the year and the infection rate on the plot. The average yield losses were determined in over 10 years of trials and reach about 10 %. However, in the case of an early infection, local losses can be significantly higher. When it comes to cultivation sustainability, the treatment needs to take into account the possible development of resistance to groups of active substances (strobilurins, azoles). It is advisable that the treatment combines organic fungicide products with inorganic products (Cu, S, Ag); early intervention is of utmost importance. Here, a signalling system, which monitors several parameters and assesses the risk of infection, plays a rather important role. Warm and humid weather is risky for the development of cercosporiosis infection. The daily infection coefficient values are monitored by weather stations directly in the crops, any presence of the pathogen in stands is verified by spore traps. The signalling is also complemented by direct observation and rating in production stands. The return on fungicide treatment increases with infection pressure, yield and sugar beet price. [ABSTRACT FROM AUTHOR]

The production of sugar beet in the Republic of Kazakhstan is insufficient to meet the domestic sugar needs of the population. This shortfall is attributed to the natural and climatic conditions, the high cost of production, and the low use of mineral fertilizers. The objective of the study is to investigate the impact of the organic humic fertilizer "Tumat" on the growth, development, yield, and sugar content of sugar beet in the conditions of irrigated light chestnut soils in Southeast Kazakhstan. Scientific research confirms the effectiveness of using the organic humic fertilizer Tumat for cultivating sugar beets. This fertilizer is highly bioavailable and contains a balanced mix of essential macronutrients and micronutrients, polyunsaturated fatty acids, and other biologically active substances. Foliar feeding of sugar beets enriches the soil with exchangeable potassium, mobile phosphorus, and easily hydrolyzable nitrogen during the plant's vegetative period. Using the Tumat fertilizer enhances plant germination rates by 6.0–16.0%, stimulates growth and development, accelerates the ripening of sugar beets, and increases the yield of tubers by 10.5–15.2%, sugar content by 0.4–0.7%, and sugar output by 13.6–20.8%. An organic humic fertilizer, is recommended as an environmentally safe and effective agricultural product that boosts the productivity and quality of sugar beets, as well as soil fertility. [ABSTRACT FROM AUTHOR]

This study reports on the physicochemical and sensory attributes, total phenolic content, and antioxidant activity of 36 honey samples produced by two different stingless bee species (Tetragonula carbonaria and Tetragonula hockingsi) from Australia. The findings reveal moisture content across all samples ranges from 24.9% to 30.8% (w/w), electrical conductivity from 1.02 to 2.15 mS/cm, pH levels between 3.57 and 6.54, soluble solids from 69.2 to 75.1 °Brix, trehalulose concentrations from 6.20 to 38.2 g/100 g, fructose levels from 7.79 to 33.4 g/100 g, and glucose content from 3.36 to 26.8 g/100 g. Sucrose was undetectable in all investigated samples. In a sensory analysis involving 30 participants, Australian stingless bee honey was perceived as having a more pronounced sourness compared with New Zealand Manuka honey. The study reveals considerable variability in the composition of Australian stingless bee honey, influenced by factors such as floral availability, geographical origin, and time of harvest. It also demonstrates the presence of phenolic compounds and antioxidant activity in stingless bee honey, underlining their potential as a natural source of antioxidants. All investigated samples contain trehalulose, which supports the findings of other recent studies that propose this unusual disaccharide as a marker compound of stingless bee honey. [ABSTRACT FROM AUTHOR]

Copyright of Food & Machinery is the property of Food & Machinery Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The agricultural sector is seriously impacted by climate change, leading to potential risks to food security. In terms of global food production, maize ranks third. As a result, crop production and food security depend critically on assessing the effects of climate change and developing measures to adapt maize. Regarding adaptability, changing planting dates and using different agrochemicals are more effective than other management. Crop models are part of a global decision support system to help farmers maximize yields despite unpredictable weather patterns. To mitigate yield loss and protect the ecosystem, it is essential to use efficient maize-sowing practices in the field. This experiment was carried out to identify the most favorable sowing dates that maximize yield while ensuring the crop's productivity and the integrity of the surrounding ecosystem remain intact. The main aim of this experiment was to mitigate the different climatic conditions by exogenous application of salicylic acid (SA) and sodium nitroprusside (SNP) on pigments and sugar content in maize under different sowing dates. A field experiment was carried out in the School of Agriculture, Lovely Professional University, Punjab, India, during the spring season of 2022. The experiment dealt with various maize crops, PMH-10, sourced from the Punjab Agricultural University (PAU), Punjab. The experiment was conducted in an open-air environment. The experimental setup was laid out in a split-plot design. The results stated that foliar application of salicylic acid and sodium nitroprusside successfully influenced high-temperature tolerance and low temperature at the reproductive phase and initial vegetative stages with other growing climatic conditions of maize in early and late sowings when controlled by increasing the chlorophyll index, carotenoids content, and sugar content of maize. [ABSTRACT FROM AUTHOR]

Sugar overconsumption is a major health threat. Here, we ask (a) how accurate is people's metric knowledge (e.g., mean, range) and mapping knowledge (i.e., relative ordering) of sugar content of food items and (b) can this knowledge be improved with a simple seeding intervention, in which the actual sugar content is provided for a few representative items? Participants (online experiment, N = 160) estimated the sugar content of various food items (in grams) and then received feedback about the actual content for a few representative seed items, with or without additionally seeing the equivalent number of sugar cubes; a control group received no feedback. Finally, they estimated again the sugar content of (seeded and unseeded) items. Participants showed a lack of metric knowledge—they overestimated mean and range—but acceptable mapping knowledge (i.e., relative ordering) of sugar content. The seeding intervention improved both types of knowledge, with and without additional visualization. General Audience Summary: Sugar overconsumption is associated with an increased risk of various health issues, including obesity and dental caries. For people to make healthy food choices, they need to possess some knowledge about sugar; for instance, how much sugar is contained in a food item or whether a food item contains more or less sugar than another item. Here, we ask two questions: (a) Do people give accurate "ballpark estimates" of sugar content of food (metric knowledge) and do they accurately rank food items according to their sugar content (mapping knowledge)? (b) Can both types of knowledge be improved with a simple seeding procedure, in which the actual sugar content is provided for a few typical items? In an online experiment, participants (N = 160) estimated the sugar content of various food items (in grams). Then, they received feedback about the actual content for a few typical seed items, with or without additionally seeing the corresponding number of sugar cubes; a control group received no feedback. Finally, they estimated again the sugar content of (seeded and unseeded) items. The results showed that participants overestimated how much sugar is, on average, contained in food items, but acceptably ordered items according to their sugar content. That is, their metric knowledge revealed more room for improvement than their mapping knowledge. Further, the seeding procedure considerably improved both types of knowledge and this was irrespective of whether participants additionally saw the corresponding number of sugar cubes or not. Our results imply that a simple, short, and cheap procedure can improve people's knowledge about sugar. Future research should address the relationship between knowledge and behavior: If people overestimate the sugar content of food, why do they consume too much of it? Does the seeding procedure also affect people's food choices? [ABSTRACT FROM AUTHOR]

A major problem in the cultivation of sugar beet is continuous cropping cycle. A study was carried out in the 2019–2021 season at the Agriculture and Forestry Sciences of Ulanqab, Inner Mongolia, to assess the impacts on the growth, root yield, and sugar content of sugar beet of various continuous cropping years with bio–organic fertilizers. A split plot system with three replications was set up to carry out the field testing. The main plots had five planting years, with the non-continuous of each growing season serving as the control (CK) and continuous cropping for one, two, three, and four years (designated as C1, C2, C3, and C4, respectively). The subplots had two bio-organic fertilizer levels: 6000 kg ha−2 (Y) and 0 (N). The results demonstrated that continuous cropping stunted sugar beet growth and lowered yield and quality. The plant height, leaf area index, root volume, root yield, and sugar yield of sugar beet significantly decreased with the extension of continuous cropping years. Compared with CKN (CKY), plant height, leaf area index, root volume, and fresh weight of C1N (C1Y), C2N (C2Y), C3N (C3Y), and C4N (C4Y) all showed a significantly decreased trend. Furthermore, the plant height, leaf area index, root volume, and fresh weight reductions had amplitudes of 5.60–27.36%, 9.53–67.86%, 17.71–57.35%, and 17.54–45.03%, respectively. The distinctions between C1 and C2 were essentially not statistically significant, and the same was evident for C3 and C4. The root yield and sugar yield exhibit noteworthy relationships with each growth indices. Compared with CKN (CKY), C1N, C2N, C3N, and C4N significantly reduced their root yield and sugar yield by 19.20% and 25.08% (19.63% and 25.67%), 24.13% and 31.02% (24.74% and 32.32%), 44.03% and 55.15% (48.47% and 58.09%), and 47.89% and 61.85% (52.35% and 64.43%). Bio-organic fertilizers applied during the same planting year all had effects on the growth and yield of sugar beet; however, these effects were only significant under the planting year treatments of CK, C1, and C2. The amplitude of the increase in plant height, leaf area index, root volume, fresh weight, and root yield reached 2.76–7.95%, 10.21–24.67%, 10.66–14.88%, 7.03–14.83%, and 18.74–19.69%, respectively. Above all, sugar beet were hindered by continuous cropping, and bio-organic fertilizer can greatly increase sugar beet yield and growth for continuous cropping lasting one or two years; for continuous cropping lasting three or more years, additional measures should be considered. [ABSTRACT FROM AUTHOR]

Aphanomyces cochlioides and Rhizoctonia solani are two of the main soil phytopathogens of sugar beet, which lead to substantial losses in yield and quality. Since disease control capabilities are complex and pathogen monitoring is important for predicting risks, it is of great importance in rural production to create available methods for preliminary field assessment. The purpose of the study was to introduce a predictive methodology for assessing the potential of soils for their suitability for growing sugar beet in the system of short-rotation crop rotations. As an indicator plant, sugar beet seeds were used, which are not characterised by genetic resistance against these diseases. The possibility of using the pre-growing disease index (PPDI), which has a gradation from 0 to 100 and covariance with the actual yield, sugar content and gross sugar yield per hectare, is tested. The pre-sowing PPDI value is compared with the actual yield from each specific field to really assess the possibility of using the PPDI index to characterise yield losses on production crops. It is determined that with an increase in the PPDI value, the gross yield of sugar beet, sugar content, and gross sugar yield decreased. The results of studies show that one unit of PPDI causes a loss of gross yield at the level of 0.24 t/ha and a decrease in the sugar harvest by 0.018 t/ha. That is why, to manage the risks of growing sugar beet, it is necessary to assess the phytopathogenic load of the soil. It is established that the most harmful and permanently identified phytopathogens are Rhizoctonia solani and Fusarium ssp, which indicates the need to select hybrids that are characterised by resistance or high tolerance to these pathogens. The information obtained can be used for timely identification of infection risks, development of effective management strategies, and improvement of agricultural techniques for growing sugar beet to reduce crop losses and increase the efficiency of agricultural products

A small-plot field experiment with sugar beet (Beta vulgaris provar. altissima Doell.) was focused on the monitoring of year weather conditions, selected genotypes and stimulating substances on the formation of quantitative and qualitative parameters. The experiment was carried out in the Center for Plant Biology and Ecology in Nitra during the years 2021 – 2022. The area is located at an altitude of 170 – 175 m above sea level in a corn production area with warm and dry climatic characteristics. The results of the experiment confirmed a statistically proven effect of the year conditions (P < 0.01) on the formation of quantitative and qualitative production parameters. In the range of monitored factors, agro-ecological conditions were more favourable in 2021, when a statistically higher root yield of 68.99 t/ha (+9.68 t/ha; rel. 16.32%) also sugar content of 16.75% (+0.68%; rel. 4.21%) were recorded. The statistical analysis confirmed a highly significant relationship (P < 0.01) between selected varieties and quantitative or qualitative production parameters. In the range of monitored genotypes, the highest root yield was recorded by Darvas 65.83 t/ha (+1.68 t/ha; rel. 2.62%) and the highest sugar content was indicated by Okapi 16.59% (+0.18%; rel. 1.11%). Implementation of stimulating substances with adaptogens positively affects the yield and sugar content of sugar beet. Stimulating preparations statistically affect (P < 0.01) the formation of monitored production parameters. The highest root yield of 67.40 t/ha (+7.56 t/ha; rel. 12.64%) and sugar content of 16.58% (+0.47%; rel. 2,91%) was indicated by variant 2 (Energeen Cleanstorm).

To explore the impact of shade treatment on grape berries, 'Marselan' grape berries were bagged under different light transmission rates (100% (CK), 75% (A), 50% (B), 25% (C), 0% (D)). It was observed that this treatment delayed the ripening of the grape berries. The individual weight of the grape berries, as well as the content of fructose, glucose, soluble sugars, and organic acids in the berries, was measured at 90, 100, and 125 days after flowering (DAF90, DAF100, DAF125). The results revealed that shading treatment reduced the sugar content in grape berries; the levels of fructose and glucose were higher in the CK treatment compared to the other treatments, and they increased with the duration of the shading treatment. Conversely, the sucrose content exhibited the opposite trend. Additionally, as the weight of the grape berries increased, the content of soluble solids and soluble sugars in the berries also increased, while the titratable acidity decreased. Furthermore, 16 differentially expressed genes (DEGs) were identified in the photosynthesis-antenna protein pathway from the transcriptome sequencing data. Correlation analysis revealed that the expression levels of genes VIT_08s0007g02190 (Lhcb4) and VIT_15s0024g00040 (Lhca3) were positively correlated with sugar content in the berries at DAF100, but negatively correlated at DAF125. qRT-PCR results confirmed the correlation analysis. This indicates that shading grape clusters inhibits the expression of genes in the photosynthesis-antenna protein pathway in the grape berries, leading to a decrease in sugar content. This finding contributes to a deeper understanding of the impact mechanisms of grape cluster shading on berry quality, providing important scientific grounds for improving grape berry quality. [ABSTRACT FROM AUTHOR]

Sugar content is an essential indicator for evaluating crisp pear quality and categorization, being used for fruit quality identification and market sales prediction. In this study, we paired a support vector machine (SVM) algorithm with genetic algorithm optimization to reliably estimate the sugar content in crisp pears. We evaluated the spectral data and actual sugar content in crisp pears, then applied three preprocessing methods to the spectral data: standard normal variable transformation (SNV), multivariate scattering correction (MSC), and convolution smoothing (SG). Support vector regression (SVR) models were built using processing approaches. According to the findings, the SVM model preprocessed with convolution smoothing (SG) was the most accurate, with a correlation coefficient 0.0742 higher than that of the raw spectral data. Based on this finding, we used competitive adaptive reweighting (CARS) and the continuous projection algorithm (SPA) to select key representative wavelengths from the spectral data. Finally, we used the retrieved characteristic wavelength data to create a support vector machine model (GASVR) that was genetically tuned. The correlation coefficient of the SG–GASVR model in the prediction set was higher by 0.0321 and the root mean square prediction error (RMSEP) was lower by 0.0267 compared with those of the SG–SVR model. The SG–CARS–GASVR model had the highest correlation coefficient, at 0.8992. In conclusion, the developed SG–CARS–GASVR model provides a reliable method for detecting the sugar content in crisp pear using hyperspectral technology, thereby increasing the accuracy and efficiency of the quality assessment of crisp pear. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine the content of certain phenolic compounds, antioxidant activity, pressing efficiency, extract content, and sugars in celeriac juices obtained from the pulp after α-amylase treatment from Aspergillus oryzae. The test material consisted of peeled and unpeeled celery pulp kept at a temperature of 25 °C with and without the enzyme for a period of 30 and 60 min. The juices obtained from them were analyzed for the content of selected phenolic acids and flavonoids using the UPLC-PDA-ESI-MS/MS method, for antioxidant activity measured using the ABTS˙+ and DPPH˙ method, and for the total polyphenol content using the F-C method. Additionally, the juice pressing efficiency, the extract content using the refractometer method, and the sugar content using the HPLC method were checked. Significantly higher antioxidant activity, pressing yield, and average content of caffeic acid glucoside, quinic acid, kaempferol-3,7-di-O-glucoside, and chrysoeriol-7-O-apiosylglucoside were obtained in juices from peeled celery. Maceration of the pulp with amylase resulted in a significant reduction in antioxidant activity compared to control samples. An is-total increase of 17–41% in total flavonoid content was observed in all juices tested after treatment with the enzyme for 30 and 60 min, and the phenolic acid content increased by 4–41% after treatment of the pulp with amylase for 60 min. The 60 min holding of the pulp at 25 °C, including with the enzyme, was shown to decrease the antioxidant activity and the content of quinic acid, ferulic acid, and chrysoriol-7-O-apiose-glucoside in the juices tested compared to the samples held for 30 min, while the content of other phenolic acids and flavonoids increased. In addition, after 60 min of enzymatic maceration, the pressing yield of the juices increased. [ABSTRACT FROM AUTHOR]

Sugar content is a critical factor in evaluating the quality of fresh peaches. This paper aims to develop a rapid and accurate prediction method for the sugar content of fresh peaches using Deep Learning combined with near-infrared spectroscopy (NIRS). The proposed model consists of three main steps. Firstly, the Multivariate Scattering Correction (MSC) is employed as a preprocessing technique to remove noise and redundant information from the raw NIR images of peaches which ensures the reliability of the subsequent analysis. Secondly, the Competitive Adaptive Reweighted Sampling (CARS) is utilized for bands selection which can effectively eliminate redundant information from the NIR spectral data and reduces computational complexity. Finally, a novel Linear Deep Belief Network (LDBN) model is constructed to predict the sugar content of fresh peaches. To validate the performance of the proposed method, a Fresh Peaches Near-infrared spectroscopy dataset (FPNIRS) containing sugar content information is constructed. The maximum value for the sugar content of fresh peaches was 13.4 and the minimum value was 7.5 in the collection of 180 fresh peach samples. The experimental results demonstrate that the proposed LDBN achieves the best prediction performance, with the determination coefficient of prediction set ( R P 2 ) value of 0.9346 and the root mean square error of prediction set (RMSEP) value of 0.4409. This study suggests that the combination of Near-infrared spectroscopy technology and the LDBN provides an effective method for accurately predicting the sugar content of fresh peaches. [ABSTRACT FROM AUTHOR]

Aphanomyces cochlioides and Rhizoctonia solani are two of the main soil phytopathogens of sugar beet, which lead to substantial losses in yield and quality. Since disease control capabilities are complex and pathogen monitoring is important for predicting risks, it is of great importance in rural production to create available methods for preliminary field assessment. The purpose of the study was to introduce a predictive methodology for assessing the potential of soils for their suitability for growing sugar beet in the system of short-rotation crop rotations. As an indicator plant, sugar beet seeds were used, which are not characterised by genetic resistance against these diseases. The possibility of using the pre-growing disease index (PPDI), which has a gradation from 0 to 100 and covariance with the actual yield, sugar content and gross sugar yield per hectare, is tested. The presowing PPDI value is compared with the actual yield from each specific field to really assess the possibility of using the PPDI index to characterise yield losses on production crops. It is determined that with an increase in the PPDI value, the gross yield of sugar beet, sugar content, and gross sugar yield decreased. The results of studies show that one unit of PPDI causes a loss of gross yield at the level of 0.24 t/ha and a decrease in the sugar harvest by 0.018 t/ha. That is why, to manage the risks of growing sugar beet, it is necessary to assess the phytopathogenic load of the soil. It is established that the most harmful and permanently identified phytopathogens are Rhizoctonia solani and Fusarium ssp, which indicates the need to select hybrids that are characterised by resistance or high tolerance to these pathogens. The information obtained can be used for timely identification of infection risks, development of effective management strategies, and improvement of agricultural techniques for growing sugar beet to reduce crop losses and increase the efficiency of agricultural products. [ABSTRACT FROM AUTHOR]

Royal jelly is a secretion produced from the hypopharyngeal glands of worker bees, which requires significant pollen reserves to stimulate gland secretion. The natural sources of food available to the hive during beekeeping season can greatly affect the quantity and quality of produced royal jelly. In this study, samples of royal jelly were collected throughout the beekeeping season, and their physical and chemical characteristics were analyzed to understand how natural variations in bee diet affect royal jelly production. Before each sample collection, the bees' food reserves were removed from the experimental colonies so that the royal jelly was produced solely from natural sources. The results showed that the production was significantly lower during the summer months compared with spring and autumn. Additionally, the moisture, protein, fructose, and glucose content of fresh royal jelly also showed significant changes in the summer, and all physical and chemical characteristics decreased when the fresh samples were converted into dry matter. It seems that the quality of pollen entering the hives has a direct impact on the physical and chemical properties of the final product, highlighting the crucial role of available resources in stimulating bees to produce royal jelly. [ABSTRACT FROM AUTHOR]

Grapes are a globally important fruit with significant economic value, influenced by factors such as sugar content, organic acids, hormones, and antioxidants. Understanding the dynamics of these compounds during grape development and ripening is critical for optimizing berry quality and production. This study investigates the changes in sugar, organic acids, hormones, and antioxidants in two grape varieties, 'Italia' and 'Bronx Seedless', at various growth stages (BBCH-77, BBCH-79, BBCH-81, BBCH-83, BBCH-85, and BBCH-89). Regarding sugars, significant variations were observed due to grapevine cultivar and phenological stage. 'Bronx Seedless' grapes consistently displayed lower sugar content than 'Italia' grapes, regardless of the type of sugar being examined. The BBCH-77 stage consistently exhibited lower sugar levels compared to BBCH-89. The varieties 'Bronx Seedless' and 'Italia' exhibited distinct nutritional profiles, each with their unique advantages in terms of sugar content and organic acid composition. Both varieties were rich in the primary sugar glucose and fructose, with 'Bronx Seedless' displaying notably high levels of the beneficial tartaric acid, enhancing its nutritional value. On the other hand, 'Italia' stood out for its higher concentrations of fumaric, butyric, and oxalic acids, contributing to its unique taste and health benefits. Throughout their growth stages from BBCH-77 to BBCH-89, an increase in organic acid levels was observed, peaking at the BBCH-85 stage, except for maleic acid. In terms of hormonal content, 'Italia' exhibited higher levels compared to 'Bronx Seedless'. The predominant hormone, abscisic acid (ABA), alongside lower quantities of zeatin, indicated a strong physiological response to environmental and developmental cues in both varieties, with hormone levels increasing as the grapes approached maturity. Antioxidant profiles also varied between the two varieties, with 'Italia' consistently showing higher antioxidant levels than 'Bronx Seedless'. Antioxidant levels consistently increased from BBCH-77 to BBCH-89. This comprehensive analysis contributes to our understanding of the complex processes underlying grape berry development and ripening, with potential implications for enhancing grape quality and refining production strategies. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agricultural Science & Sustainable Production is the property of University of Tabriz and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: Addressing the issues of poor accuracy and low efficiency in non-destructive testing methods for kiwifruit sugar content. Methods: Proposing a non-destructive testing method for kiwifruit sugar content that combined hyperspectral detection technology, least squares support vector machine, and improved whale algorithm. By collecting hyperspectral information of kiwifruit through a hyperspectral detection system, after preprocessing and feature wavelength screening, and then input into an improved whale algorithm optimized least squares support vector machine model to achieve rapid and non-destructive detection of kiwifruit sugar content, and verify its performance. Results: The proposed method could achieve rapid and non-destructive detection of kiwifruit sugar content, with a determination coefficient of 0.965 2 for the test set, a root mean square error of 0.880 5 for the test set, and an average detection time of 1.06 seconds. Conclusion: Combining machine learning algorithms with hyperspectral detection technology can achieve rapid and non-destructive detection of kiwifruit sugar content.

Sweet sorghum is the potential in Indonesia to be used as a fermentation medium for glutamic acid production. The sorghum plant resembles sugar cane which has sap in the stem. Sorghum is a plant with high sugar content and high biomass productivity. The high sugar content in sorghum sap is known from the total dissolved solids. The evaporation process on sorghum juice increases the sugar content and can inactivate microbial activity. Glutamic acid fermentation needs a substrate source derived from sugar for the growth of the producing microbes. Therefore, this study aims to describe the sugar content in sorghum juice before and after the evaporation process so that it can be used as a substrate source for glutamic acid production. This research was carried out using the evaporation method of sorghum juice for 15 minutes at a temperature of 85 - 100 oC, so a concentrated sorghum sap was obtained. The analysis was pH, total dissolved solids (oBrix) using a refractometer, and reducing sugar content using the DNS method. The results obtained in this study indicated a significant increase in the quality and sugar content of sorghum sap with a pH of 4.81 ± 0.01 to 5.55 ± 0.03, total dissolved solids from 10.44 ± 0.09 to 34.80 ± 0.02 (oBrix), and reduced sugar content from 114.10 ± 0.45 to 271.74 ± 0.26 g/l. The sugar content allows sorghum juice to be used as raw material in industrial microbiology, especially for the production of glutamic acid.

Taraxacum kok-saghyz (TKS) is one of the most promising rubber plants in the world. The question of how irrigation affects its yields and biochemical composition has not yet been studied well. The effects of irrigation frequency on the growth and yield of Taraxacum kok-saghyz were analyzed. According to the obtained results, it was established that an increase in irrigation frequency (extension of the watering interval) gradually decreased TKS rubber and total sugar yields. With the soil water content increasing from 22.8 to 38.9%, TKS rubber and sugar yields were changing in line with a cubic polynomial equation. Regular watering once every 6 days maintains soil moisture at a level above 28.0%, which makes it possible to increase the yield of Taraxacum kok-saghyz while enhancing the water-use efficiency under the conditions of Northeastern China (Harbin).

Wine is a product of human creativity, culture, and nature, and therefore it is an intriguing subject for scientific research and admiration. Among its many kinds, white wine stands out oenologically because of its diverse flavours, aromatic attributes, and capacity to mature. In this experiment, we established 3 different bud load levels (25%, 50%, and 75%) on the well-known white wine grape variety ‘Fetească Albă’. The sugar content significantly increased in the 50% and 76% groups, whereas there were no significant changes regarding titratable acid content, must quantity, and cluster weight.

Featured Application: In this study, we introduce an approach for quickly profiling the nutritional content of fruit juices by using a portable Fourier transform mid-infrared (FT-IR) device. This method enables real-time prediction and simultaneous analysis of key components, such as sugars and acids in fruit juices, addressing concerns about obesity and other health risks. The portability of the FT-IR sensor makes it a valuable tool for food processors, providing a convenient out-of-the-laboratory solution. This application detects deviations in sugar and ascorbic acid levels compared to nutritional labels, helping consumers to make healthier decisions. Furthermore, applying portable FT-IR devices by the fruit juice industry will streamline quality control processes and represents a shift towards more efficient, non-destructive, and high-throughput analytical methods. Fruit juices (FJ) have gained widespread global consumption, driven by their perceived health benefits. The accuracy of nutrition information is essential for consumers assessing FJ quality, especially with increasing concerns about added sugars and obesity risk. Conversely, ascorbic acid (Vitamin C), found in nature in many fruits and vegetables, is often lost due to its susceptibility to light, air, and heat, and it undergoes fortification during FJ production. Current analytical methods for determining FJ components are time-consuming and labor-intensive, prompting the need for rapid analytical tools. This study employed a field-deployable portable FT-IR device, requiring no sample preparation, to simultaneously predict multiple quality traits in 68 FJ samples from US markets. Using partial least square regression (PLSR) models, a strong correlation (RCV ≥ 0.93) between FT-IR predictions and reference values was obtained, with a low standard error of prediction. Remarkably, 21% and 37% of FJs deviated from nutrition label values for sugars and ascorbic acid, respectively. Portable FT-IR devices offer non-destructive, simultaneous, simple, and high-throughput approaches for chemical profiling and real-time prediction of sugars and acid levels in FJs. Their handiness and ruggedness can provide food processors with a valuable "out-of-the-laboratory" analytical tool. [ABSTRACT FROM AUTHOR]

Kiwiberry (Actinidia arguta) is a perennial fruit tree belonging to the family Actinidiaceae. Kiwiberries are known to have an extremely high concentration of sugars, phenolics, flavonoids, and vitamin C, and possess delicious taste and health-promoting properties. Numerous studies have focused on kiwiberry fruits, demonstrating that they possess a higher phytochemical content and greater antioxidant activities than other berry fruits. The purpose of this study was to compare the phytochemical content and antioxidant potential of leaf, stem, root, and fruit extracts from twelve kiwiberry cultivars grown in Wonju, Korea, characterized by a Dwa climate (Köppen climate classification). In most kiwiberry cultivars, the total phenolic (TPC) and total flavonoid (TFC) phytochemical content was significantly higher in leaf and stem tissues, while the roots exhibited higher antioxidant activity. In fruit tissues, the TPC and TFC were higher in unripe and ripe kiwiberry fruits, respectively, and antioxidant activity was generally higher in unripe than ripe fruit across most of the cultivars. Based on our results, among the 12 kiwiberry cultivars, cv. Daebo and cv. Saehan have a significantly higher phytochemical content and antioxidant activity in all of the tissue types, thus having potential as a functional food and natural antioxidant. [ABSTRACT FROM AUTHOR]

Copyright of Listy Cukrovarnicke a Reparske is the property of VUC Praha a.s. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The growing beekeeping industry in South Korea has led to the establishment of new honey plant complexes. However, studies on honey production from each species are limited. This study aimed to assess the honey production potential of various Brassica napus cultivars and two wildflower species. The nectar characteristics of B. napus varied significantly among the cultivars. Absolute sugar concentrations differed among the cultivars, but sugar composition ratios were similar. In contrast, the amino acid content remained relatively uniform regarding percentage values, irrespective of the absolute concentrations. Estimations of honey potential production per hectare (kg/ha) resulted in the following ranking among cultivars: 'JM7003' (107.1) > 'YS' (73.0) > 'JM7001' (63.7) > 'TL' (52.7) > 'TM' (42.4). The nectar volume of Pseudolysimachion rotundum var. subintegrum and Leonurus japonicus increased during the flowering stage. P. rotundum var. subintegrum was sucrose-rich and L. japonicus was sucrose-dominant. Both species predominantly contained phenylalanine, P. rotundum var. subintegrum had glutamine as the second most abundant amino acid, and L. japonicus had tyrosine. The honey production potential was 152.4 kg/ha for P. rotundum var. subintegrum and 151.3 kg/ha for L. japonicus. These findings provide a basis for identifying food resources for pollinators and selecting plant species to establish honey plant complexes. [ABSTRACT FROM AUTHOR]

The tomato (Solanum lycopersicum L.) is a very valuable horticultural crop that is produced all over the world and has a significant economic impact in Asia. Several biotic and abiotic stresses (soil-borne and foliar diseases, insect pests, drought, salt, heat, and frost) severely damage the crop, however, pose a serious threat to its output. As a result, it's crucial to make efforts to introduce valuable resistance genes into tomato from their wild relatives. This study analyzed the growth of inter and intra- specific tomato hybrids to determine the high-quality hybrids. By crossing wild (S. pimpinellifolium PI1, PI4) and domesticated tomato (S. Lycopersicum LY13, LY4, LY26, LY9, and LY11) and S. Lycopersicum cv micro-tom LY15) species, hybrids of tomato plants produced by interspecific. For morphological characteristics, the fruit weight of tomato hybrids results intermediate among prenatal lines. Results towards number of fruits per turs also show intermediate findings but LY13 X PI4 show lesser number of fruits per truss in hybrids on the same hand LY15 XLY4 show high yield and maximum number of fruits as compared to parents. Despite of fact that the wild parent male had a strong influence on hybrids for numerous morphological traits like fruit set per truss, fruit diameter, leaf length, and fruit yield. After crossing with wild cultivars, F1 tomato hybrids also had biochemical traits in reducing sugar, non-reducing sugar, total sugar, total soluble solids, and lycopene, which were improved in cultivated tomato. The wild type of tomato played a significant part in raising the lycopene content in hybrids. Therefore, it is considered that this research would expand the gene pool available for tomato breeding globally, enabling it to better adapt to climate change and withstand biotic and abiotic stress. [ABSTRACT FROM AUTHOR]

Copyright of Listy Cukrovarnicke a Reparske is the property of VUC Praha a.s. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Central European Agriculture is the property of Journal of Central European Agriculture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

One of the best sources of antioxidant and health-promoting bioactive substances is the fruit of V. corymbosum. A potent oxidizing agent, ozone (O3), can effectively eliminate bacteria. The application of ozone gas to V. corymbosum fruit during storage had a favorable impact on the fruit's phenolic component and sugar content in the current investigation. After 7 days of storage, phenolic content in all highbush blueberry cultivars and clones tested increased on average by 28.60%, including anthocyanins by 34%. After 14 days of storage, an average increase of 16.50% in phenolic compounds was observed, including a 20.53% increase in anthocyanins. Among all the tested varieties, clone BOR-21 treated with a dose of 0.01 mL·L−1 ozone for 30 min after 14 days had the highest TPC—143.73 mg·100 g−1 f.w. The sugar content of berries treated with a dose of 0.01 mL·L−1 ozone for 30 min, on day 7 and day 14 of storage increased by 9.2% and 6.3%, respectively. On day 7, the highest amount of total sugar (22.74 g·100 g−1) was observed in Duke cultivar after being exposed to 0.01 mL·L−1 ozone for 15 min. The ozonation treatments enhanced the fruit's saturation with nutrients, which raises the fruit's value as food. [ABSTRACT FROM AUTHOR]

Objective: To solve the problem of insufficient spectral information obtained by the fixed illumination angle of the near-infrared spectroscopy to detect the sugar content of fruits. Methods: A light angle adjustable device for the diffuse transmission near-infrared spectroscopy was designed to detect the sugar content of citrus based on the simplified model of the remote motion center of the light source. The device had carried out the structural performance analysis and the test of the citrus sugar under different illumination angles. Results: The adjustment range of the light angle of the device was set to 0°~60°. The displacement deviation between the center of the four light sources and the bullseye was the smallest （7.5 mm） at 60°. Under different illumination angles, the error between the average illumination angle of light source 2, 3 and 4 and the reference value of light source 1 was within 1°. When the illumination angle was 30°, the citrus sugar prediction model based on the original transmittance spectrum data had the best effect. At this time, the correlation coefficient of the prediction set, the root mean square error of the prediction set, the correlation coefficient of the correction set, and the root mean square error of the correction set were 0.887 6, 0.897 5, 0.456 0, 0.430 9 °Brix, respectively. Conclusion: The developed near-infrared spectroscopy detection device can automatically synchronize and adjust the angle of illumination of four light sources to align with the center of the fruit.

The traditional method for determining wine grape total soluble solid (TSS) is destructive laboratory analysis, which is time consuming and expensive. In this study, we explore the potential of using different predictor variables from various advanced techniques to predict the grape TSS in a non-destructive and rapid way. Calculating Pearson's correlation coefficient between the vegetation indices (VIs) obtained from UAV multispectral imagery and grape TSS resulted in a strong correlation between OSAVI and grape TSS with a coefficient of 0.64. Additionally, seven machine learning models including ridge regression and lasso regression, k-Nearest neighbor (KNN), support vector regression (SVR), random forest regression (RFR), extreme gradient boosting (XGBoost), and artificial neural network (ANN) are used to build the prediction models. The predictor variables include the unmanned aerial vehicles (UAV) derived VIs, and other ancillary variables including normalized difference vegetation index (NDVI_proximal) and soil electrical conductivity (ECa) measured by proximal sensors, elevation, slope, trunk circumference, and day of the year for each sampling date. When using 23 VIs and other ancillary variables as input variables, the results show that ensemble learning models (RFR, and XGBoost) outperform other regression models when predicting grape TSS, with the average of root mean square error (RMSE) of 1.19 and 1.2 °Brix, and coefficient of determination (R2) of 0.52 and 0.52, respectively, during the 20 times testing process. In addition, this study examines the prediction performance of using optimized soil adjusted vegetation index (OSAVI) or normalized green-blue difference index (NGBDI) as the main input for different machine learning models with other ancillary variables. When using OSAVI-based models, the best prediction model is RFR with an average R2 of 0.51 and RMSE of 1.19 °Brix, respectively. For NGBDI-based model, the RFR model showed the best average result of predicting TSS were a R2 of 0.54 and a RMSE of 1.16 °Brix, respectively. The approach proposed in this study provides an opportunity to grape growers to estimate the whole vineyard grape TSS in a non-destructive way. [ABSTRACT FROM AUTHOR]

Sugarcane (Saccharum spp.) is a widely cultivated crop that fulfils approximately 75% of the sucrose demand worldwide. Owing to its polyploidy and complex genetic nature, it is difficult to identify and map genes related to complex traits, such as sucrose content. However, association mapping is one of the alternatives for identifying genes or markers for marker-assisted selection. In the present study, EST-SSR primers were obtained from in silico studies. The functionality of each primer was tested using Blast2Go software, and 30 EST-SSR primers related to sugar content were selected. These markers were validated using association analysis. A total of 70 F1 diverse genotypes for sugar content were phenotypes with two check lines. All parameters related to sugar content were recorded. The results showed a significant variation between the genotypes for sugar yield traits such as Brix value, purity, and sucrose content, etc. Correlation studies revealed that the Brix%, sucrose content, and sucrose recovery were significantly correlated. An association analysis was performed using mixed linear model to avoid false positive associations. The association analysis revealed that the SEM 407 marker was significantly associated with Brix% and sucrose content. The SEM 407 primers are putatively related to diphosphate-fructose-6-phosphate 1-phosphotransferase which is associated with Brix% and sucrose content. This functional marker can be used for marker-assisted selection for sugar yield traits in sugarcane that could accelerate the sugarcane breeding program. [ABSTRACT FROM AUTHOR]

Accurately estimating crop performance under various fertilizer levels in a rapid and non-destructive manner has become a vital aspect of precision agriculture technology for both economic and environmental benefits. This study aimed to estimate different sugar beet parameters, such as total chlorophyll (Chlt), chlorophyll a (Chla), chlorophyll b (Chlb), root yield (RY), sugar yield (SY), and sugar content (SC) under five nitrogen (N) levels (0, 30, 60, 90, and 120 kg N ha−1). This was achieved by using a combination of the gradient boosting regression (GBR) model with published and newly developed two- and three-band spectral indices (2D- and 3D-SRIs). The results showed that the N levels had the highest proportion of variations (80.4–92.9%) for all parameters, except for SC, which had more variation (59.9%) according to year than the N levels (37.2%). All parameters, except SC, showed a significant increase with gradually increasing N levels. Additionally, the N levels displayed linear and strong positive relationships with the chlorophyll parameters, and linear and strong negative relationships with SC, while these relationships were quadratic and strong with RY and SY. Several published and novel 3D-SRIs exhibited moderate to strong relationships (R2 = 0.65–0.89) with all parameters. The newly developed 3D-SRIs, which involve wavelengths from the visible, near-infrared, and red-edge regions, such as NDI536, 538, 534, NDI738, 750, 542, and NDI448, 734, 398, were effective in accurately estimating all parameters. Combining 2D-SRIs, 3D-SRIs, and the aggregate of all spectral indices (ASRIs) with GBR models could be a robust strategy for estimating the six observed parameters with reasonable precision. The GBR-ASF-6 SRIs and the GBR-ASF-7 SRIs models performed better in predicting Chl content and SC with R2 values of 0.99 and 0.99 (RMSE = 0.073 and 1.568) for the training dataset and R2 values of 0.65 and 0.78 (RMSE = 0.354 and 6.294) for the testing datasets, respectively. The obtained results concluded that published and newly developed 3D-SRIs, GBR based on 2D-SRIs or 3D-SRIs, and the aggregate of all ASRIs can be used in practice to accurately estimate the Chl content, production, and quality of sugar beet across a wide range of N levels under semiarid conditions. [ABSTRACT FROM AUTHOR]

Sustainable and efficient agricultural production is a growing priority in modern society. Viticulture, an important agricultural and food sector, also faces this challenge. Precision Viticulture (PV) has gained prominence as it aims to foster high-quality, efficient, and environmentally sustainable practices. The Soluble Solids Content (SSC) is essential for assessing grape ripeness and quality in the winemaking process. Conventional methods for determining SSC values (expressed in °Brix) are invasive, expensive, and labour-intensive, necessitating sample preparation, making large-scale analysis impractical. In response to these limitations, this study presents an innovative approach within the field of Precision Viticulture. It focuses on the non-invasive prediction of SSC using low-cost proximal hyperspectral optical sensors. These sensors rely on spectral reflectance measurements in the range of 340–850 nm. This study was conducted in a commercial vineyard in the Demarcated Douro Region, Cima-Corgo sub-region, Portugal, over six weeks during ripening. In total, 169 grape berries from Touriga Nacional vines were analysed under three irrigation regimes (no irrigation, 30% ETc, and 60% ETc). After organising and preprocessing the data, machine learning algorithms, namely Partial Least Squares Regression (PLS), Random Forest (RF), and the Generalised Linear Model (GLM), were applied to predict SSC values. These models' performance was thoroughly evaluated using cross-validation techniques. The performance of different models was evaluated, showing significant differences according to the metrics used (R2, RMSE, and MAPE). The RF model demonstrated effectiveness and precision. A high R² value of 0.9312, coupled with low RMSE (0.9199 °Brix) and MAPE (3.88%), signifies a strong fit to the data and accurate predictive capabilities. The results of this benchmarking study on predictive models of SSC provide valuable insights into the performance of various models, aiding winegrowers and winemakers in decision making. [ABSTRACT FROM AUTHOR]

Copyright of Xinjiang Agricultural Sciences is the property of Xinjiang Agricultural Sciences Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The overall yield and sugar content of sugar beet (Beta vulgaris L.) were determined by the genotype and its interaction with the environment. This study aimed to analyze the interaction of 23 genotypes with different environmental conditions during two growing seasons. To estimate the variance of genotypes, environment, and genotype function of the environment, the R 3.5.1 software package was used. In addition, the multivariate stability method was used to explain the G (genotype) × E (environment) interaction based on the GGE (Genotype plus Genotype-by-Environment) and AMMI (additive main effects and multiplicative interaction) biplots. The AMMI ASV (AMMI stability value) and biplot analysis revealed that only two genotypes (G10 and G11) showed higher values for yield and sugar content and production compared to the other genotypes. The AMMI ASV analysis also showed that the environment significantly influenced the sugar beet yield, sugar content, and sugar production, which were the descriptors for production in this study. [ABSTRACT FROM AUTHOR]

Hybrids with heterotic effects manifest themselves with a significant enhancement in growth and productivity traits compared with their parental genotypes. However, inbreeding resulted in decreased heterosis. Researchers believe that a noteworthy increase in F1 hybrids for economic and biological attributes is evident due to heterozygosity and overdominance of the corresponding genes of different parents combined in one genotype. The presented study sought to determine the heterotic effects of sugar beet hybrids for economically valuable traits and select the best parental lines with crossing potential for productivity. Five different sugar beet hybrids, analyzed during the crop seasons 2021 and 2022 for accurate and hypothetical heterosis and the degree of dominance in F1 generation for economically valuable traits like productivity and sugar content, transpired at the LLP - Kazakh Research Institute of Agriculture and Plant Growing (KazRIAPG), Kazakhstan. The crossing of the sugar beet line KazMS with pollinators, viz., VP24, VP44, OP17231, OP17232, and OP14044, changed the type of inheritance in hybrids for productivity from negative dominance in variants with pollinators (VP24, OP17231) to overdominance in variants with pollinators (VP44, OP14044). Based on the results, the conclusion indicated that the type of productivity inheritance in F1 hybrids involving the same maternal line differed. [ABSTRACT FROM AUTHOR]

Introduction: Environmental factors affect the accumulation of sugar. Light, sunny hours and soil moisture largely determines how sugar is grown and stored at the root of sugar results of the experiment on sugar beet showed that all treatments of anti-stress materials such as salicylic acid, thioufol and glycine at different concentrations increased the quality traits such as root yield, sugar level and white sugar yield. Reducing membrane damage due to the use of salicylic acid is associated with the production of antioxidants, and thus salicylic acid increases the membrane stability against oxidative stress. Salicylic acid is an internal regulator of plant growth that affects metabolic and physiological responses to plant growth and development. Plants obtained from seeds pretreated with salicylic acid can improve the rate of photosynthesis in normal and stress conditions by increasing the relative water content, transpiration intensity, stomatal conductance and leaf chlorophyll index. In a study, it has been observed that salicylic acid treatment controls polysaccharide hydrolyzing enzymes and accelerates the formation of polysaccharides from soluble sugars. With this assumption, salicylic acid increases the amount of insoluble sugars compared to soluble sugars. Materials and Methods: In order to adjust the negative effects of drought stress in sugar beet cultivars under the influence of salicylic acid foliar spraying in drought stress conditions, a factorial split plot was used in a randomized complete block design with three replications in Jouin was conducted in 2019. The studied factors included irrigation at two levels of full irrigation and drought stress (50% of full irrigation), salicylic acid spraying at three levels of 0, 2.5 and 5 mM on the Shokofa (034) and Aria (031). Results and Discussion: Stress reduced the yield, but the use of salicylic acid increased the yield . Application of 5 mM produced the highest amount of root yield with 16.55. In the condition of full irrigation, the yield increased by increasing the amount of salicylic acid. In the stress conditions, the percentage of impure sugar increased, but in the condition of full irrigation, the percentage of impure sugar decreased, but with the use of five to 2.5 mM salicylic acid, it increased. In condition of drought stress and consumption, 2.5 mM of salicylic acid, 034, have the highest percent sugar content with 20.5%. The amount of proline of 034 cultivar was the highest in drought stress and consumption of 5 mM of salicylic acid. Consumption of salicylic acid increased root yield and sugar content yields and reduced harmful nitrogen and sodium. Drought stress caused a decrease in yield, and this decrease in yield was both qualitative and quantitative. Drought stress decreased sugar yield and root yield in sugar beet by increasing electrolyte leakage from cell membranes, decreasing relative leaf water content, and increasing harmful nitrogen. Conclusion: The amount of impure sugar (kg/m2) increased with the use of salicylic acid in both drought stress and complete irrigation. Impure sugar, which is the result of multiplying the sugar beet root yield by the percentage of impure sugar and has been affected by salicylic acid, shows that the quantity and quality of both have increased with the use of this hormone-like substance .In this study, salicylic acid was able to increase the absorption of water by increasing the proline and making the osmotic pressure of sugar beet negative by increasing the relative water content of the leaves, and finally, by increasing the impute sugar yield, it increased the root yield and sugar per unit area. The consumption of salicylic acid increased the root yield and sugar level and decreased harmful nitrogen, sodium and potassium. [ABSTRACT FROM AUTHOR]

This study aimed to determine the value of honey source on Robinia by analyzing flower morphology and nectar characteristics in floral nectar of eight selected individuals. The mean nectar volume secreted by genus Robinia was 1.7 ± 1.0 µL. Among the samples, PR (R. margaretta) and HR (R. pseudoacacia) secreted the highest and lowest nectar volumes—3.0 ± 1.1 and 1.1 ± 0.7 µL, respectively. The mean sugar concentration was 44.8 ± 6.1% (range, 40.1–51.4%). The ANOVA results revealed a statistically significant difference in nectar volume and sugar concentration among the eight individuals (p < 0.05). The free sugar content ranged from 0.39 (HR) to 0.78 (KR) mg/μL, and nectar sugar contents ranged from 0.31 (HR) to 1.53 (PR) mg per flower. The sucrose/hexose ratio ranged from 0.5 to 3.6, and sucrose was high in all samples. The results of the Kruskal-Wallis H test revealed significant differences in free sugar content (mg/µL), nectar sugar content per flower and sucrose/hexose ratio (p < 0.05). There were close correlations between nectar characteristics and flower morphology as followed; 1) nectar volume and nectar sugar content per flower (r = 0.976), 2) nectar volume and calyx length (r = 0.952), 3) sugar concentration in nectar and length of inflorescence (r = 0.952). Asparagine was the most abundant (average; 60.2%) amino acid, followed in decreasing order by alanine (6.9%), glutamine (5.2%), and serine (4.7%). The results of Kruskal-Wallis H tests showed that the rate of amino acids of alanine, glutamine, glutamic acid, and arginine significantly differed among the samples (p < 0.05). [ABSTRACT FROM AUTHOR]