Synergistic effect of seaweed extract and boric acid and/or calcium chloride on productivity and physico-chemical properties of Valencia orange.

Many citrus species and cultivars are grown successfully in tropical and subtropical countries, as well as in arid and semi-arid regions with low levels of organic matter and low cation exchange, resulting in lower nutrient uptake by the plant. The essential nutrients needed for citrus flowering and fruit set are limited in winter due to a reduction in transpiration rate, negatively effecting vegetative growth, flowering, yield, and fruit quality. The present investigation was carried out to assess the nutritional status, fruit yield parameters, and fruit quality of Valencia orange trees after foliar spraying of seaweed extract (SW) combined with calcium chloride and boric acid and their combinations in the 2020/2021 and 2021/2022 seasons. The treatments were arranged in a split-plot design (three levels spraying seaweed extract × four levels spraying calcium chloride and boric acid and their combinations × four replicates × one tree/replicate). The results indicated that all of the characteristics measured, including leaf chlorophyll, leaf mineral contents, fruit yield parameters, fruit physical properties, and fruit chemical properties, were significantly affected by the foliar spraying of seaweed extract (SW) combined with calcium chloride and boric acid and their combinations. Although all treatments increased the productivity and the physical and chemical properties of Valencia orange fruits compared to the control, a treatment of 10 g/L SW combined with 0.5 g/L boric acid and 1 g/L calcium chloride produced superior results. This ratio of SW, boric acid, and calcium chloride is therefore recommended to enhance productivity and improve the physico-chemical properties of Valencia orange for greater fruit yield.

Physico-Chemical Properties Prediction of Flame Seedless Grape Berries Using an Artificial Neural Network Model.

The grape is a very well-liked fruit that is valued for its distinct flavor and several health benefits, including antioxidants, anthocyanins, soluble sugars, minerals, phenolics, flavonoids, organic acids, and vitamins, which significantly improve the product's overall quality. Today's supply chain as a whole needs quick and easy methods for evaluating fruit quality. Thus, the objective of this study was to estimate the quality attributes of Flame Seedless grape berries cultivated under various agronomical management and other practices using color space coordinates (berry L*, berry a*, and berry b*) as inputs in an artificial neural network (ANN) model with the best topology of (3-20-11). Satisfactory predictions based on the R2 range, which was 0.9817 to 0.9983, were obtained for physical properties (i.e., berry weight, berry length, and berry diameter as well as berry adherence strength) and chemical properties (i.e., anthocyanin, total soluble solids (TSS), TSS/titratable acidity, total sugars, titratable acidity, reducing sugars, and non-reducing sugars). Meanwhile, we also performed a contribution analysis to analyze the relative importance of CIELab colorimeter parameters of berries L*, a*, and b* to determine the main fruit quality. In terms of relative contribution, berry b* contributed relatively largely to berry weight, berry adherence strength, TSS, TSS/titratable acidity, titratable acidity, total sugars, reducing sugars, and non-reducing sugars and a* contributed relatively largely to anthocyanin, berry length, and berry diameter. The developed ANN prediction model can aid growers in enhancing the quality of Flame Seedless grape berries by selecting suitable agronomical management and other practices to avoid potential quality issues that could affect consumers of them. This research demonstrated how color space coordinates and ANN model may well be utilized to evaluate the Flame seedless grape berries' quality.

Identification of Indian jujube varieties cultivated in Saudi Arabia using an artificial neural network.

This study aimed to develop a method for identifying different cultivars of Indian jujube fruits (Ziziphus mauritiana Lamk.) based on a single Indian jujube fruit color and morphological attributes using an artificial neural network (ANN) classifier. Eleven Indian jujube fruit cultivars were collected during winter of season 2020 from a local orchard located at Riyadh region, Saudi Arabia to measure their lengths, major diameters, and minor diameters. Different morphological descriptors were calculated, including the arithmetic mean diameter, the sphericity percent, and the surface area. Moreover, the color values of L*, a*, and b* of the skin of fruits were recorded. The ANN classifier was used to identify the appropriate class of Indian jujube fruit by using a combination of morphological and color descriptors. The proposed method achieved an overall identification rate of 98.39% and 97.56% in training and testing phases, respectively. In addition to color and morphological features, ANN classifier is a useful tool for identifying Indian jujube fruit cultivars and circumventing the difficulties met during fruit grading.

Development of an artificial neural network as a tool for predicting the chemical attributes of fresh peach fruits.

This investigation aimed to develop a method to predict the total soluble solids (TSS), titratable acidity, TSS/titratable acidity, vitamin C, anthocyanin, and total carotenoids contents using surface color values (L*, Hue and chroma), single fruit weight, juice volume, and sphericity percent of fresh peach fruit. Multiple regression analysis (MLR) and an artificial neural network (ANN) were employed. An ANN model was developed with six inputs and 15 neurons in the first hidden layer for the prediction of six chemical composition parameters. The results confirmed that the ANN model R2 = 974-0.998 outperformed the MLR models R2 = 0.473-0.840 using testing dataset. Moreover, sensitivity analysis revealed that the juice volume was the most dominating parameter for the prediction of titratable acidity, TSS/titratable acidity and vitamin C with corresponding contribution values of 39.97%, 50.40%, and 33.08%, respectively. In addition, sphericity percent contributed by 23.70% to anthocyanin and by 24.08% to total carotenoids. Furthermore, hue on TSS prediction was the highest compared with the other parameters, with a contribution percentage of 20.86%. Chroma contributed by different values to all variables in the range of 5.29% to 19.39%. Furthermore, fruit weight contributed by different values to all variables in the range of 16.67% to 23.48%. The ANN prediction method denotes a promising methodology to estimate targeted chemical composition levels of fresh peach fruits. The information of peach quality reported in this investigation can be used as a baseline for understanding and further examining peach fruit quality.

Fruit properties during the harvest period of eleven Indian jujube (Ziziphus mauritiana Lamk.) cultivars.

The geometric attributes and physical, mechanical, and chemical properties were determined for 11 Indian jujube (Ziziphus mauritiana Lamk.) cultivars grown in Saudi Arabia including Zaytoni, Kashmiri, Komethry, Um-Sulaem with spines, Toffahy, Um-Sulaem without spines, Abdel-Sattar, Pu-Yun, Pu-Pineau, seedy ber, and buddling ber. The geometric mean diameter, surface area, sphericity, and shape index of the fruits ranged from 20.61 to 42.48 mm, 1339.58-5666.92 mm2, 71.39-96.80%, and 110.25-275.18%, respectively. The fruit physical properties, i e fruit weight, fruit volume, stone weight, flesh weight, true fruit density, and pulp-stone ratio varied from 4.71 to 39.02 g, 4.78 to 42.75 cm3, 0.11 to 2.35 g, 4.61 to 36.67 g,0.913 to 1.055 g/cm3, and 7.90 to 43.11, respectively. In addition, the mean color value of L*, a* and b* for the fruits ranged from 64.48 to 96.33, 2.65-4.05, and 6.32-84.36, respectively. The mechanical properties, including elastic range, bioyield force, modulus of elasticity, plastic range, and rupture force ranged from 2.31 to 8.86 mm, 21.64-325.77 N, 14.15-124.09 N/s, 0.83-3.45 mm, 56.42-364.21 N, and 107.77-480.91 N/s, respectively. The greatest rupture force belonged to the Pu-Pineau cultivar and the smallest belonged to the Um-Sulaem without spines cultivar at the horizontal orientation of both cultivars. The fruit chemical analysis values for total soluble solids, titratable acidity, total soluble solids/titratable acidity ratio, and vitamin C ranged from 13.43 to 23.55%, 0.48-1.27%, 14.24-39.85%, and 55.27-164.47 mg/100 g, respectively. The relevant data obtained for the 11 varieties of Indian jujube are valuable for developing and designing machines for processing operations, transportation, separating, packing, sorting, and harvesting. Additionally, the findings revealed considerable variation in chemical content, physical and mechanical characteristics among the tested cultivars.

Co-application of mineral and organic fertilizers under deficit irrigation improves the fruit quality of the Wonderful pomegranate.

BACKGROUND: The aim of this study was to determine the individual and interactive effects of various irrigation regimes and fertilizer treatments on the quality of the Wonderful pomegranate cultivar. METHODS: Two field experiments were conducted over two consecutive growing seasons (2018 and 2019) to determine the individual and interactive effects of various organic and mineral fertilizer treatments on the fruit quality of the Wonderful pomegranate under various irrigation conditions. A split-plot experimental design was used, in which the main plots included three levels of irrigation (100%, 80%, and 60% of evapotranspiration) while the subplots included five fertilizer treatments with different co-application ratios of mineral and organic fertilizers. RESULTS: All tested physicochemical properties of the fruit were significantly affected by the irrigation treatment, with irrigation at 80% of evapotranspiration representing the best strategy for reducing water use and improving fruit quality. Moreover, the co-application of mineral and organic fertilizers had a significant effect on fruit quality, with 75% mineral + 25% organic fertilizer improving all of the physical and chemical properties of the fruit in both experimental seasons. Irrigation and the co-application of mineral and organic fertilizers also had a significant interaction effect on the physicochemical attributes of fruit, which further increased fruit quality. CONCLUSIONS: The co-application of organic and mineral fertilizers produced better quality pomegranate fruit than mineral fertilizer alone under deficit irrigation conditions. This technique could therefore be applied to improve the fruiting of horticultural trees in arid growing regions.

Impact of organic manure on fruit set, fruit retention, yield, and nutritional status in pomegranate (Punica granatum L. "Wonderful") under water and mineral fertilization deficits.

This research was conducted on mature pomegranate (Punica granatum L. "Wonderful") trees growing at a site located in North Coast, Matrouh Governorate, Egypt. The aim was to investigate the impacts of different irrigation regimes in combination with different fertilizer regimes on the fruit set, fruit retention, yield, and nutritional status of the trees. The experimental factors were arranged in a split-plot design, with four replicates per treatment combination. The results indicated that all of the characteristics measured, including leaves nutritional status, percentages of fruit set, fruit drop, fruit retention, fruit cracking, fruit sunburn, and marketable fruit, and yield were significantly affected by the interaction between the irrigation treatment which denoted by percentages of reference evapotranspiration (ETo) and fertilizer regime. The application of 75% mineral fertilizer + 25% organic manure under deficit irrigation of 80% ETo increased the yield by an average of 18.23% over the 2 years compared with 100% mineral fertilization under full irrigation, while 50% mineral fertilizer + 50% organic matter under 80% ETo gave the maximum percentage of marketable fruit (86.23% and 86.84% in 2018 and 2019, respectively). The maximum water use efficiency was obtained with the 80% ETo treatment combined with 75% mineral fertilizer + 25% organic manure in both seasons with values of 9.69 and 10.06 kg/m3 applied water, respectively. These results demonstrate that under the field conditions at the experimental site, the fruit set and retention could be improved by applying a reduced amount of mineral fertilizer in combination with organic manure and less irrigation water.

Application of artificial neural network and support vector regression in predicting mass of ber fruits (Ziziphus mauritiana Lamk.) based on fruit axial dimensions.

Fruit quality attributes are important factors for designing a market for agricultural goods and commodities. Support vector regression (SVR), MLR, and ANN models were established to predict the mass of ber fruits (Ziziphus mauritiana Lamk.) based on the axial dimensions of the fruit from manual measurements of fruit length, minor fruit diameter, and maximum fruit diameter of four ber cultivars. The precision and accuracy of the established models were assessed given their predicted values. The results revealed that using the validation dataset, the developed ANN (R2 = 0.9771; root mean square error [RMSE] = 1.8479 g) and SVR (R2 = 0.9947; RMSE = 1.8814 g) models produced better results when predicting ber fruit mass than those obtained by the MLR model (R2 = 0.4614; RMSE = 11.3742 g). In estimating ber fruit mass, the established SVR and ANN models produced more precise prediction values than those produced by the MLR model; however, the performance differences between the SVR and ANN models were not clear.

Meloidogyne incognita population control and nutritional status and productivity of Thompson seedless grapevines managed with different treatments.

A two-year field trial was conducted in a vineyard (northern Egypt)cultivated with Thompson seedless grapevines to evaluate the effectiveness of four "alternative" (biological/chemical) treatments, Bacillus megaterium, boric acid, calcium nitrate and chitosan, against the root-knot nematode Meloidogyne incognita (Mi), compared to that of the nematicide oxamyl. The influence of these treatments on plant nutritional status and fruit yield and quality was also assessed. All treatments significantly inhibited Mi reproduction parameters in both seasons, decreasing the numbers of nematode galls and egg masses (roots) and of second-stage juveniles (soil). Oxamyl application resulted in the highest reductions in Mi-reproduction parameters, followed by boric acid, which also showed the highest relative nematicidal efficacy (respect to oxamyl). In the 1st season, the highest fruit yield (10.34 kg/grapevine) was recorded from boric acid-treated plants, followed by that from oxamyl-treated plants (7.50 kg/grapevine); in the subsequent season (2019), oxamyl use led to the highest yield, followed by boric acid + chitosan use (10.04 and 8.62 kg/grapevine, respectively). In both seasons, application of boric acid alone and combined with chitosan enhanced the total soluble solids (TSS)/total acidity ratio in grape juice. All treatments led to higher nutrient contents (leaf petioles) and chlorophyll levels (leaves) as well as enhanced fruit size and weight. We conclude that the tested treatments can be safely applied for nematode management in Thompson seedless grapevines, with positive effects on fruit yield and quality.

Fibrin Sealant and Lipoabdominoplasty in Obese Grade 1 and 2 Patients

BACKGROUND: Ever since lipoabdominoplasty was first developed to achieve better aesthetic outcomes and less morbidity, the rate of seroma formation, especially in obese patients, has disturbed plastic surgeons. The aim of this study was to evaluate the effect of fibrin sealant in the prevention of seroma formation after lipoabdominoplasty in obese patients. METHODS: Sixty patients with a body mass index (BMI) between 30 and 39.9 were assigned randomly to 1 of 2 groups (30 patients each). Group A underwent lipoabdominoplasty with fibrin glue, while group B underwent traditional lipoabdominoplasty; both had closed suction drainage applied to the abdomen. The patients' demographics and postoperative complications were recorded. Seroma was detected using abdominal ultrasound examinations at two postoperative periods: between postoperative days 10 and 12 and, between postoperative days 18 and 21. RESULTS: The age range was 31 to 55 years (38.5+/-9.5 years) in group A and 25 to 58 years (37.8+/-9.1 years) in group B, while the mean BMI was 31.4 to 39.9 kg/m2 (32.6 kg/m2) in group A and 32.7 to 37.4 kg/m2 (31.5 kg/m2) in group B. In group A, the patients had a complication rate of 10% in group A versus 43% in group B (P<0.05). The incidence of seroma formation was 3% in the fibrin glue group but 37% in the lipoabdominoplasty-alone group (P<0.05). CONCLUSIONS: Lipoabdominoplasty with the use of autologous fibrin sealant is a very effective method that significantly reduces the rate of postoperative seroma.