Nitrogen and organic fertilizer on the postharvest quality of Isabel Precoce grapes

Lima, Franciezer Vicente de; Moura, Elias Ariel de; Mendonça, Vander; Oliveira, Luana Mendes; Melo, Marlenildo Ferreira; Celedônio, Wilma Freitas; Mendonça, Luciana Freitas de Medeiros; Alves, Anderson Araujo; Irineu, T. H. S.; Figueiredo, Francisco Romário Andrade; Siqueira, Raphael Henrique da Silva

doi:10.1080/01904167.2021.1881543

Cited by 4 publications

(2 citation statements)

References 42 publications

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“…Figure 3 shows the values of SSC, TA, and SSC/TA in the four ripening stages of table grapes. The SSC and TA contents ranged from 15.47 to 20.28% and 3.73 to 10.22 g/L, respectively, consistent with previous research conducted by Lima et al [ 42 ]. As expected, SSC and SSC/TA increased while TA decreased during grapes’ ripening, indicating a gradual accumulation of sugars and degradation of organic acids.…”

Section: Resultssupporting

confidence: 90%

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

Ping

Yang

Zhou

et al. 2023

Foods

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

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Section: Resultssupporting

confidence: 90%

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

Ping

Yang

Zhou

et al. 2023

Foods

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“…Suitable soil is essential for the quality and yield of grapes (Ghimire et al 2014;Poni et al 2018). The effect of nitrogen on the composition and quality of grapes is usually a combination of its direct effect on grape metabolism and its indirect effect related to its strong influence on vigor and yield, resulting in influencing the soluble solids, reducing sugars, total soluble sugars, ratio of high soluble solids content/titratable Pinot Noir Jiayuguan 2.15 ± 0.05 a 0.62 ± 0.03 a 3.36 ± 0.12 a 0.54 ± 0.01 b 4.12 ± 0.1 a 199.17 ± 0.9 c 81.63 ± 1.83 b 92.01 ± 9.26 a 23.7 ± 0.46 a 4.63 ± 0.3 c 43.78 ± 1.13 a 9.24 ± 0.54 b 155.03 ± 11.67 ab Wuwei 2.35 ± 0.23 a 0.57 ± 0.03 ab 3.08 ± 0.27 a 0.69 ± 0.06 a 3.48 ± 0.63 a 224.53 ± 5.17 a 91.98 ± 1.51 a 95.5 ± 5.89 a 22.17 ± 0.59 b 6.14 ± 0.21 b 48.93 ± 4.5 a 11.99 ± 0.18 a 166.27 ± 7.27 a Zhangye 1.6 ± 0.2 b 0.51 ± 0.06 b 2.47 ± 0.07 b 0.51 ± 0.06 b 4.17 ± 0.03 a 215.33 ± 1.72 b 95.43 ± 7.05 a 93.4 ± 8.45 a 22.87 ± 0.7 ab 8.47 ± 0.68 a 37.4 ± 0.69 b 9.69 ± 0.2 b 147.63 ± 6.36 b Vidal Jiayuguan 2.18 ± 0.39 a 0.52 ± 0.02 a 3.79 ± 0.43 a 0.71 ± 0.02 a 3.93 ± 0.12 a 201.03 ± 2.24 a 87.98 ± 6.64 a 80.5 ± 0.99 a 22.9 ± 0.44 a 0.05 ± 0.01 b 61.25 ± 3.02 a 10.36 ± 0.1 a 171.37 ± 5.39 a Wuwei 1.75 ± 0.25 a 0.54 ± 0.04 a 3.53 ± 0.17 ab 0.77 ± 0.11 a 3.82 ± 0.26 a 188. acidity, and grape pH (Baiano et al 2011;Lima et al 2021;Thomidis et al 2016). Approximately 50% of the potassium absorbed by the vine accumulates in the berry, mainly concentrated in the peel.…”

Section: Discussionmentioning

confidence: 99%

Response of Wine Grape Quality to Rainfall, Temperature, and Soil Properties in Hexi Corridor

Yan

et al. 2022

horts

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This study aimed to clarify the relationship between grape (Vitis vinifera L.) quality and environmental factors (climate and soil), and to elucidate the theoretical basis and provide technical guidance for the rational planning of the cultivation area and the precise regulation of the cultivation mode in the future. The fruits of three different grape cultivars, Pinot Noir, Merlot, and Vidal, as well as soil samples and meteorological data were collected from three wine grape growing areas (Wuwei, Zhangye, and Jiayuguan) in the Hexi Corridor, Northwest China. Principal-component analysis (PCA) and correlation analysis were conducted to understand the relationship of grape quality with weather conditions and soil properties. The results showed that the titratable acid content of grape berries was significantly negatively correlated with average temperature from August to September, average minimum temperatures from August to September, and from April to October, mean annual minimum temperature, growing degree days from August to September, and soil total nitrogen content, and significantly positively correlated with average rainfall from April to October, annual mean rainfall, and soil available potassium content. In addition, the pH of grape juice was significantly negatively correlated with annual mean rainfall and soil available potassium content. However, it was significantly positively correlated with average temperature and average minimum temperature from August to September, average minimum temperature from April to October, growing degree days from August to September, as well as soil total nitrogen content. In addition, the results of PCA showed that the fruit quality scores of ‘Vidal’ in Jiayuguan, ‘Merlot’ in Zhangye, and ‘Pinot Noir’ in Wuwei were the highest, respectively. In conclusion, the contents of titratable acid, pH, and Brix° are greatly affected by climate and soil factors. ‘Vidal’, ‘Merlot’, and ‘Pinot Noir’ were suitable for planting in Jiayuguan, Zhangye, and Wuwei, respectively. Nowadays, few reports focus on the relationship between grape quality and soil and climate conditions. Based on the investigation and analysis of the differences of climate, soil, and grape berries quality in the three production areas of Hexi Corridor, the relationship among climate, soil, and grape quality by using statistical methods was studied, which could provide references for clarifying the reasons why environmental factors affect grape quality and select the suitable area for wine grape cultivation.

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Fresh Fruits and Vegetables Quality and Safety: A Deep Insight on the Benefits of an Organic Farming Approach

Pradhan,

Srijaya

2024

Advances in Science, Technology &Amp; Innovation

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Nitrogen and organic fertilizer on the postharvest quality of Isabel Precoce grapes

Cited by 4 publications

References 42 publications

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

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

Response of Wine Grape Quality to Rainfall, Temperature, and Soil Properties in Hexi Corridor

Fresh Fruits and Vegetables Quality and Safety: A Deep Insight on the Benefits of an Organic Farming Approach

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