scholarly journals Grading and Sorting of Grape Berries Using Visible-Near Infrared Spectroscopy on the Basis of Multiple Inner Quality Parameters

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2600 ◽  
Author(s):  
Hui Xiao ◽  
Li Feng ◽  
Dajie Song ◽  
Kang Tu ◽  
Jing Peng ◽  
...  
Keyword(s):  
Vitis Vinifera ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Quality Parameters ◽  
Total Phenolic ◽  
Soluble Solid Content ◽  
Vitis Vinifera L ◽  
Grape Berries ◽  
Grape Quality

The potential of visible-near infrared (vis/NIR) spectroscopy (400 nm to 1100 nm) for classification of grape berries on the basis of multi inner quality parameters was investigated. Stored Vitis vinifera L. cv. Manicure Finger and Vitis vinifera L. cv. Ugni Blanc grape berries were separated into three classes based on the distribution of total soluble solid content (SSC) and total phenolic compounds (TP). Partial least squares regression (PLS) was applied to predict the quality parameters, including color space CIELAB, SSC, and TP. The prediction results showed that the vis/NIR spectrum correlated with the SSC and TP present in the intact grape berries with determination coefficient of prediction (RP2) in the range of 0.735 to 0.823. Next, the vis/NIR spectrum was used to distinguish between berries with different SSC and TP concentrations using partial least squares discrimination analysis (PLS-DA) with >77% accuracy. This study provides a method to identify stored grape quality classes based on the spectroscopy and distributions of multiple inner quality parameters.

Automatic discrimination of grapevine (Vitis vinifera L.) clones using leaf hyperspectral imaging and partial least squares

2014 ◽  
Vol 153 (3) ◽  
pp. 455-465 ◽  
Author(s):  
A. M. FERNANDES ◽  
P. MELO-PINTO ◽  
B. MILLAN ◽  
J. TARDAGUILA ◽  
M. P. DIAGO
Keyword(s):  
Vitis Vinifera ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Dna Analysis ◽  
Apical Part ◽  
Vitis Vinifera L ◽  
Adaxial Side ◽  
Infrared Wavelength ◽  
Grapevine Leaves

SUMMARYA worldwide innovative method to discriminate grapevine clones is presented. It is an alternative to ampelography, isozyme and DNA analysis. The spectra and their first and second derivatives of 201 bands in the visible and near-infrared wavelength range between 634 and 759 nm were used as inputs to a classifier created using partial least squares. The spectra were acquired in the laboratory for the adaxial side of the apical part of the main lobe of fully hydrated grapevine leaves. The classifier created allowed the separation of 100 leaves of the Cabernet Sauvignon (Vitis vinifera L.) variety into four clones, namely CS 15, CS 169, CS 685 and CS R5, comprising 25 leaves each. The percentages of leaves correctly classified for these clones were 98·2, 99·2, 100 and 97·8%, respectively, when the classifier input was the second derivative of the normalized spectra. These percentages were determined by Monte-Carlo cross-validation. With the new method proposed, each leaf of a given variety can be classified in a few seconds according to its clone in an environmentally friendly way.

scholarly journals Tuning Potassium Fertilization to Improve pH and Acidity in Glera Grapevine (Vitis vinifera L.) under a Warming Climate

2021 ◽  
Vol 11 (24) ◽  
pp. 11869
Author(s):  
Patrick Marcuzzo ◽  
Federica Gaiotti ◽  
Marco Lucchetta ◽  
Lorenzo Lovat ◽  
Diego Tomasi
Keyword(s):  
Vitis Vinifera ◽  
Titratable Acidity ◽  
Soluble Solids ◽  
Vitis Vinifera L ◽  
Experimental Conditions ◽  
Grape Berries ◽  
Potassium Fertilization ◽  
Grape Quality ◽  
K Concentration ◽  
K Fertilization

Potassium concentration in grape berries can affect acidity and pH in must and wines. Under the current warming scenario, where preserving equilibrated value for these grape parameters is increasingly challenging, K fertilization could represent a tool to manage grape composition. In this study, the effect of potassium fertilization was investigated over 4 years (2013–2016) in field-grown grapevines (Vitis vinifera cv. Glera). Four different potassium rates (0, 15, 30, 60 kg K2O ha−1 year−1) were tested and agronomic responses, grape quality as well as K concentration in the berry were recorded over the four years. At harvest, yield parameters and total soluble solids were unaffected by potassium fertilization. On the contrary, the titratable acidity of the musts was increased by the higher rate of potassium (K60), and both tartaric and malic acids showed higher values when the K rate was higher. K fertilization did not affect the pH, as all the treatments displayed comparable pH values and in an optimal range for winemaking. Overall, in our experimental conditions, medium potassium inputs showed better results on Glera grape quality compared to low K rates, by promoting higher titratable acidity levels without altering the pH in musts.

scholarly journals Rapid and Cost-Effective Assessment of the Neutral and Acid Detergent Fiber Fractions of Chickpea (Cicer arietinum L.) by Combining Modified PLS and Visible with Near-Infrared Spectroscopy

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 666
Author(s):  
Rafael Font ◽  
Mercedes del Río-Celestino ◽  
Diego Luna ◽  
Juan Gil ◽  
Antonio de Haro-Bailón
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Cicer Arietinum ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Cross Validation ◽  
Neutral Detergent Fiber ◽  
Acid Detergent Fiber ◽  
Cicer Arietinum L

The near-infrared spectroscopy (NIRS) combined with modified partial least squares (modified PLS) regression was used for determining the neutral detergent fiber (NDF) and the acid detergent fiber (ADF) fractions of the chickpea (Cicer arietinum L.) seed. Fifty chickpea accessions (24 desi and 26 kabuli types) and fifty recombinant inbred lines F5:6 derived from a kabuli × desi cross were evaluated for NDF and ADF, and scanned by NIRS. NDF and ADF values were regressed against different spectral transformations by modified partial least squares regression. The coefficients of determination in the cross-validation and the standard deviation from the standard error of cross-validation ratio were, for NDF, 0.91 and 3.37, and for ADF, 0.98 and 6.73, respectively, showing the high potential of NIRS to assess these components in chickpea for screening (NDF) or quality control (ADF) purposes. The spectral information provided by different chromophores existing in the chickpea seed highly correlated with the NDF and ADF composition of the seed, and, thus, those electronic transitions are highly influenced on model fitting for fiber.

scholarly journals Polyphenols From Vitis vinifera Lambrusco By-Products (Leaves From Pruning): Extraction Parameters Evaluation Through Design of Experiment

2019 ◽  
Vol 14 (7) ◽  
pp. 1934578X1986290 ◽  
Author(s):  
Massimo Tacchini ◽  
Ilaria Burlini ◽  
Immacolata Maresca ◽  
Alessandro Grandini ◽  
Tatiana Bernardi ◽  
...  
Keyword(s):  
Vitis Vinifera ◽  
Antioxidant Capacity ◽  
Design Of Experiment ◽  
Extraction Yield ◽  
Wine Industry ◽  
Raw Material ◽  
Extraction Time ◽  
Total Phenolic ◽  
Vitis Vinifera L ◽  
By Products

Vitis vinifera L. leaves from pruning are by-products of the wine industry and represent an important source of secondary raw material, thanks to their polyphenols content. Optimization of the extraction processes is a key factor for their valorization, and Design of Experiment (DOE) could be a tool to obtain the most performing extract in terms of polyphenols quality/quantity and bioactivity. Vitis vinifera Lambrusco leaves were subjected to ultrasound-assisted extractions guided by a 23 factorial design. Three independent parameters (% solvent, time of extraction, and solvent:solid ratio) were considered to evaluate the extraction process by analyzing the extraction yield, the total phenolic content (Folin-Ciocalteu assay), and the antioxidant capacity (DPPH assay). Moreover, the content of the main molecules was identified and quantified by reversed-phase high-performance liquid chromatography coupled with diode array detection and mass spectrometry. The DOE highlighted the best extraction conditions that showed slight changes considering the different evaluating parameters. The highest extraction yield was obtained by extraction with 100% water, 60 minutes of extraction time, and 30:1 solvent:solid ratio, but it was neither the richest in polyphenols nor antioxidant capacity. The latter 2 characteristics were associated with the extraction performed using 50% ethanol, 35 minutes of extraction time, and a 20:1 solvent:solid ratio. That extract also exhibited the highest quantity of flavonols.

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