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Characterization and predicting of carbohydrate content in zucchini fruit using near infrared spectroscopy: Predicting carbohydrates in zucchini by NIRS
Journal of The Science of Food and Agriculture
Abstract
Background:
Zucchini fruit plays an important part in healthy nutrition due to its high content of carbohydrates. Recent studies have demonstrated the feasibility of Vis/NIRS to predict quality profile. However, this procedure has not been applied to determinate carbohydrates.
Results:
VIS-NIR and wet chemical methods were used to determinate individual sugars and starch in zucchini fruits. By applying a principal component analysis (PCA) with NIR spectral data a differentiation between the less sweet vs. the sweetest zucchini accessions could be found. For the determination of carbohydrate content effective prediction models for individual sugars such as glucose, fructose, sucrose and starch by using partial least square (PLS) regression have been developed.
Conclusion:
The coefficients of determination in the external validation (R(2) VAL) ranged from 0.66 to 0.85. The standard deviation (SD) to standard error of prediction ratio (RPD) and SD to range (RER) were variable for different quality compounds and showed values that were characteristic of equations suitable for screening purposes. From the study of the MPLS loadings of the first three terms of the different equations for sugars and starch, it can be concluded that some major cell components as pigments, cellulose, organic acids highly participated in modelling the equations for carbohydrates.
... The absorption bands considered for analysis were 484 nm, 680 nm, 980 nm, 1168 nm, 1434 nm, 1780 nm, 1900 nm, 2010 nm, and 2432 nm. The absorption peaks around 484 nm and 680 nm correspond to chlorophyll pigment (Aparatana et al., 2022;Pomares-Viciana et al., 2018). The visible region was included in the model development, although it was not part of the objective of this study. ...
... Meanwhile, the PC2 loadings spectra distinguished the juice samples of DEM from those of SEM based on the variables observed (Fig. 4b). The SEM samples depicted several chemical information with absorption peaks at 1486 nm and 2110 nm, which are associated with the N-H stretching model of protein (Aït Kaddour et al., 2008), 1780 nm and 2336 nm are related to the C-H (Bázár et al., 2016;Pomares-Viciana et al., 2018) and 1880 nm corresponds to the C-O stretching mode (Golic et al., 2003) as shown in Fig. 4b. While for DEM, the absorption peak at 1888 nm is related to the C-H stretching mode of the first overtone and 2010 nm relates to the combined group of the O-H deformation and C-O deformation, corresponding to carbohydrates (Osborne et al., 1993). ...
... The highest absorption peak at 1892 nm from the raw spectra influenced the prediction of SSC in sugarcane juice (Fig. 5c). The peak of 1892 nm is a combined group of the O-H stretch and C-H stretch associated with carbohydrates (Osborne et al., 1993;Pomares-Viciana et al., 2018). For the 2D spectra of SEM samples, the strongest absorption peak was found at 2280 nm which is identified as the main absorption band to predict SSC in juice (Fig. 5d). ...
... For this reason a non-chemical (producing no chemical waste) and rapid technique, near-infrared reflectance spectroscopy (NIRS), which has been successfully applied in various fields from life sciences to environmental issues, is explored here to screen quality in mangetout pods [17]. Near-infrared spectroscopy is a technique that uses the radiation absorbed by a set of samples in the region from 780 to 2500 nm (near-infrared region-NIR spectroscopy in combination with chemometric analyses can be used for analysis of numerous components (protein, carbohydrates, carotenoid, minerals, glucosinolates, phenolics) and parameters of the sample (firmness, Brix, acidity, color) to be analyzed [18][19][20][21][22][23]. NIRS depends on the number and type of C-H, N-H and O-H bonds in the material being analyzed, then spectral features are combined with reliable compositional or functional analyses of the material in a predictive statistical model. ...
... Recently, the use of NIRS models for predicting the quality of vegetables has been reported, several of which have addressed zucchini [19,20], pepper, rocket leaves, blackberries [16,21,22] and Ethiopian mustard leaves [23], among others. The seed quality of various legume species has also been analyzed using NIRS such as lentils [25], chickpeas [26] and pea accessions from different germplasm collections [27,28]. ...
Pisum sativum L. ssp. arvense, is colloquially called tirabeque or mangetout because it is eaten whole; its pods are recognized as a delicatessen in cooking due to its crunch on the palate and high sweetness. Furthermore, this legume is an important source of protein and antioxidant compounds. Quality control in this species requires the analysis of a large number of samples using costly and laborious conventional methods. For this reason, a non-chemical and rapid technique as near-infrared reflectance spectroscopy (NIRS) was explored to determine its physicochemical quality (color, firmness, total soluble solids, pH, total polyphenols, ascorbic acid and protein content). Pod samples from different cultivars and grown under different fertigation treatments were added to the NIRS analysis to increase spectral and chemical variability in the calibration set. Modified partial least squares regression was used for obtaining the calibration models of these parameters. The coefficients of determination in the external validation ranged from 0.50 to 0.88. The RPD (standard deviation to standard error of prediction ratio) and RER (standard deviation to range) were variable for quality parameters and showed values that were characteristic of equations suitable for quantitative prediction and screening purposes, except for the total soluble solid calibration model.
... PCA systematically identifies orthogonal axes, or principal components, that capture the maximum variance in the data, effectively transforming the dataset into a lowerdimensional subspace while preserving key information [38]. PCA has been utilized in the detection of nutritional stress in sugarcane, nitrogen analysis in tomato, as well as characterization and prediction of carbohydrates in zucchini [2,41,46]. On the other hand, the chlorophyll index is a measurement of the total chlorophyll pigments, generally making use of the spectral region 400-860 nm [47]. This index has been widely used for the identification of the amount of chlorophyll in plants such as tomato, maize (corn) and banana [8,27,55]. ...
... R 2 is a measure of the PLSR model s adaptability to the observed data. Based on R 2 , the model can be categorized as follows: a model exhibiting weak correlation 0.26 R 2 0.49 ; a model capable of distinguishing between models with low and high sample values 0.50 R 2 0.64 ; a model suitable for rough sample prediction 0.65 R 2 0.81 ; models with good correlation 0.82 R 2 0.90 and high accuracy R 2 0.90 26 . The higher the value of RPD, the better the model s ability for quantitative prediction and RPD values larger than 2 shows the model s reliability 27 . ...
The negative impact of lipid peroxidation on health is intimately tied to its oxidation products. In this study, methyl oleate was oxidized at 180℃ for 0, 2, 4, 8 and 12 h respectively. The free radicals and volatile components generated during the oxidation process were determined using electron spin resonance and headspace solid-phase microextraction (HS-SPME)-GC-MS. The pro-inflammatory effects of oxidized methyl oleate were evaluated in RAW264.7 cells. Then partial least-squares regression (PLSR) models were established for predicting the 3 pro-inflammatory genes expression based on the volatile components. The results revealed that the alkoxy radical content increased rapidly during oxidation from 4 h to 8 h, and the rate of oxidation of methyl oleate dropped after 8 h. A total of 27 volatile oxidation compounds were detected by HS-SPME-GC-MS. The content of most compounds, including aldehydes, esters, and acids, exhibited a pattern of initial increase and then decrease as the oxidation time increased. Similarly, the proinflammatory effects of oxidized methyl oleate peaked after 8 h of oxidation. The PLSR quantitative prediction models showed that the coefficient of determination (R²P) between the predicted and measured values of the 3 inflammatory gene expressions were 0.915, 0.946 and 0.951 respectively. The established PLSR model predicts the pro-inflammatory effects of oxidized methyl oleate well and provides a theoretical foundation for quick evaluation of the pro-inflammatory effects of oxidized lipids.
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... The ratio between TSS and TA (TSSTAR) was also calculated. Similarly, the total sugar (TS) was determined as described by Pomares-Viciana et al., (2018), Bates et al., (1973) method was followed for leaf proline content (PC). The relative water content (RWC) was estimated as described by Khakwani et al., (2012). ...
... The prediction models were developed using partial least squares (PLS) regression and leave-one-out cross-validation [40], as developed by Corrêdo et al. [41]. The PLS regression is often adopted for spectroscopy studies since it can cope with multivariate data, converting it into a new multi-dimensional coordinate system (loadings) through the creation of a smaller number of orthogonal variables (latent variables-LV) [42,43]. The optimal PLS models were determined based on the lowest number of latent variables (LV) and a lower RMSE of the cross-validation value. ...
In-field quality prediction in agricultural products is mainly based on near-infrared spectroscopy (NIR). However, initiatives applied to sugarcane quality are only observed under laboratory-controlled conditions. This study proposed a framework for NIR spectroscopy sensing to measure sugarcane quality during a real harvest operation. A platform was built to support the system composed of the NIR sensor and external lighting on the elevator of a sugarcane harvester. Real-time data were acquired in commercial fields. Georeferenced samples were collected for calibration, validation, and adjustment of the multivariate models by partial least squares (PLS) regression. In addition, subsamples of defibrated cane were NIR-acquired for the development of calibration transfer models by piecewise direct standardization (PDS). The method allowed the adjustment of the spectra collected in real time to predict the quality properties of soluble solids content (Brix), apparent sucrose in juice (Pol), fiber, cane Pol, and total recoverable sugar (TRS). The results of the relative mean square error of prediction (RRMSEP) were from 1.80 to 2.14%, and the ratio of interquartile performance (RPIQ) was from 1.79 to 2.46. The PLS-PDS models were applied to data acquired in real-time, allowing estimation of quality properties and identification of the existence of spatial variability in quality. The results showed that it is possible to monitor the spatial variability of quality properties in sugarcane in the field. Future studies with a broader range of quality attribute values and the evaluation of different configurations for sensing devices, calibration methods, and data processing are needed. The findings of this research will enable a valuable spatial information layer for the sugarcane industry, whether for agronomic decision-making, industrial operational planning, or financial management between sugar mills and suppliers.
... They obtained a coefficient of determination of prediction set (r 2 ) of around 0.70-0.80. Pomares-Viciana et al. (2017) developed NIR models to predict the SC of freeze-dried zucchini samples, and the model could be used for screening purposes (r 2 of 0.66 and SEP of 21.29 mg g −1 DW). NIR spectroscopy could become an especially useful selection tool in zucchini breeding programmes and quality control as well. ...
Online measurement of moisture content (MC) and higher heating value (HHV) is desired for supporting the thermal conversion process in power plants. The main objective of this study was to develop a reliable and accurate method for online measuring of the HHV and MC of dried and as received sugarcane bagasse, respectively, using near-infrared (NIR) spectroscopy. Simulation of the conveyor belt in power plants and online energy quality analysis of bagasse for combustion process were designed. One hundred samples of bagasse were collected from different sugar mills at various locations of large piles of bagasse stored in both indoor and outdoor buildings. A long-wave spectrometer with a wavelength range of 860–1755 nm was used for scanning using diffuse reflection mode. The models were developed by partial least squares (PLS) regression using spectral sets obtained from the raw spectra, the preprocessed full spectra from the traditional approach, and the preprocessed spectra from the multi-block technique. The multi-blocks of the spectral pre-treatment technique provided effective models for both MC and HHV prediction. The best model for MC had a coefficient of determination of prediction (R²p) and the root mean square error of prediction (RMSEP) of 0.90 and 3.9% wb respectively. In the meantime, the best model for HHV had R²p and the RMSEP of 0.71 and 188.7 J g⁻¹. This research demonstrated that NIR spectroscopy provides a feasible and reliable method for online analysis of MC and could be used for screening of HHV of bagasse.
... This might account for the variation in predicted values for the tubers. Pomares-Viciana et al. (2018) used the visible and near-infrared region of 400-2500 nm to measure SC in freeze-dried zucchini fruit. Their results yielded R 2 cv and SEP values of 0.66 and 21.29 g kg − 1 of dry weight sample, respectively. ...
This study used a portable near-infrared (NIR) spectrometer at wavelengths of 570–1031 nm to evaluate starch content (SC) and dry matter content (DMC) in fresh cassava tubers. An improved model was developed for the prediction of cassava tuber quality. The cassava samples were taken from four main varieties: CMR38-125-77, KU50, RY11, and RY9. The samples were obtained 4–12 months after planting (MAP). Partial least squares (PLR) regression was combined with different variable selection methods and spectral pre-treatment. Their accuracies were then compared. Variable selection methods included the successive projections algorithm (SPA) and the genetic algorithm (GA). The NIR spectra were obtained in the interactance mode under field conditions. The GA wavelengths combined with sequential pre-processing by orthogonalization (SPORT) pre-processing provided the optimum model for predicting both the SC and the DMC of cassava. The R²p, RMSEp, and RPD of SC were 0.91, 1.76%, and 3.26, respectively, and those of DMC were 0.75, 2.00%, and 2.00, respectively. The most effective model was tested against unknown samples of newly developed varieties obtained from different harvest seasons, yielding RMSEp and bias values of 2.37% and −9.178 × 10⁻⁶%, respectively, for SC. For DMC, the RMSEp and bias values were 2.67% and 4.16 × 10⁻¹⁴%, respectively. The results suggest that the calibration model could be used to monitor the internal quality of cassava tubers in the field. The variety, age, position, and section of the tubers had a slight influence on the prediction performance; however, the prediction accuracy was acceptable for in-field applications. The in-field portable NIR spectrometer could become a new tool for breeders, saving time and costs. Breeders could evaluate SC without destroying the cassava roots or stalks and could correct and inspect the behaviour of the SC and DMC accumulation.
... Near-Infrared Reflectance Spectroscopy (NIRS) could help breeders in the choice of promising genotype and selection of the elite accessions based on the chemical composition that meets the market demand (sugars, high starch, or protein contents) [7] and provides a non-destructive rapid tool for constituent measurement of food samples. Many researchers have used the NIR spectral fingerprints to distinguish melon and watermelon genotypes [8,9], zucchini lines [10], as well as yam genotypes [11], along with the metabolic fingerprinting of water-stressed soybean cultivars [12]. ...
Background
Germplasm identification is an essential connection linking the conservation and exploitation of crop genetic resources in several plant breeding programs. This study highlights the biochemical and molecular variations in a collection of pumpkin genotypes representing four climate zones. The information could help improve germplasm management and sustainable exploitation of the neglected genotypes.
Methods and results
Chemical characterization and genetic diversity among nine Egyptian landraces of pumpkin (Cucurbita moschata Duchesne) were estimated using Diode Array (DDA) Near Infra-Red (NIR) technology and the Inter simple Sequence Repeat markers (ISSR). Pumpkin seeds were collected from various geographical parts of Egypt. The spectroscopic properties of pumpkin seeds were used to quantify the fat, moisture, protein, ash, fiber, and total carbohydrate contents. The ten ISSR primers generated a total number of 46 genotype-specific bands, and the total polymorphism produced in the tested landraces was 63.58%. Based on the ISSR data, the polymorphism analysis divided the nine pumpkin landraces into two main groups, two subgroups, and four sub subgroups. The most diverse pumpkin landraces were Alexandria and Sohag, with a similarity percentage of 49.6%. However, the highest calculated similarity value was 88.3% between Matruh and Gharbia. The resultant genotype-specific bands can be used as markers for future genotypic characterization of pumpkins.
Conclusions
The study results could be helpful in the chemical phenotypic characterization and the parental selection and planning for future breeding programs for pumpkin improvement.
... In consideration of the demand for a large number of samples in routine testing, rapid analysis methods are still in urgent need for practical applications. Recently, spectroscopic technology, such as Raman spectroscopy ) and near-infrared (NIR) spectroscopy (Pomares-Viciana et al. 2018), have been preliminarily employed for determining organic acids, mostly due to their quick detection ability and relatively simple process of sample pretreatment (Cortes et al. 2019;Wenlei et al. 2021). Nevertheless, every detection method has both its own merits and demerits (Indurani et al. 2019;Xu et al. 2020b), which make it challenging to meet all the requirements in food analysis using single specific technique because of the complexity and diversity of food matrices. ...
Organic acids are important components in determining fruit taste, and it is necessary to develop rapid analysis methods for them. A simple and effective method based on laser-engraved free-standing terahertz (THz) metamaterials has been developed for rapid analysis of fruit acids. Compared with traditional fabrication methods for THz metamaterials, laser direct writing technology was employed for fabricating the Cu-foil-based THz devices in this research, which is time-saving, cost-effective, and high-throughput. To realize effective fabrication of metamaterials, proper fabrication parameters were selected according to morphology and spectral characterization. Numerical analysis was performed to reveal the fundamental mechanism of THz sensing based on metamaterials. Furthermore, experimental results indicate that fruit acid with a concentration of 0.1 mg L−1 can be successfully distinguished, which is quick and simple compared with traditional acid–base titration. The proposed strategy demonstrates great potential for rapid in situ analysis of flavor components in food products.
... Overall, the most considerable variation occurred in the spectral region between 1300 and 1500 nm and between 1800 and 1950 nm. Other authors have found similar response in these spectral regions for prediction of sugars in other products [52,53]. This effect was similar for all sample types and all parameters evaluated. ...
Proximal sensing for assessing sugarcane quality information during harvest can be affected by various factors, including the type of sample preparation. The objective of this study was to determine the best sugarcane sample type and analyze the spectral response for the prediction of quality parameters of sugarcane from visible and near-infrared (vis-NIR) spectroscopy. The sampling and spectral data acquisition were performed during the analysis of samples by conventional methods in a sugar mill laboratory. Samples of billets were collected and four modes of scanning and sample preparation were evaluated: outer-surface (‘skin’) (SS), cross-sectional scanning (CSS), defibrated cane (DF), and raw juice (RJ) to analyze the parameters soluble solids content (Brix), saccharose (Pol), fibre, pol of cane and total recoverable sugars (TRS). Predictive models based on Partial Least Square Regression (PLSR) were built with the vis-NIR spectral measurements. There was no significant difference (p-value > 0.05) between the accuracy SS and CSS samples compared to DF and RJ samples for all prediction models. However, DF samples presented the best predictive performance values for the main sugarcane quality parameters, and required only minimal sample preparation. The results contribute to advancing the development of on-board quality monitoring in sugarcane, indicating better sampling strategies.
... JP presented the highest carbohydrate content (Table 2), followed by JC and MP. Carbohydrates are essential components to be determined as they include reducing sugars (such as glucose and fructose), non-reducing sugar (sucrose), starches, and cellulose, which play a key role in fruit flavor and structure (Pomares-Viciana, Martínez-Valdivieso, Font, Gómez, & Del Río-Celestino, 2018). Another critical factor is that carbohydrate composition influences probiotic growth. ...
The jerivá (Syagrus romanzoffiana) and the macaúba (Acrocomia aculeata) are palm trees of the Arecaceae family, widely distributed in tropical and subtropical areas of Latin America, which have a low production cost and high productivity throughout the year. Due to the high content of lipids, their fruits have been used for oil extraction, which generates byproducts such as the pulps and the kernel cakes, a nutritionally rich byproduct that can be added into human food and, may have prebiotic potential. Therefore, the objective of this work was to characterize and evaluate the prebiotic potential of jerivá pulp (JP), macaúba pulp (MP), jerivá kernel cake (JC) and macaúba kernel cake (MC). For this, the fruits characterization was carried out through proximate composition, phenolic compounds content, and antioxidant activity, besides evaluating the antimicrobial and fermentative capacity of Bifidobacterium lactis, Lactobacillus casei, and Lactobacillus acidophilus against Escherichia coli. Jerivá and macaúba pulps and kernel cakes presented high levels of dietary fiber (20.45% JP, 37.87% JC, 19.95% MP and 35.81% MC) and high antioxidant activity, especially JP, which also showed the high values found for ABTS and DPPH (2498.49 µMTrolox.g⁻¹ fruit and 96.97g fruit.g⁻¹ DPPH, respectively), has a high total phenolic content (850.62 mg GAE.100 g⁻¹). Also, JP promoted a better growth of probiotic strains and a more relevant pH reduction when compared to the commercial prebiotic FOS. However, MP, JC, and MC were also able to favor the growth of the strains. Probiotic microorganisms were able to use JP, MP, JC, and MC and produced short-chain fatty acids such as lactic, propionic, butyric, and acetic acid, capable of promoting health benefits. Therefore, the byproducts from jerivá and macaúba oil extraction have characteristics that indicate their prebiotic potential, and maybe interesting components to increase the nutritional value of foods.
... They obtained a coefficient of determination of prediction set (r 2 ) of around 0.70-0.80. Pomares-Viciana et al. (2017) developed NIR models to predict the SC of freeze-dried zucchini samples, and the model could be used for screening purposes (r 2 of 0.66 and SEP of 21.29 mg g −1 DW). NIR spectroscopy could become an especially useful selection tool in zucchini breeding programmes and quality control as well. ...
This paper involves the prediction of cassava tuber starch content (SC) using near-infrared (NIR) spectroscopy, aiming to follow the change of SC in individual tubers utilised for a breeding programme. This study applies a portable NIR spectrometer at wavelengths of 570–1031 nm in the evaluation of SC in fresh cassava tubers. The prediction models are established using partial least squares (PLS) regression with NIR spectra obtained in the interactance mode. The effective model was developed from the wavelength region of 600–1000 nm with spectral pre-processing of the second derivative, giving the coefficient of determination of prediction set (r²) and root mean square error of prediction (RMSEP) of 0.62 and 2.21%, respectively. The effect of tuber section (including head, middle and tail) on the performance of the SC model was investigated. The individual head, middle and tail models were acceptable for screening. However, the performances of the combined model (which is the model developed a mix of all individual section samples) and the individual section model were not significantly different. Therefore, the combined model was suitable in real application because of the ease of in-field scanning. The result demonstrates that the SCs of cassava tubers can be measured by a NIR spectroscopy method. Furthermore, it can be used as an alternative tool which is appropriate for breeders to use to follow the behaviour of SC during breeding.
... It is known that courgette fruit contains approximately 93.5-95% of water [16,17] and is thus characterised by very low energy value (21)(22) kcal in 100 g f.w.) [16,18], contributed mainly by carbohydrates (2.3-4.2 g/100 g f.w., including 1.3-3.2 g/100g f.w. of sugars) [16][17][18][19] and proteins (1-2.5 g/100g f.w.) [16][17][18]. The fibre content in courgette reaches 1.1 g/100g f.w. ...
Courgette is considered as a low-calorie vegetable with health-promoting properties. However, scientific publications focused on the profile and content of bioactive compounds in courgette, as well as the potential fruit quality modulating factors, are rare. Due to the high adaptability of courgette to weather and agronomic conditions, it is produced on a global scale. The aim of this study was to analyse the impact of organic versus conventional agronomic practices on the concentration of selected antioxidants in courgette fruits. Fruits of two courgette varieties (Astra Polka and Nimba) produced in an organic and conventional system were tested by high performance liquid chromatography (HPLC) to determine the content of polyphenols (flavonoids and phenolic acids), carotenoids, chlorophylls, and vitamin C. Organic courgette fruits were characterised by their significantly higher content of phenolic acids and flavonoids when compared to the conventionally grown fruit. The organic cultivation might be a good method to increase concentration of bioactive compounds with antioxidant properties in courgette fruits. Nevertheless, the identified trends should be further confirmed, with attention paid to other courgette varieties, as well as to the potential interactions between the plant genotype, agronomic system and the location-specific growing conditions.
... 12 Chemometrics combined with near-infrared reflectance spectroscopy (NIRS) has the potential to provide a faster and more reliable approach for quantification of starch concentrations in various tissues. 13,14 NIRS is a powerful technique that has enabled rapid analysis of various compositional parameters in wine grapes, must and grapevine tissues, 13,15,16 grapevine water potential [17][18][19] and starch. Accurate predictive models of starch have been reported for a range of woody tree systems including grapevine, Vitis spp., 8,20,21 73 tree species 22 and Eucalyptus globulus 23 using dried and ground samples. ...
BACKGROUND
Near‐infrared reflectance spectroscopy (NIRS) technology can be a powerful analytical technique for the assessment of plant starch, but generally samples need to be freeze‐dried and ground. This study investigated the feasibility of using NIRS technology to quantify starch concentration in ground and intact grapevine cane wood samples (with or without the bark layer). A partial least squares regression was used on the sample spectral data and was compared against starch analysis using a conventional wet chemistry method.
RESULTS
Accurate calibration models were obtained for the ground cane wood samples (n = 220), one based on 17 factors (R² = 0.88, root mean square error of validation (RMSEV) of 0.73 mg g⁻¹) and the other based on 10 factors (R² = 0.85, RMSEV of 0.80 mg g⁻¹). In contrast, the prediction of starch within intact cane wood samples was very low (R² = 0.19). Removal of the cane bark tissues did not substantially improve the accuracy of the model (R² = 0.34). Despite these poor correlations and low ratio of prediction to deviation values of 1.08–1.24, the root mean square error of cross‐validation (RMSECV) values were 0.75–0.86 mg g⁻¹, indicating good predictability of the model.
CONCLUSIONS
As indicated by low RMSECV values, NIRS technology has the potential to monitor grapevine starch reserves in intact cane wood samples. © 2020 Society of Chemical Industry
... NIRS also successfully predicted NDF, ADF, and N in canola [26], NDF and ADF in dryland cereal cultivars [14], and ADF and ADL in rice [27]. The use of NIRS is routine for prediction of various traits in many other agricultural crops such as postharvest quality of apples [28], postharvest ripeness and quality of mango [29,30], and carbohydrate content in zucchini fruit [31]. ...
Adoption of no-till systems in Eastern Washington has been slow due to the difficulty of managing wheat (Triticum aestivum L.) straw residue and the unknown decomposition potential of cultivars. We hypothesize that by analyzing wheat straw with near-infrared spectroscopy (NIRS), calibration models can be developed to accurately predict fiber and chemical constituents of wheat, determining straw decomposition potential. Straw from a panel of 480 soft winter wheat cultivars adapted to the Pacific Northwest are analyzed for neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), cellulose, hemicellulose, carbon (C), and nitrogen (N). Using modified partial least squares regression and cross validation techniques, specific environment and broad-based NIRS models are calibrated and predictive ability is validated. R²cal values from broad models are better than the specific models, and are 0.85 (NDF), 0.86 (ADF), 0.65 (ADL), 0.88 (cellulose), 0.42 (hemicellulose), 0.67 (C), and 0.73 (N). The corresponding SEP values are 1.68% (NDF), 1.54% (ADF), 0.62% (ADL), 1.14% (cellulose), 1.11% (hemicellulose), 1.23% (C), and 0.06% (N). A Finch × Eltan breeding population is used to further validate models and prediction accuracies for variety selection within a breeding program scenario. The broad NIRS models prove useful for estimating high and low ranges of NDF, ADF, and cellulose in wheat cultivars which translate into characteristics of slow and fast decomposition potential.
Natural carbohydrates are gaining importance over a wide spectrum of human activity due to their versatile functionalities. The properties of carbohydrates are currently used in many branches of industry and new possibilities of their utilization, like in medicine or materials science, are demonstrated systematically. The attractive properties of carbohydrates result from their chemical structure and ability to form macromolecules and derivatives. Each application of carbohydrate requires a knowledge of their chemical composition, which due to the number and differentiation of monosaccharides and their spatial forms is often challenging. This review presents an overview on sample preparation and the methods used for the determination of the fine chemical structure of natural carbohydrates. Most popular and reliable colorimetric, chromatographic and spectroscopic methods are presented with an emphasis on their pros and cons.
The present study investigated the influence of boiling and grilling deployed at 15, 30, and 45 minutes on selected eggplant and zucchini qualities. The colorants present in these vegetables contribute to their attractive appearance while presenting health-benefit components. This study shows that boiling and grilling differently affected the color properties of the eggplant and zucchini flesh and skin, leading to discoloration. However, the multifactorial mechanisms behind this phenomenon are not yet fully uncovered.
Both boiling and grilling caused softening in examined vegetables within cooking prolongation, but different effects were observed. In the case of grilling, large- and small-deformation mechanical parameters established higher values. Thus, grilling produced firmer samples, which was further projected on mastication and dynamic sensory perception. Although there was limited differentiation in mastication parameters, it was observable that grilled products were more mastication-demanding. The number of chews and consumption time provided most of the information and established higher values for short-time cooking treatments and grilling. As a consequence, samples that had longer in-oral exposure times were perceived as bitter (eggplant) or sweet (zucchini). Oppositely, boiled vegetables were juicier. Regardless of the type of vegetable or cooking method, the shortest cooking treatments resulted in products dominantly perceived as firm.
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An empirical model for the estimation of starch content (SC) and dry matter (DM) in cassava tubers was developed as an alternative method to polarimetry and dry oven. These improved estimation equations were developed based on the specific gravity (SG) method. To improve accuracy, the one hundred-seventy-four sample were obtained from four commercial varieties of cassava in Thailand including KU50, CMR38-125-77, RY9 and RY11, respectively. The age of sample collected from four to twelve months after planting was used in this experiment. The empirical model was created from their relationships between SG obtained from small sample size (~100 g) and its SC and DM. The SG for cassava was strongly correlated with the SC and DM, with values for the coefficient of determination (R2) of 0.81 and 0.83, respectively. The SC showed a high correlation with the DM, with R2 of 0.96. To confirm that the empirical model was effective when applied to other samples, unknown samples collected from another area were tested, and the results showed a standard error of prediction (SEP) of 1.02%FW and 3.49%, mean different (MD) of -0.66%FW, -0.89% for the SC and DM, respectively. Hence, our empirical equation based on a modified SG method could be used to estimate the SC and DM in cassava tubers. It can help breeders to reduce costs and time requirements. Moreover, breeders could be used the methods to evaluate the SC and DM from the tuber formation to harvesting stage and monitoring the changes in SC and DM during breeding.
The gender identification of silkworm pupae is a critical step in the sericulture industry's breeding process. In this study, a low cost, short-wavelength (815-1075 nm) near infrared (NIR) spectrometer combined with multivariate spectra evaluation methods was used to establish calibration models for the on-line identification of female and male pupae of eight silkworm varieties (Hibiscus, Jingsong, 932, Xiang Hui, 7532×Xiang Hui, Haoyue B, Jingsong B, and 7532). The diffuse reflection short-wavelength spectra were recorded, and then principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares discriminant analysis (PLSDA) were tested for calibration model development. The PCA and LDA results showed, that spectral differences between the female and male silkworm pupae existed, however, the two evaluation techniques could not separate the female and male silkworm pupae with the required accuracy. The PLSDA calibration models, on the other hand, could separate the pupae according to their gender with the necessary prediction accuracy of >98.44%. Thus, it has been proved, that a low-cost, short-wavelength range NIR spectrometer in combination with a PLSDA calibration routine can be successfully applied for the reliable on-line identification of female and male silkworm pupae.
The objective of this study was to quantify the chemical content of multiple products using one single calibration model. This study involved seven tuber and root powders from arrowroot, Canna edulis, cassava, taro, as well as purple, yellow, and white sweet potato, for partial least square (PLS) regression to predict polysaccharide contents (i.e., amylose, starch, and cellulose). The developed PLS models showed acceptable results, with R c 2 of 0.9, 0.95, and 0.85 and SEC of 2.7%, 3.33%, and 3.22%, for amylose, starch, and cellulose, respectively. The models also successfully predicted polysaccharide contents with R p 2 of 0.89, 0.95, and 0.79; SEP of 2.83%, 3.33%, and 3.55%; and RPD of 3.02, 4.47, and 2.18 for amylose, starch, and cellulose, respectively. These results showed the potential of Fourier transform near-infrared spectroscopy to quantify the chemical composition of multiple products instead of using one individual model.
Regular consumption of fruits, vegetables, whole grains, and other plant foods has been negatively correlated with the risk of the development of chronic diseases.
The zucchini is a summer squash which can reach nearly a meter in length, but which is usually harvested at half that size or less.
Zucchini are widely used around the world. Their functional components have long been thought to play a key role in modifying the major risk factors for some chronic diseases.
What is the history of the zucchini? Is it used in modern times? Is the zucchini used for culinary purposes? What is its composition? Nutritional value? What are its health giving properties? Are there any adverse effects of consuming zucchini?
A Biblical verse dealing with these issues is studied from a contemporary viewpoint.
Walnut (Carya cathayensis Sarg.) oil contains over 85% of unsaturated fatty acids, which are easily oxidized during storage. As a result, a large number of volatile oxidation compounds (VOCs) are formed during oxidation. The qualitative composition of VOCs in walnut oil and quantitative prediction of the oxidation parameters (peroxide value, acid value and p‐anisidine value) by VOCs were investigated through SPME/GC‐MS combined with partial least‐squares (PLS) regression analysis. Eighteen volatile oxidation compounds including aldehydes, alcohols, and acids were detected by SPME/GC‐MS. According to the comprehensive scores of principal component analysis (PCA), 2‐octenal, hexanal, 2‐heptenal, 1‐octen‐3‐ol, hexanoic acid and nonanal were the main products formed during oxidation. Then PLS regression was applied to developing quantitative prediction models of oxidation parameters (peroxide value, acid value and p‐anisidine value) by VOCs. The PLS prediction models had a good performance, with determination coefficients (R²p) of 0.993‐0.997 for the prediction sets of the three oxidation parameters.
Practical applications: The quantitative relationship between VOCs and oxidation parameters was developed in this study, which provided a new method for monitoring the quality of walnut oil. The SPME/GC‐MS combined with PLSR was a feasible and potential method for simultaneous qualitative and quantitative analysis of oxidation process. This method was proven to have a precise predictive ability and provided a potential application in the quality assessment of other nut products.
The potential of near infrared spectroscopy (NIRS) in the wavelength range of 1000-2500 nm for predicting quality parameters such as total soluble solids (TSS), acidity (TA), firmness, and individual sugars (glucose, fructose, sucrose, and xylose) for two cultivars of apples ("Braeburn" and "Cripps Pink") was studied during the pre- and post-storage periods. Simultaneously, a qualitative investigation on the capability of NIRS to discriminate varieties, harvest dates, storage periods and fruit inhomogeneity was carried out. In order to generate a sample set with high variability within the most relevant apple quality traits, three different harvest time points in combination with five different storage periods were chosen, and the evolution of important quality parameters was followed both with NIRS and wet chemical methods. By applying a principal component analysis (PCA) a differentiation between the two cultivars, freshly harvested vs. long-term stored apples and, notably, between the sun-exposed vs. shaded side of apples could be found. For the determination of quality parameters effective prediction models for titratable acid (TA) and individual sugars such as fructose, glucose and sucrose by using partial least square (PLS) regression have been developed. Our results complement earlier reports, highlighting the versatility of NIRS as a fast, non-invasive method for quantitative and qualitative studies on apples.
Background:
Fruit set is a key process for crop production in tomato which occurs after successful pollination and fertilization naturally. However, parthenocarpic fruit development can be uncoupled from fertilization triggered by exogenous auxin or gibberellins (GAs). Global transcriptome knowledge during fruit initiation would help to characterize the molecular mechanisms by which these two hormones regulate pollination-dependent and -independent fruit set.
Principal findings:
In this work, digital gene expression tag profiling (DGE) technology was applied to compare the transcriptomes from pollinated and 2, 4-D/GA3-treated ovaries. Activation of carbohydrate metabolism, cell division and expansion as well as the down-regulation of MADS-box is a comprehensive regulatory pathway during pollination-dependent and parthenocarpic fruit set. The signaling cascades of auxin and GA are significantly modulated. The feedback regulations of Aux/IAAs and DELLA genes which functioned to fine-tune auxin and GA response respectively play fundamental roles in triggering fruit initiation. In addition, auxin regulates GA synthesis via up-regulation of GA20ox1 and down-regulation of KNOX. Accordingly, the effect of auxin on fruit set is mediated by GA via ARF2 and IAA9 down-regulation, suggesting that both pollination-dependent and parthenocarpic fruit set depend on the crosstalk between auxin and GA.
Significance:
This study characterizes the transcriptomic features of ovary development and more importantly unravels the integral roles of auxin and GA on pollination-dependent and parthenocarpic fruit set.
Zucchini, the richest source of macronutrient and micronutrient content among the vegetables, was dried in
a solar and oven dryer to investigate the effect of So2-pretreatment on loss of macronutrient and micronutrient content and other rehydration and color characteristics. The effect of solar and oven drying on the nutrients and non-nutrients composition of zucchini (green squash) rings was determined. Results indicated that the macronutrient and micronutrient contents were highest in So2-treated solar and So2-treated oven dried zucchini slices samples compared with untreated or fresh sample. Ash, carbohydrates and protein contents of solar (14.3, 54.32 and 15.55 %) and oven (15.42, 53.05 and 16.43 %) dried samples were increased compared to fresh (1.29, 2.32 and 2.58 %) samples, respectively. Solar and oven drying were found to increase energy content compared to fresh samples. Increases of all mineral elements contents upon So2-solar and So2-oven drying with exception of potassium were observed. So2-solar and So2-oven drying were found to increase vitamin C, total chlorophyll, total carotenoids and total phenol contents compared to fresh samples. The rehydrated moisture content, rehydration ratio, coefficient of rehydration and shrinkage ratio were also found to be maximum for the So2-treated solar dried zucchini slices sample. Also, the most effective pre-treatment for the inhibition of oxidative enzymes (PPO), good colour characteristics and lower non-enzymatic browning in solar and oven dried zucchini rings was So2 -pretreated. Solar drying may be the preferred method of drying the zucchini (green squash) rings as it is faster, more hygienic and better preserves the nutrients.
Parthenocarpy is an important trait determining yield and quality of fruit crops. However, the understanding of the mechanisms underlying parthenocarpy induction is limited. Cucumber (Cucumis sativus L.) is abundant in parthenocarpic germplasm resources and is an excellent model organism for parthenocarpy studies. In this study, the transcriptome of cucumber fruits were studied using RNA-sequencing. Differentially expressed genes (DEGs) of setted fruits were compared against abortive fruits. Distinctive features of parthenocarpic and pollinated fruits were revealed by combining the analysis of the transcriptome, together with cyto-morphological and physiological analysis. The cell division and the transcription of cell division genes were found to be more active in parthenocarpic fruit. The study also indicated that parthenocarpic fruit set is a high sugar-consuming process which is achieved via enhanced carbohydrate degradation through transcription of genes that lead to the breakdown of carbohydrates. Furthermore, the evidence provided by this work supports a hypothesis that parthenocarpic fruit set is induced by mimicking the processes of pollination/fertilization at the transcriptional level, i.e. by performing the same transcriptional patterns of genes inducing pollination and gametophyte development as in pollinated fruit. Based on the RNA-sequencing and ovary transient expression results, 14 genes were predicted as putative parthenocarpic genes. The transcription analysis of these candidate genes revealed auxin, cytokinin, and gibberellins crosstalks at transcriptional level during parthenocarpic fruit set.
This study evaluated the influence of NPK fertilizer on protein, fibre, ash, fat, carbohydrate, antioxidant activities and antioxidant phenolic compounds in immature and mature fruits of pumpkin. The treatment consisted of six NPK levels (0, 50, 100, 150, 200 and 250 kg/ha), and was replicated six times in a randomized complete block design (RCBD). Proximate analysis and antioxidant assays were done using standard analytical methods. At control and lower NPK rates, the proximate compositions and antioxidant profile of pumpkin fruits decreased with increasing NPK fertilizer. Between the control and the highest fertilizer rate, proximate compositions decreased by 7-62% while the antioxidant profile decreased by 13-79% for both immature and mature fruits. Across all the measured parameters, mature fruit had higher proximate contents and higher antioxidant concentrations. For the high health value of pumpkin fruits to be maintained, little or no NPK fertilizer should be applied.
ABSTRACTA reversed-phase HPLC method using a Spherisorb NH2 column and 85:15 v/v acetonitrile/water as mobile phase was developed for determination of starch and soluble sugars (glucose, fructose and sucrose) in plants. When applied to pure starch samples, the analytical method was as accurate as the official AOAC method and had better precision (coefficient of variation 0.87% vs 1.27%). When applied to green bean (Phaseolus vulgaris L.), recovery was 97.7% for starch, 98.0% for glucose and 98.1% for both fructose and sucrose.
Acoustic impulse resonance frequency sensor and miniaturized VIS/NIR spectrometer were applied on apple fruit Malus domestica ‘Idared’ and ‘Golden Delicious’ (n = 800) to predict fruit flesh firmness and soluble solids content (SSC) on tree and in shelf life. Partial least-squares calibration models on acoustic data and VIS spectra of ‘Golden Delicious’/‘Idared’ apple fruits on tree were built for predicting the fruit flesh firmness: coefficients of determination (R2) and standard errors of cross-validation (SECV) of R2 = 0.93/0.81 and SECV = 7.73/10.50 [N/cm2] were calculated. SSC prediction of freshly harvested apples using NIR spectrometry was obtained with R2 = 0.20/0.41 and SECV = 1.29/0.94 [°Brix]. Prediction of SSC and fruit flesh firmness of stored ‘Golden Delicious’/‘Idared’ apple fruits showed high errors or was not possible.The fruit maturity stage on tree was predicted as classes based on calendar weeks for ‘Golden Delicious’/‘Idared’ apple fruits with 64%/66% correct classification and 92%/84% correct plus neighboring class with SECV = 0.9/0.9 [weeks]. Classes of ‘Golden Delicious’/‘Idared’ apple fruit at different quality levels due to different storage conditions were non-destructively discriminated with 77%/84% correctly classified fruits and 93%/99% correct plus neighboring class with SECV = 0.8/0.5 [classes].The results show the potential of non-destructive sensors for predicting accepted fruit parameters enabling the determination of optimum harvest date and fruit quality in shelf life.
Oil from pumpkin seeds has been widely used in the treatment of prostatic hyperplasia. In the present paper, the effect of lipophilic extract of Cucurbita pepo L seeds (ELMSC) was studied in an in vivo model of testosterone propionate -induced experimental prostatic hyperplasia during 15 days. It was found that ELMSC at doses of 400 and 200 mg/kg caused a significant decrease of prostatic growth. Our findings showed that doses of ELMSC over 200 mg/kg inhibits the testosterone-induced prostatic growth in the experimental model of prostatic hyperplasia in rats.
The sweetness of various sweet substances, such as sugars, synthetic sweetners, and amino acids were evaluated by sensory analysis. The relative sweetness varied in many ways as the concentration increased and the quantitative relationships between the sweetness and the concentration were established. The substances were clasified according to their patterns of the taste intensity curves.
The sweetness of various sweet substances, such as sugars, synthetic sweetners, and amino acids were evaluated by sensory analysis. The relative sweetness varied in many ways as the concentration increased and the quantitative relationships between the sweetness and the concentration were established. The substances were clasified according to their patterns of the taste intensity curves.
A new genetic resource for Cucurbita pepo has been developed with chemically induced mutagenesis. The seeds of the zucchini cultivar MU-CU16 were treated with 40 mM–80 mM ethyl methanesulfonate (EMS), reaching high germination rates between 70 and 85%. However, most plants of those M1 populations did not produce offspring, and the fertility rates were lower in plants treated with higher concentrations of EMS. Once we established that visual flower abnormality rates were not sufficient to explain low fruit yield, pollen viability was analysed with fluorochromatic reaction. Compared with untreated plants, treatment with EMS produced a substantial decrease in pollen viability, and only the group of plants with pollen viability rates higher than 45% yielded nearly 70% of fruits with seeds. Therefore, the main issues to be addressed for developing mutant lines in this species are to increase the number of mutations in the genome and to increase the number of mutant lines with sufficient fertility. In this case, the early plantlet selection for high pollen viability carried out as part of this work represents a useful tool for use in future breeding programs by mutagenesis, allowing an increase of up to 40% in the production of mutant lines for a dosage of 65 mM EMS.
A user-friendly guide to Multivariate Calibration and Classification provides a readable text, for non-mathematicians, as an introduction with little or moderate knowledge of chemometrics. It is aimed specifically at readers using chemometrics in the context of near infrared (NIR) spectroscopy. The techniques described are, however, much more widely applicable. Thus, although the columns were our starting point, our aim in rewriting and expanding them was to make this book a useful one for any chemometrics practitioner. Most of the examples still involve NIR spectroscopy, and some material that is specific to this application has been included, but we have tried to emphasise the generality of the approaches where ever possible.
NIR Spectroscopy ability was investigated to assess the fruit structure effect (passion fruit, tomato and apricot) on prediction performance of soluble solids content (SSC) and titratable acidity (TA). Relationships between spectral wavelengths and SSC and TA were evaluated through the application of chemometric techniques based on partial least squares (PLS). Good prediction performance was obtained for apricot with correlation coefficients of 0.93 and 0.95 for SSC and TA and root mean square errors of prediction (RMSEP%) of 3.3% and 14.2%, respectively. For the passion fruit and tomato, the prediction models were not satisfactorily accurate due to the high RMSEP. Results showed that NIR technology can be used to evaluate apricot internal quality, however, it was not appropriate to evaluate internal quality in fruits with thick skin, (passion fruit), and/or heterogeneous internal structure (tomato).
The prediction accuracy of models based on visible-short wavelength near infrared spectra (VIS–SWNIR; 500–1050nm) collected from intact fruit using a partial transmittance optical geometry was considered for dry matter (DM) and total soluble solids (TSS) content of mesocarp tissue of banana (Musa acuminata, cv. Robusta) and mango (Mangifera indica, cv. Keitt) fruit. The DM content was modelled well across all stages of maturity for mango, with a cross validation correlation coefficient of determination (Rcv2)>0.75 and root mean square error of cross-validation (RMSECV) of 0.75, RMSECV0.85) with skin colour (Hunter a and a/b) in the populations assessed. VIS–SWNIR is recommended for assessment of the ripening stage of mango and banana fruit and for assessment of DM in intact mango, but not banana fruit. The technique is also not recommended for assessment of TSS content across ripening stages of banana or mango fruit.
Particle size, scatter, and multi-collinearity are long-standing problems encountered in diffuse reflectance spectrometry. Multiplicative combinations of these effects are the major factor inhibiting the interpretation of near-infrared diffuse reflectance spectra. Sample particle size
accounts for the majority of the variance, while variance due to chemical composition is small. Procedures are presented whereby physical and chemical variance can be separated. Mathematical transformations—standard normal variate (SNV) and de-trending (DT)—applicable to individual
NIR diffuse reflectance spectra are presented. The standard normal variate approach effectively removes the multiplicative interferences of scatter and particle size. De-trending accounts for the variation in baseline shift and curvilinearity, generally found in the reflectance spectra of
powdered or densely packed samples, with the use of a second-degree polynomial regression. NIR diffuse NIR diffuse reflectance spectra transposed by these methods are free from multi-collinearity and are not confused by the complexity of shape encountered with the use of derivative spectroscopy.
A filter based near infrared (NIR) technique to evaluate Brix value, in a non destructive way, of Indian apples, along with apples from other countries, has been investigated here. Reflectance characteristics at ten NIR wavelengths were recorded by in-house developed probe for five Indian varieties and four imported varieties. A separate calibration and validation set for each variety was formed. Brix values of the calibration and validation sets of apples were evaluated with a refractometer from Bellingham and Stanley, Model 840. Principal component regression was used to generate calibration and prediction of Brix for the validation set. It was found that Brix values of all varieties of apples can be predicted with a standard error of prediction, 0.7322–1.7809, while root mean square error is also in the same range. It was further noticed that reduction in data recording wavelength leads to an increase in SEP and RMSE.
The computer programs CENTER and SELECT have been presented as a way to establish population boundaries and choose samples for near infrared calibrations. This study was conducted to evaluate calibrations derived on samples chosen by CENTER and SELECT from broad groups of hay, haylage, corn ( Zea mays L.), wheat ( Triticnm aestivum L.), and barley ( Hordeum vulgare L.) samples. Population boundaries were established with a maximum standardized H distance from the average spectrum of 3.0. Every fifth sample was reserved for equation validation. Calibration samples were selected with a minimum standardized H distance between samples of 0.6. Forage samples were found to have more diverse spectra and chemistry than grain samples. Average r ² values were smaller, numbers of eigenvectors were larger, and standard deviations of laboratory reference values were larger for forages than for grains. The standard error of performance (SEP) for all samples and SEP for samples chosen by SELECT with a limit of 0.6 were similar for four of five products. Calibrations were developed using five different math treatments with and without multiplicafive scatter correction (De‐trend). First derivative was the best math treatment for protein in all products. Second derivative was best for acid‐detergent fiber (ADF) in forage products, but no single math treatment was superior for ADF in grain products. De‐trend improved SEP in 28 of 50 calibrations.
Six varieties of winter squashes were studied to determine the differences between and effect of storage on the total sugar and starch content and the extent to which varietal differences and changes in these constituents were associated with preference. Increases in total sugar content resulted in varietal differences during storage. Varietal differences in starch content varied depending on the extent and rate of decrease in starch during storage. While the major sugar accumulation occurred within the first 5 weeks of storage with little or no change thereafter, starch decreased in an exponential fashion throughout storage. The sugar-starch ratio was approximately the same for all six varieties at harvest, and increased to approximately 1.00 after 5 weeks of storage. Subsequent increases in the ratio, due primarily to continuous decrease in starch, differed between varieties. Varietal differences in acceptability appear to be related to the sugar-starch ratio and total solids content as well as the absolute amount of total sugar and starch.
Two sensitive wavelength (SWs) selection methods combined with visible/near-infrared (Vis/NIR) spectroscopy were investigated to determine the soluble solids content (SSC) and pH value in peaches, including latent variables analysis (LVA) and independent component analysis (ICA). A total of 100 samples were prepared for the calibration (n = 70) and prediction (n = 30) sets. Calibration models using SWs selected by LVA and ICA were developed, including linear regression of partial least squares (PLS) analysis and nonlinear regression of least squares-support vector machine (LS-SVM). In the nonlinear models, four SWs selected by ICA achieved the optimal ICA-LS-SVM model compared with LV-LS-SVM and both of them better than linear model of PLS. The correlation coefficients (r
p and r
cv), root mean square error of cross validation, root mean square error of prediction, and bias by ICA-LS-SVM were 0.9537, 0.9485, 0.4231, 0.4155, and 0.0167 for SSC and 0.9638, 0.9657, 0.0472, 0.0497, and −0.0082 for pH value, respectively. The overall results indicated that ICA was a powerful way for the selection of SWs, and Vis/NIR spectroscopy incorporated to ICA-LS-SVM was successful for the accurate determination of SSC and pH value in peach.
During the ripening season, measurements were performed on 4 grape varieties (i.e. Cabernet Sauvignon, Merlot, Syrah and Carmenère). Spectral reflection measurements were performed on intact grapes using the Zeiss corona 45 VIS–NIR spectrophotometer. Thereafter, the concentration of extractable anthocyanins at pH equal to 1.0 (pH10) and 3.2 (pH32), the concentration of polyphenols (IPT), the concentration of sugars (OH) and the density were determined from the samples. Partial least squares analysis showed that prediction of PH10 and PH32 was possible for Syrah. For this variety, PH10 and PH32 increased during the season and changes in the spectral properties of the grapes could be linked to these parameters. For all other varieties, the parameters PH10 and PH32 remained fairly constant over time and the results showed that prediction was not possible. The prediction of IPT was not possible for all varieties. The prediction of OH and density was achieved accurately for all varieties. An important region for the prediction of OH and density was detected around 700 nm, corresponding to the red colour. The prediction of sugar is consequently, at least partially, feasible due to the co-occurring colour change from green to blue/red.
A non-destructive optical method based on near-infrared spectroscopy has been used for the evaluation of apricot fruit quality. Diffuse reflectance measurements (800–2500 nm), physical, physiological and biochemical measurements were performed individually on 877 apricot fruits from eight contrasted cultivars harvested at different ripening stages. Relationships between spectral wavelengths and quality attributes were evaluated by application of chemometric techniques based on partial least squares (PLS) on fruit set divided randomly into two groups: 598 fruits for calibration and 279 for validation. Good prediction performance was obtained for soluble solids and titratable acidity with correlation coefficients of 0.92 and 0.89 respectively and root mean square errors of prediction of 0.98% Brix and 3.62 meq 100 g−1 FW respectively. For the other quality traits such as firmness, ethylene, individual sugars and organic acids, the prediction models were not satisfactorily accurate due to the high error of calibration and prediction.
In the Mediterranean region, zucchini squash (Cucurbita pepo L.) is widely grown under unheated greenhouse conditions for off-season production. Climatic conditions affecting both radiation and water use are mainly determined by the planting dates. Elucidating the relationship between the radiation and the water use with climate variables is important for the quantification of crop productivity and for improving water use efficiency (WUE) and radiation use efficiency (RUE). The influence of seasonal fluctuations (spring–summer and summer–fall) resulting from two planting dates (28 March and 6 September) on growth, radiation and water use efficiencies was investigated in zucchini plants cultivated hydroponically in a unheated greenhouse located at Viterbo, central Italy. Plants grown in the spring–summer season exhibited a higher maximum value of total, leaf, stem, fruit dry matter and leaf area index (971, 460, 91, 422 g m−2 and 5.1, respectively) than those grown during the summer–fall season (672, 306, 58, 311 g m−2 and 2.7, respectively). The marketable fresh yield in the spring–summer was higher than the summer–fall (6.2 versus 4.7 kg m−2). The canopy extinction coefficient was empirically determined as 0.72 for the light interception. The crop coefficient (Kc) during the spring–summer period ranged from 0.10 to 1.15, while for the summer–fall season the Kc ranged from 0.12 to 0.80. Before harvest initiation, the transpiration rates, RUE and water use efficiency calculated on above dry weight basis (WUEb) were similar between growing seasons (average 0.51 L m−2 day−1, 2.07 g MJ−1 and 2.92 g kg−1, respectively), while after harvest initiation, summer–fall season showed a lower transpiration rate (0.97 versus 2.60 L m−2 day−1) and a higher RUE (4.17 versus 2.46 g MJ−1) and WUEb (4.02 versus 2.73 g kg−1) in comparison to the spring–summer season. Water use efficiency on fresh fruit yield basis (WUEy) was also higher in summer–fall season compared to spring–summer season (50.5 versus 31.5 g kg−1). The variability in RUE and WUEb was associated with, daily mean solar radiation (Rs), daily mean air temperature (Ta) and daily mean vapour pressure deficit (VPD). In both growing phases, negative exponential relationships were evident by plotting the RUE, and WUEb against climatic variables (Rs, Ta and VPD). Rs, Ta and VPD were greatly higher in the spring–summer season, which influences RUE and WUEb negatively.These results may be applied in greenhouse climate control and management decisions. In our case the use of light selective and movable screen may improve substantially water use efficiency of warm season crops in Mediterranean areas, where water supplies are limited.
Melon is one of the economically important and widely cultivated vegetable crops in the world. There is a wide genetic diversity in the cultivated and wild species of melon. Melon as one of the most consumed fruits, the development and ripening of fruit is known to be a complex developmental process that involves many biochemical and physiological changes including the breakdown of chlorophyll, degradation of the cell wall, increase in sugars content, alteration in pigment biosynthesis, and the accumulation of flavour and aromatic compounds. However, the information on genetic engineering and molecular biology of melon is very limited. With the development of genetics and molecular biology, a large number of quality/ripening-regulated genes involved in pigmentation, vitamin, soluble carbohydrate metabolism, cell wall metabolism and ethylene biosynthesis have been identified in melons. Some genetic manipulations of melons have been proved to be useful technology to improve quality, sensory attributes, shelf life and other agronomic traits of melon fruit. This paper reviewed some progresses in the trangenic approach to improve quality traits of melon fruit.
Bayberry plays an important role in the nutrition and is a very important fruit-product. It has a high economic and officinal value. In this study, glucose, fructose and sucrose in bayberry juice were detected and quantified using near-infrared (NIR) spectroscopy. The HPLC method was assumed to provide the reference value of the analyte for calibration. Partial least-squares regression (PLSR) was used to construct calibration models with different pre-processing methods. The number of PLS factors was optimised. The results show PLS models are good for predicting glucose, fructose and sucrose concentrations in bayberry juice, and their prediction accuracy can be improved by using derivative process with the exception of the glucose. The best models were mostly given by the second derivative processed spectra, especially for sucrose with the determination coefficient, R2 of 0.9931. This demonstrates the potential of NIR spectroscopy to quickly detect these components simultaneously in bayberry juice with the reference method of HPLC.
A rapid, reliable, and nondestructive method for quality evaluation of mango (Magnifera indica) fruit is important to the mango industry for international trade. The objective of this study was to determine the potential of near-infrared (NIR) spectroscopy to predict soluble solids content (SSC) and individual and combined concentrations of sucrose, glucose, and fructose nondestructively in mango. Mature mangoes at two different temperatures (15 °C and 20 °C) were measured by NIR interactance (750-1088 nm wavelength region analyzed) over an 11-day period, starting when the fruit were underripe and extending to a few days past optimal ripeness. Partial least squares regression was used to develop models for SSC, individual sugar concentration, and the sum of the concentrations of the three sugars. Such analyses yielded calibration equations with R2 = 0.77 to 0.88 (SSC), 0.75 (sucrose), 0.67 (glucose), 0.70 (fructose), and 0.82 (sum); standard error of calibration = 0.56 to 0.90 (SSC), 10.0 (sucrose), 0.9 (glucose), 4.5 (fructose), and 10.4 (sum); and standard error of cross-validation = 0.93 to 1.10 (SSC), 15.6 (sucrose), 1.4 (glucose), 6.9 (fructose), and 16.8 (sum). When the SSC calibration was applied to a separate validation set, the standard error of performance ranged from 0.94% to 1.72%. These results suggest that for assessment of mango ripeness, NIR SSC calibrations are superior to the NIR calibrations for any of the individual sugars. This nondestructive technology can be used in the screening and grading of mangoes and in quality evaluation at wholesale and retail levels.
Abiotic environmental stresses such as drought, salinity and low temperature are major limitations for plant growth and crop productivity. Certain plants, marine algae and bacteria have evolved a number of adaptations to such abiotic stresses: some of these adaptations are metabolic and others structural. Accumulation of certain organic solutes (known as osmoprotectants) is a common metabolic adaptation found in diverse taxa. These solutes protect proteins and membranes against damage by high concentrations of inorganic ions. Some osmoprotectants also protect the metabolic machinery against oxidative damage. Many major crops lack the ability to synthesize the special osmoprotectants that are naturally accumulated by stress-tolerant organisms. Therefore, it was hypothesized that installing osmoprotectant synthesis pathways is a potential route to breed stress-tolerant crops. Proving this, recent engineering efforts in model species led to modest but significant improvements in stress tolerance of transgenic plants. Synthetic pathways to two kinds of osmoprotectants—polyols and quaternary ammonium compounds—are discussed here. Results from the metabolic engineering experiments emphasize the need for a greater understanding of primary metabolic pathways from which osmoprotectant synthesis pathways branch. Future research avenues include the identification and exploitation of diverse osmoprotectants in naturally stress-tolerant organisms, and the use of multiple genes and reiterative engineering to increase osmoprotectant flux in response to stress. High-throughput genomic technologies offer a number of tools to refine this by rapidly identifying genes, pathways, and regulatory controls. Copyright 2000 Annals of Botany Company
The effect of exogenous polyamines on electrolyte leakage, chilling index, polygalacturonase activity (PG), ethylene production, and firmness in zucchini squash fruits stored for 12 days at 2 degrees C or 10 degrees C, 85-90% RH was evaluated. Fruits were infiltrated with putrescine (PUT) spermidine (SPD) and spermine (SPM) at 0.1, 0.25, 0.5, 2.0, and 4.0 mM. All polyamines exerted a protective effect on cell and organelle membranes. The most effective was SPD, which reduced electrolyte leakage between 62% and 82%, compared to control fruits stored at 2 degrees C. At 10 degrees C they did not exhibit chilling injury (CI) symptoms, while at 2 degrees C SPM (0.5 mM) and SPD (0.5 mM) diminished them 92% and 100%, respectively; which extended storage life for 8-10 days at 2 degrees C. High concentrations of polyamines (>2.0 mM) caused the appearance of CI symptoms. PG activity diminished proportionally to the concentration of polyamine except for the concentration at 4.0 mM. No significant changes were observed in ethylene production.
A wild tomato species, Lycopersicon chmielewskii, accumulates high levels of soluble sugar in mature fruit and, unlike the domesticated tomato species, Lycopersicon esculentum, accumulates sucrose rather than glucose and fructose. Genetic and biochemical analyses of progeny resulting from a cross of L. chmielewskii with L. esculentum have previously indicated that the trait of sucrose accumulation is controlled by a single recessive gene and is associated with low levels of acid invertase protein in the developing fruit. Analysis of progeny from the BC2F3 generation from the L. esculentum x L. chmielewskii cross revealed that sucrose-accumulating fruit accumulate sugar in two phases corresponding to fruit expansion and fruit maturation and that the majority of the sucrose was stored in the latter phase after the fruit had reached maximum size. The only significant enzymic difference between the sucrose-accumulating and hexose-accumulating fruit was the lack of acid invertase activity in sucrose-accumulating fruit. Sucrose phosphate synthase activity did not increase in the sucrose-accumulating fruit during late development when the rate of sucrose accumulation increased. The lack of acid invertase activity in sucrose-accumulating fruit was correlated with inheritance of the L. chmielewskii acid invertase gene and the absence of acid invertase mRNA in developing fruit. This suggests that the L.chmielewskii invertase gene is transcriptionally silent in fruit and that this is the basis for sucrose accumulation in progeny derived from the interspecific cross of L. esculentum and L. chmielewskii.
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