Texture Prediction in Intact Green Asparagus by Near Infrared (NIR) Spectroscopy,Assaying Linear and Non-linear Regression Strategies

Texture-related parameters were assessed in intact green asparagus at harvest and during postharvest storage using near-infrared spectroscopy combined with MPLS and LOCAL algorithms. Three spectrophotometers were evaluated for this purpose: a monochromator (range, 400–2,500 nm), a diode-array Vis–NIR spectrophotometer (range, 400–1,700 nm), and a handheld micro-electro-mechanical system (MEMS) spectrophotometer (range, 1,600–2,400 nm). Three hundred green asparagus spears (cv. “Grande”) were used to obtain calibration models based on reference data and NIR data. Results for maximum shear force showed that LOCAL algorithm improved the predictive capacity of models constructed using all three NIRS instruments, increasing r ² by 24, 16, and 56 % and reducing the SEP(c) values by 11, 8, and 14 %, respectively. For cutting energy, the LOCAL also improved the predictive capacity of the models (r ² increased by 3 % for the monochromator and the diode-array instrument and by 6 % for the MEMS device; and the SEP(c) decreased by 3 % in the three instruments). It is worth noting that while the monochromator and diode-array instruments displayed similar predictive capacity for the parameters tested, the MEMS instrument achieved slightly poorer results but has clear advantages for the measurement of texture in intact asparagus, being economical, portable, and easy to use in situ.     

First steps towards the development of a non-destructive technique for the quality control of wine grapes during on-vine ripening and on arrival at the winery

NIR spectroscopy was used as a non-destructive technique for the assessment of changes in certain internal quality properties of wine grapes (Vitis vinifera L.) during on-vine ripening and at harvest. A total of 108 different wine grape samples were used to construct calibration models based on reference data and NIR spectral data, obtained using a commercially-available diode-array spectrophotometer (380-1700 nm). The feasibility of testing bunches of intact grapes was investigated and compared with more traditional methods of presentation, such as berries or must. Predictive models were constructed to quantify changes in soluble solid content (SSC, °Brix), reducing-sugar content (g/l), pH-value, titrable acidity (g/l tartaric acid), tartaric acid (g/l) and malic acid (g/l), these being the major parameters used to chart ripening. NIRS technology provided good precision for the bunch analysis mode assayed for SSC (r² = 0.89; SECV = 1.41 °Brix), for reducing-sugar content (r² = 0.87; SECV = 17.13 g/l) and for pH-value (r² = 0.69; SECV = 0.19). Models developed for testing other fruit acidity parameters yielded results sufficient to provide a screening tool to distinguish between low and high acidity values in intact grapes. Significantly, the results obtained with bunch presentation were similar to those obtained with berries and must, thus justifying further implementation of NIRS technology for the non-destructive analysis of quality properties both during on-vine ripening and on arrival at the winery. This method allows musts to be processed separately depending on initial grape quality, assessed with a single spectrum measurement and in a matter of seconds.     

Non-destructive characterization and quality control of intact strawberries based on NIR spectral data

External and internal quality parameters of strawberries (Fragaria x ananassa Duch.) were studied at harvest and during postharvest refrigerated storage using a handheld micro-electro-mechanical system (MEMS) near-infrared spectrophotometer. A total of 189 strawberry punnets were used to develop calibration models using various spectral signal pretreatments and linear and non-linear regression algorithms; the sampling unit for both NIRS analysis and reference methods comprised 5 strawberries from each punnet. Modified partial least squares analysis confirmed the feasibility of NIRS for predicting color-related external quality parameters (L^∗, a^∗ and C^∗) as well as firmness, soluble solid content and titratable acidity. For other tested parameters (b^∗, h^∗ and pH), the results suggested that NIRS prediction was not feasible. However, the application of a LOCAL algorithm considerably improved the ability of models to predict all the internal quality parameters studied. Use of the LOCAL algorithm proved valuable in minimizing the error in NIRS models for predicting complex internal quality parameters, mainly those related to texture and acidity. Subsequently, the ability of NIR technology to classify individual strawberries as a function of variety was tested using partial least squares discriminant analysis (PLS-DA), which yielded percentages of correctly classified samples (ratio of correctly classified samples to total samples) ranging from 57% for the Camarosa variety to 78% for Antilla Fnm.     

Postharvest shelf-life discrimination of nectarines produced under different irrigation strategies using NIR-spectroscopy

Quick assessment of storage time in fruits is important for both growers and consumers due to the fresh fruit market is becoming increasingly demanding with regard to product quality. This study sought to evaluate the ability of near-infrared reflectance spectroscopy (NIRS) to classify intact nectarines in post-harvest storage, as a function of pre-harvest irrigation strategies applied and post-harvest cold storage duration. A total of 220 nectarine fruits (Prunus persica (L.) Batsch cv. ‘Sweet Lady’) were sampled after 7, 14, 21 and 28 days of refrigerated storage (0 °C, 95% RH) and at commercial harvest time. Two commercially-available spectrophotometers were evaluated for this purpose: a handheld MEMS spectrophotometer of 1600-2400 nm and a diode-array Vis/NIR spectrophotometer of 400-1700 nm. Models developed using partial least squares 2-discriminant analysis (PLS2-DA) correctly classified between 86 and 96% of samples by post-harvest storage time using the handheld instrument, and between 66 and 89% in the case of the diode-array spectrophotometer. Classification models based on pre-harvest irrigation treatment classified 57-84% of the samples correctly, due to the similarity in physical-chemical properties of fruits in both irrigation strategies. These results showed that NIRS could be used to monitor changes in nectarine quality parameters during pre- and post-harvest as an essential tool for decision-making both in-field and on-line.     

Apples Nutraceutic Properties Evaluation Through a Visible and Near-Infrared Portable System

Non-destructive and rapid tools are required for predicting the optimum harvest window and for monitoring fruit quality during postharvest period. This study tested a portable, experimental visible/near-infrared (vis/NIR) spectrophotometer, more versatile and handy than traditional vis/NIR instruments, to measure phytonutrients active in human health and important in fruit storability. Parameters determining sensorial and quality properties of the fruit were also analyzed. The vis/NIR measurement was carried out in field using apples of “Golden Delicious” and “Stark Red Delicious” on tree. Calibration models were developed using PLS regression based on second derivative spectra. For “Golden Delicious” apple, the cross-validation R ² for soluble solids content (SSC), chlorophyll, titratable acidity (TA), flesh firmness, total phenols, carotenoids, and ascorbic acid were 0.72, 0.86, 0.52, 0.44, 0.09, 0.77, and 0.50, respectively. The corresponding RMSECV were 0.78 °Brix, 0.50 nmol/cm², 0.59 g/L, 6.08 N, 0.10 mg/g, 0.08 nmol/cm², and 0.83 mg/100 g, respectively. For “Stark Red Delicious” similar calibration statistics were found for SSC, TA, flesh firmness, chlorophyll, and ascorbic acid content. A better calibration performance was achieved for total phenols, while for carotenoids it was less accurate. Cross-validation R ² for “Stark Red Delicious” total anthocyanins, total flavonoids, and non-anthocyanic flavonoids were 0.67, 0.86, and 0.77, respectively. The corresponding RMSECV were 0.12, 0.14, and 0.15 mg/g, respectively. It was concluded that the portable vis/NIR instrument performed similarly to bench top or portable vis/NIR instruments reported in the literature.     

Characterisation of peach juices obtained from cultivars Redhaven,Suncrest and Maria Marta grown in Italy

The compositions of three peach juices obtained from the cultivars Redhaven, Suncrest and Maria Marta, respectively, were studied. The fruits were grown in the Emilia-Romagna region (Italy). The juices were characterised by pH, CIE L*, a*, b* colour values, soluble solids, individual carbohydrates, organic acids, and phenolic compounds. Univariate analysis disclosed some significant differences among the compositions of the varietal peach juices. Principal component revealed clear group structures in the data matrix, the most relevant variables being glucose, fructose, sorbitol, malic acid, L* and b*-values. Suncrest peach juice was clearly distinguished from Redhaven and Maria Marta juices.     

近红外漫反射无损检测赣南脐橙中可溶性固形物和总酸

目的:利用近红外漫反射无损检测技术对赣南脐橙可溶性固形物和总酸含量进行相关研究。方法:通过自行设计的NIR光谱系统测定150个赣南脐橙可溶性固形物和总酸。120个赣南脐橙样品用来建模,其余30个用来验证模型的性能。采集完整赣南脐橙的近红外漫反射光谱(350～1800nm),光谱经移动窗口平滑处理、一阶微分和二阶微分预处理后,再分别采用主成分回归(PCR)和偏最小二乘法(PLS),建立赣南脐橙可溶性固形物和总酸含量的定量预测数学模型。结果:采用一阶微分结合偏最小二乘法所建模型的预测效果较好,可溶性固形物和总酸含量定量预测数学模型的相关系数分别为0.9263和0.9562,均方根误差分别为0.4102°Brix和0.018%。结论:近红外漫反射光谱作为一种无损的检测方法,可用于评价赣南脐橙的可溶性固形物和总酸含量。     

Change in Rind, Flesh, and Juice Color of Blood Oranges Stored in Air Supplemented with Ethylene or in Oxygen-Enriched Atmospheres

Ruby, Tarocco, and Sanguinello blood oranges were stored 4 wk at 15°C in flowing air, 20 ppm ethylene in air, 40% O₂+ 60% N₂, or 80% O₂+ 20% N₂, followed by storage in air. Ethylene caused rind color of Ruby and Tarocco oranges to become deeper orange while 80% O₂ caused rind of Ruby and Sanguinello oranges to be paler orange than when stored in other atmospheres. Ethylene deepened red color of the flesh and juice of Ruby and Tarocco oranges, but high O₂ more intensely deepened the red color of flesh and juice of all three cultivars. Total soluble solids content, total acidity, or pH of the juice was not affected. Fruit stored in the ethylene atmosphere developed off-flavor.     

Discrimination between Chinese rice wines of different geographical origins by NIRS and AAS

The feasibility of near infrared spectroscopy (NIRS) for discrimination between Chinese rice wine of different geographical origins (Shaoxing and Jiashan, China) is presented in this research. NIR spectra were collected in transmission mode in the wavelength range of 800–2500 nm. Qualitative analysis models were developed based on partial least squares regression (PLSR). The prediction performance of calibration models in different wavelength range was also investigated. The best models gave a 100% classification of wines of the two geographical origins in the range of 1300–1650 nm. The content of trace metals (potassium, magnesium, zinc, and iron) was also investigated to classify wines of the two categories by atomic absorption spectroscopy (AAS). The AAS results were in agreement with NIRS, with 100% classification for wines of the two categories. In addition, the correlation between NIRS and AAS was also investigated by PLSR. Potassium and magnesium were well predicted by quantitative models based on NIR spectra and AAS data. The correlation coefficient of calibration (R _cal) for potassium and magnesium were 0.958 and 0.885, respectively, and the correlation coefficient of validation (R _val) were 0.861 and 0.700, respectively. The results demonstrated that NIRS technique could be used as a rapid method for classification of geographical origin of Chinese rice wine, and AAS could be used as an alternative technique or to validate the discrimination results.     

Quantitative nmr imaging of kiwifruit (actinidia deliciosa) during growth and ripening

Quantitative ¹H magnetic resonance (MR) imaging was used to determine relaxation changes (T₁, T₂-CPMG) at regular intervals during growth and ripening of kiwifruit (Actinidia deliciosa var deliciosa). Temporal trends and differences between flesh, locule and core tissue were found for both relaxation parameters. However, no consistent associations were found between non-destructive measurements and those for individual free sugars, soluble solids content (SSC) and macronutrients and micronutrients determined on dissected companion samples. Increases of 200% in total free sugar concentration in flesh and 68% in SSC accompanied starch hydrolysis after harvest. Despite the magnitude of these changes, relaxation times remained unaltered. These observations were repeated in a second investigation using A arguta fruit and T₁, T₂, T₂-CPMG and self-diffusion image contrasts. Here, SSC increased 125% during a compressed 15-day ripening period, while MR parameters like self-diffusion declined only 7–14% from harvest values. T₂-CPMG relaxation was also investigated in aqueous solutions containing individual organic acids, sugars or pectate and juice from ripening fruit (4·7–15·5% SSC). Analysis of solutions and juices showed relaxation is indeed sensitive to increases in sugar composition but relatively insensitive to changes in organic acids and soluble pectin at concentrations normally found in fruit. Results imply that relaxation parameters determined from MR images may not be appreciably influenced by processes that cause solution composition to vary dramatically, even though these changes are reflected in the relaxation properties of the juice itself. Possible reasons for this are discussed with regard to the impact of cell structure and magnetic field strength on relaxation processes. © 1998 Society of Chemical Industry.     

Image Processing Applied to Classification of Avocado Variety Hass (Persea americana Mill.) During the Ripening Process

This work was undertaken to analyze the ripening process of avocados variety Hass (Persea americana Mill.) by image processing (IP) methodology. A set of avocados (10 samples) was used to follow the changes in image features during ripening by applying a computer vision system, extracting color and textural parameters. Other 16 avocados were used to evaluate the firmness and mass loss. Three maturity stages of avocados were established, and a classification was obtained by applying principal component analysis and k-nearest neighbor algorithm. During the ripening process (12 days), avocado firmness decreased from 75.43 to 2.63 N, while skin color values kept invariable during 6 days; after that, a decrement in the peel green color (a*) was observed (−9.68 to 2.32). Image features showed that during ripening the color parameters (L*, a*, and b*), entropy (4.29 to 4.00), angular second moment (0.287 to 0.360), and fractal dimension (2.58 to 2.44) had a similar path as compared to mass loss, a*, and firmness ripening parameters, respectively. Relationships between image features and ripening parameters were obtained. The parameter a* was the most useful digital feature to establish an acceptable percentage of avocado classification (>80%) in three different maturity stages found. Results obtained by means of IP could be useful to evaluate, at laboratory level, the ripening process of the avocados.     

Maturity determination of fresh dates by near infrared spectrometry

In Israel, fresh dates are normally harvested unripe and stored in a controlled environment until marketed. Proper ripening depends on maturity at harvest time. Sugar and water contents of the dates are considered important maturity attributes. Decision‐making on the harvesting schedule for each section in a plantation of fresh dates (variety Hayani) is one of the major problems for the growers. In order to estimate the optimum harvest time, conventional laboratory methods have been used to assess the maturity of samples of dates; methods which by nature are destructive, manual and time consuming. A semi‐automatic system for maturity determination of fresh dates has been developed, tested and operated. It combines a near infrared (NIR) spectrometer with a step‐wise cell conveyor, both of which are controlled by a PC. The NIR models were based on measuring the water and total soluble solids (TSS) contents. The calibration models and the prediction results had a standard error of prediction (SEP) of 1% for TSS and water contents. The correlation coefficient R between TSS and water contents as predicted by NIR models and as measured in routine laboratory destructive tests was 0.9. The system was capable of testing 100 dates in 3 min. © 1999 Society of Chemical Industry     

Identification of animal meat muscles by visible and near infrared reflectance spectroscopy

Visible (VIS) and near infrared reflectance spectroscopy (NIRS) was used to identify and authenticate different meat muscle species. Samples from beef (n: 100), lamb (n: 140), pork (n: 44) and chicken (n: 48) muscles were homogenised and scanned in the visible (VIS) and near infrared (NIR) region (400-2500 nm) in a monochromator instrument in reflectance. Both Principal Component Analysis (PCA) and dummy partial least-squares regression (PLS) models were developed to identify different meat species. The models correctly classified more than 80% of the meat sample muscles according with the muscle specie. The results showed the potential of VIS and NIR spectra as an objective and rapid method for authentication and identification of meat muscle species.     

Discoloration Kinetics of Clarified Apple Juice Treated with Lewatit® S 4528 Adsorbent Resin During Processing

The present work studies the adsorption of colored compounds in apple juice with a Lewatit® resin S 4528. The sorption equilibrium through the adsorption isotherms for 20, 35, and 50 °C was studied. The absorbance at 420 nm was used to measure the concentration of colored compounds, which permits correlating the residual concentration with the adsorbed concentration, proving that the data matched reasonably well according to the Langmuir and Freundlich models. Also, the efficiency of the adsorption process was studied for different resin/juice mass ratios at different temperatures, from which it was observed that there was an improvement in efficiency as the resin content increased, while the increase in temperature was not so important in the process. The adsorption kinetics at 35 °C for different resin/juice mass ratios was also studied. The kinetic model developed by Ibarz was used, concluding that the data matched this model reasonably well. The adsorption kinetic constant was always higher than the desorption kinetic constant, which indicates that the adsorption stage predominates the desorption stage. The adsorption kinetic constant shows a decreasing tendency with the raise in the resin/juice ratio, and the desorption kinetic constant shows an increasing tendency. The variation of the CIELab color parameters (L*, a*, and b*) with the adsorption time was studied, obtaining results that match the kinetic adsorption model proposed.     

On-line analysis of intact olive fruits by vis–NIR spectroscopy: Optimisation of the acquisition parameters

In the last years, the potential of NIRS for quantitative and qualitative analysis of olives fruits and oils has been investigated. However, limited work has been published about the on-line implementation of NIR spectroscopy in this sector. NIRS application at factory level (olive mills) is desirable. However, prior its implementation, many parameters related to the on-line spectrum acquisition, must be studied and optimised. In this paper, the influence of parameters such as focal distance and integration time has been studied. On-line spectral measurements were performed on intact olives in the spectral range of 380–1690 nm using a diode array spectrometer located on the top of a conveyor belt. The statistical criteria used to evaluate the spectral repeatability for each level of parameters considered were the standard deviation (SD) of the log (1/R) values and the root mean square statistics (RMS). Results demonstrated that for on-line control of olives in movement, spectra acquisition process was more affected by the focal distance chosen than by the integration time used. A focal distance of 13 mm and an integration time of 5 s have been defined as the optimal operational conditions.     

Estimation of physical and mechanical properties of agro-based particleboards by near infrared spectroscopy

Partial least square regression (PLS-R) calibrations based on near infrared (NIR) spectroscopic data were developed in order to predict mechanical and physical properties of agro-based particleboards. The panels were manufactured using Eucalyptus and Pinus wood particles and sugar cane bagasse. The following panel properties were evaluated according to standard methods: modulus of elasticity (MOE), modulus of rupture (MOR), internal bonding (IB) strength, water absorption (WA24H), and thickness swelling (TS24H) after 24 hours of immersion. NIR spectra information was measured on samples cut from each particleboard and correlated with their physical and mechanical properties by PLS-R to build predictive NIR models. The NIR models for IB, WA24H and TS24H presented satisfactory coefficient of determination (0.73; 0.72 and 0.75, respectively.) The key role of resins (adhesives), cellulose, and lignin for NIRS calibrations of mechanical and physical properties of the particleboards is shown. These models can be useful to quickly verify such properties in unknown agro-based particleboards.     

Delayed harvest and cold storage period influence ethylene production,fruit firmness and quality of ‘Cripps Pink’ apple

The effects of harvest date and cold storage period on ethylene production, fruit firmness and quality of ‘Cripps Pink’ apple were investigated. Fruit were harvested from Perth Hills and Donnybrook (Western Australia) at commercial maturity (CM), 2, 4 and 6 weeks after CM prior to 0, 45, 90 and 135 days cold storage in 2003 and 2004. Delayed harvest significantly increased ethylene production, CIE values a* and C* at both locations in 2 years. Delayed harvest and extended cold storage period increased the internal ethylene production and reduced fruit firmness, soluble solids concentration: titratable acidity (SSC:TA) ratio and reduced CIE values L*, b*, h° during both years and locations. Fruit harvested 2 weeks after CM can be cold‐stored for 90 days with acceptable fruit quality. If the fruit is intended to be sold fresh immediately in local markets, the harvest can be delayed up to 6 weeks after CM to harness substantially improved fruit colour with acceptable fruit quality.     

Quality Assessment of Intact Chicken Breast Fillets Using Factor Analysis with Vis/NIR Spectroscopy

Factor analysis (FA) method was tested to assess quality of chicken breast fillets with the visible/near-infrared (Vis/NIR) spectroscopy with wavelength range between 400 and 2500 nm. According to inherent correlation, three factors were extracted from the measured eight quality traits (L*, a*, b*, pH, moisture, drip loss, expressible fluid, and salt-induced water gain). The extracted “grade factor” (F ₁), “color factor” (F ₂), and “moisture factor” (F ₃) could respectively represent the characteristics and the variation tendency of the corresponding quality traits and were defined as three new quality assessment indexes. Furthermore, partial least squares regression (PLSR) models were established to quantitatively relate spectral information to eight individual quality traits and three factors. The results indicated that the models for predicting each factor performed better than those for individual quality traits. Key wavelengths of each quality trait were then selected, and the corresponding spectra were taken to build new PLSR prediction models. The selected key wavelengths showed obvious practical significance, and the new models had comparable predictive performance to those models developed based on the full spectra, among which the new models of F ₁ and F ₂ had acceptable and robust predictive abilities (R²p?=?0.73, RPD?=?1.91; R²p?=?0.74, RPD?=?1.97). Our results in the present study demonstrate the potential for FA and Vis/NIR spectroscopy as a useful method to assess the quality of chicken breast fillets.     

Assessing the Value of a Portable Near Infrared Spectroscopy Sensor for Predicting Pork Meat Quality Traits of “Asturcelta Autochthonous Swine Breed”

Sixty-one intact meat samples from Asturcelta autochthonous swine breed were scanned in the slaughterhouse in reflectance mode. A handheld microelectromechanical system digital transform (Phazir1624, Polychromix Inc.), with a window sampling area of 0.8?×?1 cm and wavelengths ranging from 1,600 to 2,400 nm, was used. With the spectra database recorded were developed different chemometrical models assaying first and second derivatives as math treatment and standard normal variate (SNV) and multiplicative scatter correction for minimizing scattering effect. The greatest predictive capacity was achieved after applying SNV and first derivative for moisture, intramuscular fat (IMF) content, and pH parameters and second derivative for CIE L*, a*, b* colorimetric values, and the Warner–Bratzler force (instrumental texture). The coefficients of determination for calibration ranged from 0.63 to 0.89. The ratio between the standard error of the laboratory and the standard error of calibration ranged from 0.8 to 2.5 for all parameters (1.7 on average) with the exception of b and pH with ratios of 3.5 and 4.1, respectively. The statistical values obtained for the models developed to estimate IMF, CIE L*, a*, b*, moisture, and pH, displayed acceptable predictive capacity. For instrumental texture, the model could be able to discriminate among tender, medium, and hard meat in carcasses for characterization slaughter purposes.     

Quantification of glucose,fructose and sucrose in bayberry juice by NIR and PLS

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.