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1.
INTRODUCTION Determination of fruit and vegetable quality is very important for both producers and processors. Watermelon as a delicious fruit has been widely ac-cepted in the world and its internal quality is impor-tant for consumers and merchants. The current fa-vorite way for checking a watermelon is to sense sound or vibration by slapping or rapping it. It is time consuming, tedious, and subject to error. Several studies on assessing the quality of watermelon based on its acoustic o…  相似文献   

2.
The near infrared (NIR) spectroscopy technique has been applied in many fields because of its advantages of simple preparation,fast response,and non-destructiveness.We investigated the potential of NIR spectroscopy in diffuse reflectance mode for determining the soluble solid content (SSC) and acidity (pH) of intact loquats.Two cultivars of loquats (Dahongpao and Jiajiaozhong) harvested from two orchards (Tangxi and Chun'an,Zhejiang,China) were used for the measurement of NIR spectra between 800 and 2500 nm.A total of 400 loquats (100 samples of each cultivar from each orchard) were used in this study.Relationships between NIR spectra and SSC and acidity of ioquats were evaluated using partial least square (PLS) method.Spectra preprocessing options included the first and second derivatives,multiple scatter correction (MSC),and the standard normal variate (SNV).Three separate spectral windows identified as full NIR (800-2500 nm),short NIR (800～1100 nm),and long NIR (1100～2500 nm) were studied in factorial combination with the preprocessing options.The models gave relatively good predictions of the SSC of loquats,with root mean square error of prediction (RMSEP) values of 1.21,1.00,0.965,and 1.16 °Brix for Tangxi-Dahongpao,Tangxi-Jiajiaozhong,Chun'an-Dahongpao,and Chun'an-Jiajiaozhong,respectively.The acidity prediction was not satisfactory,with the RMSEP of 0.382,0.194,0.388,and 0.361 for the above four loquats,respectively.The results indicate that NIR diffuse reflectance spectroscopy can be used to predict the SSC and acidity of loquat fruit.  相似文献   

3.
The use of visible-near infrared (NIR) spectroscopy was explored as a tool to discriminate two new tomato plant varieties in China (Zheza205 and Zheza207).In this study,82 top-canopy leaves of Zheza205 and 86 top-canopy leaves of Zheza207 were measured in visible-NIR reflectance mode.Discriminant models were developed using principal component analysis (PCA),discriminant analysis (DA),and discriminant partial least squares (DPLS) regression methods.After outliers detection,the samples were randomly split into two sets,one used as a calibration set (n=82) and the remaining samples as a validation set (n=82).When predicting the variety of the samples in validation set,the classification correctness of the DPLS model after optimizing spectral pretreatment was up to 93%.The DPLS model with raw spectra after multiplicative scatter correction and Savitzky-Golay filter smoothing pretreatments had the best satisfactory calibration and prediction abilities (correlation coefficient of calibration (Rc)=0.920,root mean square errors of calibration=0.196,and root mean square errors of prediction=0.216).The results show that visible-NIR spectroscopy might be a suitable alternative tool to discriminate tomato plant varieties on-site.  相似文献   

4.
Near infrared reflectance （N1R） spectroscopy is as a rapid, convenient and simple nondestructive technique useful for quantifying several soil properties. This method was used to estimate nitrogen （N） and organic matter （OM） content in a soil of Zhejiang Province, Hangzhou County. A total of 125 soil samples were taken from the field. Ninety-five samples spectra were used during the calibration and cross validation stage. Thirty samples spectra were used to predict N and OM concentration. NIR spectra of these samples were correlated using partial least square regression. The regression coefficients between measured and predicted values of N and OM was 0.92 and 0.93, and SEP （standard error of prediction） were 3.28 and 0.06, respectively, which showed that NIR method had potential to accurately predict these constituents in this soil. The results showed that NIR spectroscopy could be a good tool for precision farming application.  相似文献   

5.
To compare mid-infrared(MIR)and near-infrared(NIR)spectroscopies for the determination of the fat and protein contents in milk,the same sample sets with varying concentrations of fat and protein were measured in the MIR range of 3 200-700 cm-1 and NIR range of 9 000-4 000 cm-1.The spectral features in the two regions were analyzed.The MIR spectra of milk were characteristic due to the MIR inherent molecular specificity,whereas the NIR spectra were relatively characterless due to the NIR low selectivity.Partial least squares(PLS)regression models for fat and protein were developed by using both MIR and NIR spectra.MIR data with no pretreatment gave better results than NIR data.The square correlation coefficient(R2)and the root mean square error of prediction(RMSEP)were 0.98 and 0.10 g/dL for fat and 0.97 and 0.11 g/dL for protein.With NIR techniques,satisfactory results were not obtained with raw data.However,NIR data after pretreatment gave similarly good results to the ones using MIR method.This paper indicates that either of the MIR and NIR spectral methods is reliable for the determination of the fat and protein contents.  相似文献   

6.
INTRODUCTION Consumers’ acceptance of fresh or processedapples is the ultimate goal of apple breeders, foodscientists and supermarket managers. Internal qualityassessment has focused on two major objectives:removal of fruit with internal defects and taste selec-tion. Three major parameters including sugar content,acidity and firmness have to be taken into account todetermine the internal quality and the taste of an apple.Near infrared spectroscopy has been used to measureseveral properti…  相似文献   

7.
To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (r^2) of 0.759,low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way.  相似文献   

8.
INTRODUCTION Soluble solids content (SSC) is a major charac- teristic used for assessing citrus fruit quality. Near-infrared spectroscopy (NIRS) has been used as a rapid and nondestructive technique for determining the soluble solids content of fruit. Kawano et al.(1992) measured sugar content of peaches in the wavelength region of 680~1235 nm. Their experiments indicated good correlation between the NIR spectra and the sugar content (r=0.97, SEP=0.05 °Brix). Slaughter (1995) devel…  相似文献   

9.
This study investigated the performance of fit indexes in selecting a covariance structure for longitudinal data. Data were simulated to follow a compound symmetry, first-order autoregressive, first-order moving average, or random-coefficients covariance structure. We examined the ability of the likelihood ratio test (LRT), root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker–Lewis Index (TLI) to reject misspecified models with varying degrees of misspecification. With a sample size of 20, RMSEA, CFI, and TLI are high in both Type I and Type II error rates, whereas LRT has a high Type II error rate. With a sample size of 100, these indexes generally have satisfactory performance, but CFI and TLI are affected by a confounding effect of their baseline model. Akaike's Information Criterion (AIC) and Bayesian Information Criterion (BIC) have high success rates in identifying the true model when sample size is 100. A comparison with the mixed model approach indicates that separately modeling the means and covariance structures in structural equation modeling dramatically improves the success rate of AIC and BIC.  相似文献   

10.
In this paper, a flexible high-precision calibration method suitable for industrial field was proposed. The complexity of the coordinate transformation was simplified by choosing the camera coordinate system as the unified reference coordinate system. A flexible planar calibration pattern was introduced to the calibration process, which can be arbitrarily placed and from which the known feature points can be extracted to construct other unknown feature points. With the known intrinsic parameters, the laser projector plane equation was fitted by the multi-noncollinear points, which were acquired through the principle of triangulation and the projective invariance of cross ratio. With this method, the strict alignment and multiple times of coordinate transformation can be avoided. Experimental results showed that the arithmetic mean of the root mean square （RMS） error of distance was 0.000 7 mm.  相似文献   

11.
How should researchers choose between competing scales in predicting a criterion variable? This article proposes the use of nonnested tests for the 2SLS estimator of latent variable models to discriminate between scales. The finite sample performance of these tests is compared to structural equation modeling information-based criteria such as root mean squared error of approximation (RMSEA) and Akaike's Information Criterion (AIC). The Cox and encompassing tests and augmented versions of these tests are compared to the inconsistent ordinary least squares (OLS) J test. An augmented version of the encompassing test performs best for sample sizes of 100 or more and can be recommended for use on scales with high reliability (0.9) and sample sizes of 200 or more, under varying regressor and error distributions. The OLS J test performs best for small samples of N = 50 and can be recommended for use in small samples when scales have high reliability (0.9). Relative to the nonnested tests, the information-based criteria perform poorly.  相似文献   

12.
The impact force response of a peach impacting on a metal flat-surface was considered as nondestructive determination of firmness. The objectives were to analyze the effect of firmness, drop height, fruit mass, and impact orientation on the impact force parameters, and to establish a relationship between the impact force parameter and firmness. The effect of fruit firmness, drop height and fruit mass on the impact force parameters (coefficient of restitution, percentage of energy absorbed, and coefficient of force-time) was evaluated. The study found that the coefficient of restitution, percentage of energy absorbed, and force-time impact coefficient were significantly affected by fruit ripeness, but not affected by drop height, impact position (fruit cheek), and mass. The percentage of absorbed energy increased with ripeness, while the force-time impact coefficient and coefficient of restitution decreased with ripeness. Relationships were obtained between the three impact characteristic parameters (force-time impact coefficient, coefficient of restitution, and percentage of energy absorbed) and peach firmness using a polynomial model (R~2=0.932), S model (R~2=0.910), and exponential model (R~2=0.941), respectively.  相似文献   

13.
This article considers the implications for other noncentrality parameter-based statistics from Steiger's (1998) multiple sample adjustment to the root mean square error of approximation (RMSEA) measure. When a structural equation model is fitted simultaneously in more than 1 sample, it is shown that the calculation of the noncentrality parameter used in tests of approximate fit and in point and interval estimators of other noncentral fit statistics (except the expected cross-validation index) also requires a likeminded adjustment. Furthermore, it is shown that an adjustment is needed in multiple sample models for correctly calculating MacCallum, Browne, and Sugawara's (1996) approach to power analysis. The accuracy of these proposals is investigated and demonstrated in a small Monte Carlo study in which particular attention is paid to using appropriately constructed covariance matrices that give specified nonzero population discrepancy values under maximum likelihood estimation.  相似文献   

14.
Model fit indices are being increasingly recommended and used to select the number of factors in an exploratory factor analysis. Growing evidence suggests that the recommended cutoff values for common model fit indices are not appropriate for use in an exploratory factor analysis context. A particularly prominent problem in scale evaluation is the ubiquity of correlated residuals and imperfect model specification. Our research focuses on a scale evaluation context and the performance of four standard model fit indices: root mean square error of approximate (RMSEA), standardized root mean square residual (SRMR), comparative fit index (CFI), and Tucker–Lewis index (TLI), and two equivalence test-based model fit indices: RMSEAt and CFIt. We use Monte Carlo simulation to generate and analyze data based on a substantive example using the positive and negative affective schedule (N = 1,000). We systematically vary the number and magnitude of correlated residuals as well as nonspecific misspecification, to evaluate the impact on model fit indices in fitting a two-factor exploratory factor analysis. Our results show that all fit indices, except SRMR, are overly sensitive to correlated residuals and nonspecific error, resulting in solutions that are overfactored. SRMR performed well, consistently selecting the correct number of factors; however, previous research suggests it does not perform well with categorical data. In general, we do not recommend using model fit indices to select number of factors in a scale evaluation framework.  相似文献   

15.
The graded response model can be used to describe test-taking behavior when item responses are classified into ordered categories. In this study, parameter recovery in the graded response model was investigated using the MULTILOG computer program under default conditions. Based on items having five response categories, 36 simulated data sets were generated that varied on true θ distribution, true item discrimination distribution, and calibration sample size. The findings suggest, first, the correlations between the true and estimated parameters were consistently greater than 0.85 with sample sizes of at least 500. Second, the root mean square error differences between true and estimated parameters were comparable with results from binary data parameter recovery studies. Of special note was the finding that the calibration sample size had little influence on the recovery of the true ability parameter but did influence item-parameter recovery. Therefore, it appeared that item-parameter estimation error, due to small calibration samples, did not result in poor person-parameter estimation. It was concluded that at least 500 examinees are needed to achieve an adequate calibration under the graded model.  相似文献   

16.
校正变换矩阵法用于多组分染色剂的同时测定研究   总被引：1，自引：1，他引：0  
将校正变换矩阵法(CTM)与可见分光光度法相结合,对藏红、荧光桃红、曙红三种染色剂进行不经分离同时测定.使用交叉验证法选择主因子数建立了校正模型,预测结果令人满意.在相同条件下,将校正变换矩阵法与偏最小二乘(PLS)回归的结果进行了比较,结果表明两种方法的预测准确性没有显著性差异.  相似文献   

17.
目的:采用偏最小二乘法结合近红外漫反射光谱,建立阿昔洛韦片的快速无损含量测定模型.方法:以阿昔洛韦片为分析对象,用光纤探头测定近红外漫反射光谱.对光谱进行不同预处理方法建模并进行比较,多元校正模型为偏最小二乘法.结果:在11995.5～4246.7cm-1波长范围内采用一阶导数结合矢量归一化对光谱进行预处理,结果最优.定量模型的浓度范围为27%～53%.预示集平均回收率为98.69%,RSD为4.60%,RMSEP为0.0526.结论:近红外漫反射光谱法快速,简便,无损,能够用于阿昔洛韦片含量测定.  相似文献   

18.
To further develop the methods to remotely sense the biochemical content of plant canopies,we report the results of an experiment to estimate the concentrations of three biochemical variables of corn,i.e.,nitrogen (N),crude fat (EE) and crude fiber (CF) concentrations,by spectral reflectance and the first derivative reflectance at fresh leaf scale.The correlations between spectral reflectance and the first derivative transformation and three biochemical variables were analyzed,and a set of estimation models were established using curve-fitting analyses.Coefficient of determination (R2),root mean square error (RAISE) and relative error of prediction (PEP) of estimation models were calculated for the model quality evaluations,and the possible opti-mum estimation models of three biochemical variables were proposed,with R2 being 0.891,0.698 and 0.480 for the estimation models of N,EE and CF concentrations,respectively.The results also indicate that using the first derivative reflectance was better than using raw spectral reflectance for all three biochemical variables estimation,and that the first derivative reflectances at 759 nm,1954 nm and 2370 nm were most suitable to develop the estimation models of N,EE and CF concentrations,respectively.In addition,the high correlation coefficients of the theoretical and the measured biochemical parameters were obtained,especially for nitrogen (r=0.948).  相似文献   

19.
Bootstrapping approximate fit indexes in structural equation modeling (SEM) is of great importance because most fit indexes do not have tractable analytic distributions. Model-based bootstrap, which has been proposed to obtain the distribution of the model chi-square statistic under the null hypothesis (Bollen & Stine, 1992), is not theoretically appropriate for obtaining confidence intervals (CIs) for fit indexes because it assumes the null is exactly true. On the other hand, naive bootstrap is not expected to work well for those fit indexes that are based on the chi-square statistic, such as the root mean square error of approximation (RMSEA) and the comparative fit index (CFI), because sample noncentrality is a biased estimate of the population noncentrality. In this article we argue that a recently proposed bootstrap approach due to Yuan, Hayashi, and Yanagihara (YHY; 2007) is ideal for bootstrapping fit indexes that are based on the chi-square. This method transforms the data so that the “parent” population has the population noncentrality parameter equal to the estimated noncentrality in the original sample. We conducted a simulation study to evaluate the performance of the YHY bootstrap and the naive bootstrap for 4 indexes: RMSEA, CFI, goodness-of-fit index (GFI), and standardized root mean square residual (SRMR). We found that for RMSEA and CFI, the CIs under the YHY bootstrap had relatively good coverage rates for all conditions, whereas the CIs under the naive bootstrap had very low coverage rates when the fitted model had large degrees of freedom. However, for GFI and SRMR, the CIs under both bootstrap methods had poor coverage rates in most conditions.  相似文献   

20.
INTRODUCTION Researchers continue to develop non-destructive methods to evaluate the effect of their impact on ag-ricultural products using high-tech methods. Non-destructive techniques sensing has been applied for obtaining fruit and vegetable quality index. Non-destructive method for measuring firmness us-ing sonic or vibration characteristics applied in pre-vious investigations was recently reviewed by Arm-strong (1989) and Liljedahl and Abbott (1994). The sonic vibration technique u…  相似文献   

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