Application Fourier transform near infrared spectrometer in rapid estimation of soluble solids content of intact citrus fruits

Nondestructive method of measuring soluble solids content (SSC) of citrus fruits was developed using Fourier transform near infrared reflectance (FT-NIR) measurements collected through optics fiber. The models describing the relationship between SSC and the NIR spectra of citrus fruits were developed and evaluated. Different spectra correction algorithms (standard normal variate (SNV), multiplicative signal correction (MSC)) were used in this study. The relationship between laboratory SSC and FT-NIR spectra of citrus fruits was analyzed via principle component regression (PCR) and partial least squares (PLS) re- gression method. Models based on the different spectral ranges were compared in this research. The first derivative and second derivative were applied to all spectra to reduce the effects of sample size, light scattering, instrument noise, etc. Different baseline correction methods were applied to improve the spectral data quality. Among them the second derivative method after baseline correction produced best noise removing capability and yielded optimal calibration models. A total of 170 NIR spectra were acquired; 135 NIR spectra were used to develop the calibration model; the remaining spectra were used to validate the model. The developed PLS model describing the relationship between SSC and NIR reflectance spectra could predict SSC of 35 samples with correlation coefficient of 0.995 and RMSEP of 0.79 °Brix.

Measurement of soluble solids content in watermelon by Vis/NIR diffuse transmittance technique

Watermelon is a popular fruit in the world with soluble solids content （SSC） being one of the major characteristics used for assessing its quality. This study was aimed at obtaining a method for nondestructive SSC detection of watermelons by means of visible/near infrared （Vis/NIR） diffuse transmittance technique. Vis/NIR transmittance spectra of intact watermelons were acquired using a low-cost commercially available spectrometer operating over the range 350-1000 nm. Spectra data were analyzed by two multivariate calibration techniques： partial least squares （PLS） and principal component regression （PCR） methods. Two experiments were designed for two varieties of watermelons [Qilin （QL）, Zaochunhongyu （ZC）], which have different skin thickness range and shape dimensions. The influences of different data preprocessing and spectra treatments were also investigated. Performance of different models was assessed in terms of root mean square errors of calibration （RMSEC）, root mean square errors of prediction （RMSEP） and correlation coefficient （r） between the predicted and measured parameter values. Results showed that spectra data preprocessing influenced the performance of the calibration models. The first derivative spectra showed the best results with high correlation coefficient of determination [r=0.918 （QL）; r=0.954 （ZC）], low RMSEP [0.65 °Brix （QL）; 0.58 °Brix （ZC）], low RMSEC [0.48 °Brix （QL）; 0.34°Brix （ZC）] and small difference between the＇RMSEP and the RMSEC by PLS method. The nondestructive Vis/NIR measurements provided good estimates of SSC index of watermelon, and the predicted values were highly correlated with destructively measured values for SSC. The models based on smoothing spectra （Savitzky-Golay filter smoothing method） did not enhance the performance of calibration models obviously. The results indicated the feasibility of Vis/NIR diffuse transmittance spectral analysis for predicting watermelon SSC in a nondestructive way.

Online quantitative analysis of soluble solids content in navel oranges using visible-nearinfrared spectroscopy and variable selection methods

Variable selection is applied widely for visible-near infrared(Vis-NIR)spectroscopy analysis of internal quality in fruits.Different spectral variable selection methods were compared for online quantitative analysis of soluble solids content(SSC)in navel oranges.Moving window partial least squares(MW-PLS),Monte Carlo uninformative variables elimination(MC-UVE)and wavelet transform(WT)combined with the MC-UVE method were used to select the spectral variables and develop the calibration models of online analysis of SSC in navel oranges.The performances of these methods were compared for modeling the Vis NIR data sets of navel orange samples.Results show that the WT-MC-UVE methods gave better calibration models with the higher correlation cofficient(r)of 0.89 and lower root mean square error of prediction(RMSEP)of 0.54 at 5 fruits per second.It concluded that Vis NIR spectroscopy coupled with WT-MC-UVE may be a fast and efective tool for online quantitative analysis of SSC in navel oranges.

Achieving robustness to temperature change of a NIR model for apple soluble solids content

The temperature difference of fruit itself will affect its near infrared spectrum and the accuracy of its soluble solids content(SSC)prediction model.To eliminate the influence of apple temperature difference on the SSC model,a diffuse transmission dynamic online detection device was used to collect the spectral data of apples at different temperatures,and four methods were used to establish partial least squares correction models:global correction,orthogonal signal processing,generalized least squares weighting and external parameter orthogonal(EPO).The results show that the temperature has a strong influence on the diffuse transmission spectrum of apples.The 20ºC model can get a satisfactory prediction result when the temperature is constant,and there will be great errors when detecting samples at other temperatures.The effect of temperature must be corrected to establish a more general model.These methods all improve the accuracy of the model,with the EPO method giving the best results;the prediction set correlation coefficient is 0.947,the root mean square error of prediction is 0.489%,and the prediction bias is 0.009%.The research results are of great significance to the practical application of SSC prediction of fruits in sorting workshops or orchards.

Neural network and principal component regression in non-destructive soluble solids content assessment:a comparison

Visible and near infrared spectroscopy is a non-destructive,green,and rapid technology that can be utilized to estimate the components of interest without conditioning it,as compared with classical analytical methods.The objective of this paper is to compare the performance of artificial neural network(ANN)(a nonlinear model)and principal component regression(PCR)(a linear model)based on visible and shortwave near infrared(VIS-SWNIR)(400-1000 nm)spectra in the non-destructive soluble solids content measurement of an apple.First,we used multiplicative scattering correction to pre-process the spectral data.Second,PCR was applied to estimate the optimal number of input variables.Third,the input variables with an optimal amount were used as the inputs of both multiple linear regression and ANN models.The initial weights and the number of hidden neurons were adjusted to optimize the performance of ANN.Findings suggest that the predictive performance of ANN with two hidden neurons outperforms that of PCR.

Nondestructive determining the soluble solids content of citrus using near infrared transmittance technology combined with the variable selection algorithm

Nondestructive determination the internal quality of thick-skin fruits has always been a challenge.In order to investigate the prediction ability of full transmittance mode on the soluble solid content(SSC)in thick-skin fruits,the full transmittance spectra of citrus were collected using a visible/near infrared(Vis/NIR)portable spectrograph(550–1100 nm).Three obvious absorption peakswere found at 710,810 and 915 nmin the original spectra curve.Four spectral preprocessing methods including Smoothing,multiplicative scatter correction(MSC),standard normal variate(SNV)and first derivativewere employed to improve the quality of the original spectra.Subsequently,the effective wavelengths of SSC were selected from the original and pretreated spectra with the algorithms of successive projections algorithm(SPA),competitive adaptive reweighted sampling(CARS)and genetic algorithm(GA).Finally,the prediction models of SSC were established based on the full wavelengths and effectivewavelengths.Results showed that SPA performed the best performance on eliminating the useless information variable and optimizing the number of effective variables.The optimal predictionmodel was established based on 10 characteristic variables selected from the spectra pretreated by SNV with the algorithmof SPA,with the correlation coefficient,root mean square error,and residual predictive deviation for prediction set being 0.9165,0.5684°Brix and 2.5120,respectively.Overall,the full transmittance mode was feasible to predict the internal quality of thick-skin fruits,like citrus.Additionally,the combination of spectral preprocessing with a variable selection algorithmwas effective for developing the reliable predictionmodel.The conclusions of this study also provide an alternative method for fast and real-time detection of the internal quality of thick-skin fruits using Vis/NIR spectroscopy.

Nondestructive determination of soluble solids and firmness in mix-cultivar melon using near-infrared CCD spectroscopy

Nondestructive evaluation of melon quality is in great need of comprehensive study.Soluble solids content(SSC)and firmness are the two indicators of melon internal quality that mostly a®ect consumer acceptance.To provide guidance for fruit classification,internal quality standards was preliminarily established through sensory test,as:Melon with SSC over 12
Brix,firmness 4–5.5 kgf·cm^(-2)2 were considered as satisfactory class sample;and SSC over 10
Brix,¯rmness 3.5–6.5 kgf·cm^(-2) as average class sample.The near infrared(NIR)nondestructive detection program was set as spectra collected from the stylar-end,Brix expressed by the average SSC of inner and outer mesocarp,each cultivar of melon was detected with its own optimum integration time,and the second derivative algorithm was used to equalize them.Using wavelength selected by genetic algorithms(GA),a robust SSC model of mix-cultivar melon was established,the root mean standard error of cross-validation(RMSECV)was 0.99 and the ratio performance deviation(RPD)nearly reached 3.0,which almost could meet the accuracy requirement of 1.5
Brix.Firmness model of mix-cultivar melon was acceptable but inferior.

Determination of soluble solid content and acidity of loquats based on FT-NIR spectroscopy

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 loquats 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 rim）, 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.

Review on Effects of Nitrogen on the Internal Quality of Peach Fruit

On the basis of referring plenty of literatures, we summarized the research advance in effects of nitrogen on the internal quality of peach fruit. Most studies have shown that proper nitrogen application can improve internal quality of fruit, and excessive nitrogen application can reduce soluble solid and sugar contents of fruit, increase organic acid content, reduce fruit aroma, increase protein and amino acid contents, and increase or reduce vitamin C content. Relevant issues were discussed.

Review on Effects of Sunlight on the Internal Quality of Peach Fruit

On the basis of referring plenty of literatures, we summed up the research advance in effects of sun light on the internal quality of peach fruit. This paper discussed the effect of light on the internal quality of peach fruit under the conditions of open cultivation, protected cultivation, bagging and surface covering with reflective film, the mechanism of occurrence and the technical measures to improve the utilization rate of light and light energy, and prospected the future research work.

Impact of greenhouse whitefly management on strawberry fruit quality

The greenhouse whitefly, Trialeurodes vaporariorum （Westwood）, is an important pest of strawberries in California, USA. The adults and nymphs feed on phloem sap of leaves to remove the photo-assimilates. The objective of this study is to test the impact of whitefly management with insecticides on strawberry fruit quality. Applications of imidacloprid, thiamethoxam, buprofezin and pyriproxyfen decreased the mean adult whitefly numbers by 2.80-, 2.17-, 1.69- and 1.39-fold, respectively, compared to the untreated control, Similarly, the mean numbers of first and second instar whiteflies were reduced 4.36-, 2.20-, 1.90- and 2.02-fold, respectively, while the mean numbers of third and fourth instars were reduced 5.48-, 2.28-, 2.71- and 1.43-fold, respectively, in plants treated with imidacloprid, thiamethoxam, buprofezin and pyriproxyfen. The mean soluble solids content in imidacloprid, thiamethoxam, buprofezin and pyriproxyfen treatments was 1.04-, 1.06-, 1.03- and 1.04-fold greater, respectively, than that in the control. The whitefly reduction enhanced the mean fruit titratable acidity by 4%-6%. Mean glucose levels in imidacloprid and thiamethoxam treatments were significantly higher than in other treatments. However, the whitefly management did not affect the mean fructose levels, lmidacloprid, thiamethoxam and pyriproxyfen treatments boosted the ascorbic acid levels by up to 4%. The impact of whitefly management on strawberry fruit nutrition and antioxidant capacity is discussed.

Effects of regulated deficit irrigation on soil salinity,physiological processes and fruit quality of gray jujube under desert conditions

Regulated deficit irrigation(RDI)was applied to gray jujube trees in an oasis region,to determine the effects of this irrigation system on soil salinity,gray jujube physiological processes,fruit yield,and fruit quality.Treatments consisted of severe,moderate and low deficit irrigation(irrigated with 85%,70%and 55%of CK,respectively)at the flowering stage to fruit set stage.During the other growth stages,all treatments were irrigated with 80%of pan evaporation,which was the same as that in control.The results indicated that soil salinity was enhanced during the periods of water stress,but the high value of soil salinity declined by 3.48%-37.27%,at each depth,after irrigation was resumed.RDI caused a decline in the photosynthetic rate,transpiration rate,and stomatal conductance,but enhanced the water use efficiency of the leaves.However,the leaf photosynthetic rate was effectively enhanced after the recovery of irrigation,especially in the moderate deficit irrigation treatment,which exceeded the control.This led to an improved fruit yield,which was 9.57%higher than that of the control.The deficit treatments caused a significant increase in the soluble solid content,soluble sugar content,single fruit weight and sugar/acid ratio.Enhanced vitamin C content,resulting from deficit treatments,has also been observed in the gray jujube.Therefore,this research shows that RDI provides some benefits in the production of gray jujube trees in desert conditions.