Ying Yibin

Measurement of sugar content in Fuji apples by FT-NIR spectroscopy

To evaluate the potential of FT-NIR spectroscopy and the influence of the distance between the light source/detection probe and the fruit for measuring the sugar content (SC) of Fuji apples, diffuse reflectance spectra were measured in the spectral range from 12500 to 4000 cm−1 at 0 mm, 2 mm, 4 mm and 6 mm distances. Four calibration models at four distances were established between diffused reflectance spectra and sugar content by partial least squares (PLS) analysis. The correlation coefficients (R) of calibrations ranged from 0.982 to 0.997 with SEC values from 0.138 to 0.453 and the SECV values from 0.74 to 1.58. The best model of original spectra at 0 mm distance yielded high correlation determination of 0.918, a SEC of 0.092, and a SEP of 0.773. The results showed that different light/detection probe-fruit distances influence the apple reflective spectra and SC predictions.

Machine vision inspection of rice seed based on Hough transform

A machine vision system was developed to inspect the quality of rice seeds. Five varieties ofJinyou402,Shanyou10,Zhongyou207,Jiayou and IIyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on Hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.

Non-destructive measurement of pear internal quality indices by visible and near-infrared spectrometric techniques

Abstract The feasibility of non‐destructive measurement of internal quality indices of intact pear fruit using visible and near‐infrared (Vis/NIR) spectrometric techniques was studied. In the wavelength region from 350 to 1800 nm, calibration models relating Vis/NIR spectra to soluble solids content (SSC) and firmness were developed based on multilinear regression (MLR), principal component regression (PCR) and partial least squares regression (PLSR) with respect to the logarithms of the reflectance reciprocal log (1/R), its first derivative D1 log (1/R) and its second derivative D2 log (1/R). The best combination, based on the reliable and robust models obtained, was the PLS models with respect to log (1/R) at an equatorial position of the fruit. Prediction with the PLS model with respect to log (1/R) resulted in correlation coefficients (rp ) of 0.9121 and 0.8541, and root mean standard error of prediction (RMSEP) of 0.6619 and 1.2324 for SSC and firmness, respectively. The experimental results indicate that the Vis/NIR spectrometric technique could provide an accurate, reliable and non‐destructive method for assessing internal quality indices of pear fruit, especially for SSC.

Determining heating pipe temperature in greenhouse using proportional integral plus feedforward control and radial basic function neural-networks *

Proportional integral plus feedforward (PI+FF) control was proposed for identifying the pipe temperature in hot water heating greenhouse. To get satisfying control result, ten coefficients must be adjusted properly. The data for training and testing the radial basic function (RBF) neural-networks model of greenhouse were collected in a 1028 m2 multi-span glasshouse. Based on this model, a method of coefficients adjustment is described in this article.

Correlation analysis-based image segmentation approach for automatic agriculture vehicle

It is important to segment image correctly to extract guidance information for automatic agriculture vehicle. If we can make the computer know where the crops are, we can extract the guidance line easily. Images were divided into some rectangle small windows, then a pair of 1-D arrays was constructed in each small windows. The correlation coefficients of every small window constructed the features to segment images. The results showed that correlation analysis is a potential approach for processing complex farmland for guidance system, and more correlation analysis methods must be researched.

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 by Fourier transform near infrared (FT-NIR) reflectance and fiber optics. Also, the models describing the relationship between SSC and the NIR spectra of the fruit were developed and evaluated. To develop the models several different NIR reflectance spectra were acquired for each fruit from a commercial supermarket. Different spectra correction algorithms (standard normal variate (SNV), multiplicative signal correction (MSC)) were used in this work. The relationship between laboratory SSC and FT-NIR spectra of citrus fruits were analyzed via principle component regression (PCR) and partial least squares (PLS) regression method using TQ 6.2.1 quantitative software (Thermo Nicolet Co., USA). Models based on the different spectral ranges were compared in this research. The first derivative and second derivative were applied to all measured spectra to reduce the effects of sample size, light scattering, noise of instrument, 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 to obtain optimal calibration models. Total 170 NIR spectra were acquired from 85 citrus fruits and 135 NIR spectra were used to develop the calibration model, the rest spectra were used to validate the model. Developed PLS model, which describes the relationship between SSC and NIR reflectance spectra, could predict SSC of 35 samples with correlation coefficient of 0.872 and SEP of 0.45 oBrix.

DETERMINATION OF RESIDENCE TIME OF GRAINS IN DRUM DRYER

Abstract On the basis of the theoretical analysts of the forces applied to grains and moving locus of grains in rotary drum dryer, residence time and contact heating time of grains in the dryer were calculated. The values of calculation conformed to the measured values. These results supplied reliable foundation in theory and practice for further studying and improving the dryer. They also provided designers with references to construct similar type of dryers.