大白菜花青素含量及色差指标相关性研究

为了探寻大白菜花青素含量快速测定的方法,本文利用pH差计法和色差仪分别测定了‘城阳青’(普通大白菜)、‘秋宝黄’(黄心白菜)和‘彩凤’3个不同叶色大白菜品种花青素含量以及色差指标,并对6个色泽参数与花青素含量进行了相关和回归分析。结果表明:6个色泽参数均能反映白菜叶片间叶色的细微变化,‘城阳青’和‘秋宝黄’不含花青素,紫色白菜‘彩凤’的花青素主要分布于由外向内的第1～4层叶片。色泽参数L,b,h和C分别与花青素含量呈极显著或显著负相关关系(相关系数分别为-0.85**,-0.58**,-0.49*,-0.58**)。以色泽参数值L、a、h与花青素含量建立了多元回归方程:y=90.24-1.07x1+5.65x2-142.71x3(x1为L值,x2为a值,x3为h值,y为花青素含量),该回归方程相关系数为0.9629。通过色差计依据建立的回归方程可快速测定紫色大白菜花青素的含量。     

Predicting the degree of phosphorus saturation using the ammonium acetate–EDTA soil test

As a result of the important role played by phosphorus (P) in surface water eutrophication, the susceptibility of soils to release P requires evaluation. The degree of phosphorus saturation, assessed by oxalate extraction (DPS_ox), has been used as an indicator. However, most laboratories do not include DPS_ox in routine soil tests because of cost and time. This study evaluates the suitability of the ammonium acetate extraction in the presence of EDTA (AAEDTA), the standard soil test P (STP) in Wallonia (Southern Belgium), to predict DPS_ox; we also compared it with the Mehlich 3 extraction. Ninety‐three topsoil samples were collected in agricultural soils throughout Wallonia. Good correlations were found between the AAEDTA and the Mehlich 3 methods for P, Fe and Al (r = 0.85, 0.77 and 0.86, respectively). An exponential relationship was found between P_AAEDTA and DPS_ox. Results of principal component analysis and regression demonstrated that STP can be used to predict DPS_ox (r = 0.93) after logarithmic transformation. Soil test Al was also a good indicator of the P sorption capacity (PSC_ox) of soils (r = 0.86). Including the clay fraction in regression equations only slightly improved the prediction of PSC_ox (r = 0.90), while other readily available data (such as pH or organic carbon) did not significantly improve either DPS_ox or PSC_ox predictions.     

Relationship between corn yield and chemical composition of the ear leaf measured with different regression models

Abstract

Corn yields and leaf samples were obtained from experimental plots receiving varying rates of N, P and K. Yields were regressed on leaf levels of N, P, K, Ca, Mg, B, Cu, Fe, Mn and Zn as independent variables. Various polynomial regressions were fitted to the yields and “goodness of fit”; of particular mathematical models was used as a basis for evaluating particular biological and statistical concepts.

It was found that no regression, where chemical elements were used as ratios, fit the observations as well as a quadratic polynomial or its square root transformation. This suggests that within the set of data used, emphasis on particular cation or anion ratios does not necessarily result in the “best”; explanation of variation in yield.

“Classical”; growth equations were fitted to corn yields, but were not as precise in predicting yields as the polynomials. A modified stagewise regression procedure was used for fitting one mathematical model, but results were less satisfactory than those obtained with usual least squares procedures.     

Influence of Soil Particle Size on the Measurement of Sodium by Near-Infrared Reflectance Spectroscopy

This study evaluates the effect of soil particle size (SPS) on the measurement of exchangeable sodium (Na) (EXC-Na) by near-infrared reflectance (NIR) spectroscopy. Three hundred thirty-two (n = 332) top soil samples (0–10 cm) were taken from different locations across Uruguay, analyzed by EXC-Na using emission spectrometry, and scanned in reflectance using a NIR spectrophotometer (1100–2500 nm). Partial least squares (PLS) and principal component regression (PCR) models between reference chemical data and NIR data were developed using cross validation (leaving one out). The coefficient of determination in calibration (R²) and the root mean square of the standard error of cross validation (RMSECV) for EXC-Na concentration were 0.44 (RMSECV: 0.12 mg kg^–1) for soil with small particle size (SPS-0.053) and 0.77 (RMSECV: 0.09 mg kg^–1) for soils with particle sizes greater than 0.212 mm (SPS-0.212), using the NIR region after second derivative as mathematical transformation. The R² and RMSECV for EXC-Na concentration using PCR were 0.54 (RMSECV: 0.07 mg kg^–1) and 0.80 (RMSECV: 0.03 mg kg^–1) for SPS-0.053 and SPS-0.212 samples, respectively.     

Application of Slicing in Component-based System Regression Testing

In component-based system regression testing, the dependence model of component-based system should be built in order to confirm the part which will be affected by modify. Since high reusability and high complexity, the existing dependence models may not be applicable to component-based systems, a hierarchical dependence model is proposed to describe component-based. Through the forward slicing of modified points in the model, the modified and affected parts can be gotten, then traverse these parts and get affected testing path, thereby regression testing examples can be chosen effectively, the efficiency of regression testing can be improred.     

Regression Applied in Continuous Mathematical Forecast

Data Mining can distill the connotative, unknown and potential value information or pattern from many data. It is a problem that must be settled during the developing of Decision Support System how to discover knowledge from Data Warehouse. In order to realize the continuous mathematical forecast that will be used in the Marketing Decision Support System for Industrial Enterprise, the authors use the method of regression to discuss how to design the algorithm for Data Mining, how to design the model for Data Mining, and so on. When the algorithm applied to the sales forecast, the result processing to simulation data indicates it can realize the expected effect.     

THE DEVELOPMENT OF COMPUTER AIDED NORM OF WORKING HOUR PLANNING SYSTEM

Based on Group Technology, part families of the norm of working hour are formed according to the similarity among components. With the progressive regerssion, the models of the norm of working hour are built for every part family. A computer aided norm model building program and a computer aided norm of working hour planning system are developed. The system is successfully integrated with CAD/CAPP system. Some examples of the model building and calculation results are illustrated as well.     

Transmission Congestion Management Based on Power Influence Coefficient

Basing eliminating on the idea that the generator who has the most influence on the power flow of line is mostly in favor of transmission congestion, the model of congestion management with the object of minimizing adjustments of bufions varied with generation outputs is proposed. It can eliminate the congestion effectively by judging the generators who should be adjusted and the amounts of adjustment. The test on IEEE-RTS24 buses system and other practical systems show that the proposed method is effective.