Studies On The Model And The Regional Distributing And Variating Evaluation System Of The Integrated Fiber Quality

Based on previous research achievements on cotton fiber quality in China and abroad, the test experimental results form different qualities of spinning yarn, regional cotton trials in Yangtze River valley during 2001～2002, the plantting experiments with different sowing periods in different locations during 1994～1996, the application of the SPSS 11.5, SYSTAT10.0 software and so on , the model of integrated cotton fiber quality index was established in the research, and the models presenting the effect of meteorological and ecological factors on cotton fiber length, strength, micronaire, and model of integrated cotton fiber quality , and GIS-based regional distribution system of integrated cotton fiber quality index was developed, and apply them to practice.1. Model of Integrated Cotton Fiber Quality IndexWith the experimental data of different qualities of spinning yarn, the analysis of cotton fiberquality by Principal Component Analysis method developed and confirmed several findings: 1) The single yarn strength is the key index that influences yarn quality. 2) The cotton fiber qualitiy is the crucial factors in determine spinning strength. 3).The strength on the same raw cottons are the same under different spinning yarn processshows the same tendency. 4) If the cotton fiber qualities are higher than others, their spinning strength is higher as well, no matter what spinning yarn process was carried with. The key indexes expressing the cotton fiber quality are fiber length, fiber strength, uniformity and micronaire. So,there established the the model of integrated fiber quality index (IFQI): IFQI = (Len - 10) / Str . IFQI model has many advances: explicit andmechanism, few independent variables, simple and intuitive, and integrated fiber quality index is directly related to the yarn strength and the spinning consistence index, furthermore, the model of the relationship of IFQI and SCI is established as: SCI=0.3684×IFQI+35.588. IFQI is a universal reference index for cotton fiber testing of the Ministry of Agriculture and the Ministry of Spin industry, hence,may be helpful in cutting offthe repetitive worrkload in cotton fiber testing.2. The Model of Cotton Fiber Quality Characters with Meteorological and Ecological Factors(1) The Model of Cotton Fiber Length Varied withMeteorological and Ecological Factors. Many experiments were conducted to analysis the effect of planting date, node position and branch position, abloom date and such meteorological and ecological factors on fiber length and fiber quality development. Results indicated that fiber length is mainly determined by cultivar charactorvistics meteorological and ecological factors. Thus, there suggested that the model of fiber length changes with branch node can represent the genetic background and the lowest temperature of the day and relative humidity effect on fiber length, and they are also factors that effect fiber length. Furthermore, it was confirmed that the relation tendency between the lowest temperature of the day time and the fiber length is same as the relation between the average night temperature and the fiber length. It also proposed in the modified model that the lowest temperature of the day time and the average night temperature greatly affect fiber length. Considering the difficulty on the observation of the average night temperature, the lowest temperature of the day replaced the average night temperature in the modified model. Integrated model of fiber length vairate with node positions and such meteorological and ecological factors is as follow: LEN_i=LEN_s×LENI×LENI_MIN LENI=0.049×SIN (0.767×PMSN_i-1.424)+1.010 LENI_MIN=-0.002×TAMIN²+0.0225×TAMIN+0.5942 This model not only emphasized the primary effect of qualities to fiber length, but also present the effect of meteorological and ecological factor on cotton fiber length.(2) The Model of Cotton Fiber Strength Varied with Meteorological and Ecological Factors. The genetic background plays a decicive role in impacting on ultimate fiber strength, and cotton fiber strength is very sensitive to climatic conditions. The research proved that during the average daily temperature, daily average precipitation, daily maximum temperature, and daily relative humidity are key factors that affect fiber strength. And Considering fiber strength is very sensitive environment factors, we proposed that single model and multiple models of fiber strength which involve single and many meteorological and ecologyical factors respectively, at last, the best model singled out is the interplay model between daily maximum temperature and relative humidity. That is STH=STHs×AMTRH_STH, AMTRH_STH=2.6384×AMT/RH+0.0261.(3) The Model of Cotton Fiber Micronaire Varied with Met-ecological Factors. The application of similar method of simulatting cotton fiber strength,the model about boll period meteorological factors affecting fiber micronaire was simulated. The model is MIC=MIC_s×DAT_MIC×ARF_MIC, DAT_MIC=0.0341 DAT²-1.5756 DAT+19.125 ARF_MIC= 0.8396EXP(0.0272×ARF).3. Model of Integrated Cotton Fiber QualityAccording to the conclusions above, the model of integrated cotton fiber quality was simulated.By application, the model of integrated cotton fiber quality has advantages, such as the explicit mechanism, few independent variables, simple and intuitive,and can predict the cotton fiber quality and spin yarn quality alike SCI. 4. Model and GIS-Based Access System on The Regional Distribution and Variation of Model of The Integrated Fiber QualityTaking MapObjects2.1 as investigative platform, adopting digital software and DBMS, using Visual Basic6.0, and then based on model of an integrated fiber quality index(IFQI), the system of regional distribution of IFQI was developed. It can predict and access cotton fiber length,fiber strength,micronaire and IFQI and their regional distribution.According to the conclusions above, and comparring with existed researches, we can thus conveniently draw out several items of innovations scattered in this dissertation as below:(1) On the basis of the previous research results and the present situations of cotton fiber testing system, we revised and reconstructed the integrated fiber quality exponential model, which could be shared by agricultural sections in assess of the integrated cotton fiber quality and the spinning departments in the evaluation of the yarn quality.(2) We successfully built up the meteorological and ecological models of main cotton fiber quality factors, namely, fiber length, fiber strength and micronaire, which were already involved in the integrated cotton fiber exponential model. Among them:The cotton fiber length met-ecological model was composed of the model relevant to cotton sympodial branch node and the model associated with the revised coefficients of met-ecological factors. Therefore, we could notice that the genetic characters were the decision-making factors in affecting the formation of cotton fiber length and also the impacts from meteorological factors in the model. Besides, this research effectively improved the model practicality by the replacement of night mean temperature with daily lowest temperature for the first time.We brought forward singular met-ecological factor models and also the multiple met-ecological factors' interactive models first, and then based on the cautiously comparison and tests we screened out the met-ecological model with interaction of highest temperature and relative humidity was the optimum one, which was not a simple statistical model but a mechanic model. The cotton fiber micronaire met-ecological model was proposed out in the similar way, we also considered of the interactions among met-ecological factors, configured out various of revised models, and at last the model with interaction between daily mean value and daily precipitation was singled out as the best met-ecological micronaire model.(3) The integrated cotton fiber quality exponential model was established for the first time in this area according to the national and international research reports.