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Analysis And Evaluation Of Nutrient Status Of The Carya Cathayensis Stands Soil In Ningguo City

Posted on:2018-10-16Degree:MasterType:Thesis
Country:ChinaCandidate:Q WeiFull Text:PDF
GTID:2370330518978052Subject:Garden Plants and Ornamental Horticulture
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Carya cathayensis is a special economic tree species in China.It has significant economic and social benefits because of its high quality nuts and strong wood which are often used as raw materials in military-industrial industry.The management of pecan forest is getting more and more attention with the increasing of the total area of pecan planting.It is urgent to find out the soil nutrient status which can guide the management of soil nutrient and improve the fertility of forest land in pecan forest.In this paper,the author selected Ningguo typical pecan forest as object to analyze and evaluate the soil nutrients in order to find out soil nutrient distribution.The following results have been obtained through analysis and evaluation of the county in 5 soil samples.1.The analysis of soil nutrient showed that the content of ferrum which was between 10.33 mg/kg and 28.93mg/kg and manganese which was between 10.21 mg/kg and 23.49mg/kg in soil were at a high level.The content of organic matter which was between 9.9 g/kg and 33.7g/kg,effective phosphorus which was between 8.9 mg/kg and 37.1 mg/kg and zinc which was between 0.36 mg/kg and 2.54mg/kg in soil were at medium level.The content of total nitrogen which was between 0.34 g/kg and 1.46g/kg and available kalium which was between 45.0 mg/kg ane 266.0mg/kg in soil were at a low level.The content of copper which was 0.03 in soil in Xianxia was at a very low level.The content of copper in soil in Hule,Jialu,Wanjia and Nanji which was between 0.39 mg/kg ane 2.20 mg/kg was at medium level.The soil pondus hydrogenii was mainly acidity.Therefore,it was necessary to increase the application of nitrogen,phosphorus,potassium and copper fertilizers which can improve the soil fertility of pecan forest in Ningguo.2.The variability analysis of soil nutrient showed that the variation coefficient of pondus hydrogenii was 9.06 which was at the very lowest level and uniform in spatial distribution.The spatial variability of organic matter,ferrum,manganese element was 28.27?20.70?19.66 which was at the lower level.The spatial difference of fertility level was not significant.The spatial variability of available kalium,total nitrogen and effective phosphorus spatial variability coefficient was 40.98?37.88?32.58 which was at the medium level.The spatial variation coefficient of zinc was 41.81 which was at the high level.The spatial variation coefficient of copper was 68.12 which was too large to balance the soil fertility.The content of copper in Xianxia is lower than in Hule,Jialu,Wanjia and Nanji.3.The correlation analysis of soil nutrient showed that the correlation coefficient between organic matter and total nitrogen was the highest,reaching 0.940,so the interaction between them was obvious.Organic matter was positively correlated with total nitrogen,available phosphorus,available kalium,copper,zinc,ferrum and manganese.Therefore,and the management of organic matter content is the key of soil fertility management.4.The comprehensive evaluation of soil fertility showed that the soil fertility of pecan forest was at a medium level because the score between 0.5 and 2 was more than 50%.The all score was between-0.076 and 2.886.The level of soil fertility in Hule was 2.538 which was the highest.The level of soil fertility in Jialu was 1.758 which was higher than Nanji.The level of soil fertility in Nanji was 1.096.The level of soil fertility in Wanjia was 0.721 which was lower.The level of soil fertility in Xianxia was 0.137 which was the lowest.The fitting curve of the relationship between soil fertility and yield showed that when the soil fertility was 1.85,the yield reached 3064.5 kg/ hm2.Therefore,it is important to improve the management of soil nutrient in Xianxia.
Keywords/Search Tags:Carya cathayenensis, Soil fertility, Soil nutrients, Principal Component Analysis
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