Yield-based soil fertility prediction method for constructing geographic minimum data set
A soil fertility and prediction method technology, applied in prediction, data processing applications, instruments, etc., can solve the problems of immature soil fertility evaluation of Camellia oleifera, neglecting the role of trace elements, etc. Effect
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Embodiment 1
[0046] Camellia oleifera soil samples were taken within the scope of Zhejiang Province. According to the average yield of the sample plot and the county where the sample plot is located, the oil production in the sample plot is greater than 150kg ha -1 , 75-150kg·ha -1 , less than 75kg·ha -1 Three levels to divide the soil measurement results.
[0047] When sampling, the sample plot is divided into upper, middle and lower slopes. The S-shaped sampling method is used to collect 0-40cm layer of soil, among which 15-20 sample points are randomly selected for each slope, and the sample weight of each sample point is not less than 100g. After fully mixing the samples of each slope, take 1kg by quartering method, put them into plastic bags, number them, register the sample information, take them back to the laboratory to air-dry, and test the contents of various fertility indicators. The specific division results of the test and the content of soil fertility indicators in each cou...
Embodiment 2
[0072] The minimum data set fertility index construction:
[0073] The index content measured in Table 1, Table 2 and Table 3 of Example 1 utilizes SPSS software to carry out principal component analysis, and the results are as shown in Table 6;
[0074] Table 6 Eigenvalues and contribution rates of principal components of each factor
[0075]
[0076]
[0077] According to Table 6, according to the principle that the characteristic value is greater than 1 and the cumulative contribution rate is greater than 70%, 5 principal components are extracted; according to the calculation formula of the principal components, the results of principal component analysis are shown in Table 7;
[0078] Table 7 Rotation component matrix
[0079]
[0080] It can be seen from Table 7 that the main factors determining the size of the main component 1 are exchangeable calcium, magnesium, potassium and pH, which can be classified as exchangeable nutrients. The main components that de...
Embodiment 3
[0094] The establishment of the minimum data set fertility index:
[0095] The standardization of soil fertility indicators is an important part of soil quality evaluation. The relationship between soil total nitrogen, available phosphorus, exchangeable calcium and magnesium, available copper and available iron and crop growth is a parabolic curve, that is, the indicators have an optimal value for crop growth and development. The growth range, the corresponding curve can be converted into a broken line function by determining the critical value, as described in Chinese literature: Soil Quality Index and Evaluation (Xu Jianming, Zhang Ganlin, Xie Zhengmiao, etc., Science Press, 2010). The present invention draws up critical value according to document: the data of Zhejiang forestry soil (Ye Zhongjie, Chai Xizhou, Zhejiang Science and Technology Press, 1986) and this research data, critical value result is as shown in table 9;
[0096] Table 9 Critical value of Camellia oleifera...
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