Method for predicting element content of plant based on annual variation of element content of red date annual ring

Abstract

This invention relates to a method for predicting plant element content based on the interannual variation of element content in jujube tree rings. The method includes: (1) cutting off the main trunk of a jujube tree, cross-dating the annual rings and slicing them, measuring the nitrogen, phosphorus, and potassium content in each year of the trunk's annual rings, determining the correlation coefficients between the nitrogen, phosphorus, and potassium content in each year of the annual rings and the elemental indicators for the predicted year, and screening based on the obtained correlation coefficients to obtain screening indicators; (2) using the obtained screening indicators to establish multiple linear regression models for nitrogen, phosphorus, and potassium elements respectively, obtaining the optimal multiple linear regression model, and predicting the interannual variation of nitrogen, phosphorus, and potassium content in the annual rings. This invention's method for predicting plant element content based on the interannual variation of element content in jujube tree rings constructs a multiple linear regression model to predict the interannual variation of nitrogen, phosphorus, and potassium content in the annual rings, enabling balanced fertilization in jujube orchards.

Description

Technical Field

[0001] This invention belongs to the technical field of agricultural planting, specifically relating to a method for predicting plant element content based on interannual variations in element content in jujube tree rings. Background Technology

[0002] Mineral elements participate in various physiological and biochemical processes within fruit trees, regulating their life activities and playing a crucial role in their growth, development, and fruit quality. A balanced intake of nutrients is essential for the normal growth, development, and fruiting of fruit trees; a deficiency in any nutrient will cause varying degrees of harm. Achieving a balanced intake of nutrients in fruit trees is a critical issue in fruit tree cultivation. Traditional methods for assessing the nutritional status of fruit trees include morphological diagnosis, tissue analysis, and soil analysis. However, these methods have many limitations. For example, morphological diagnosis is used after nutrient deficiency symptoms have appeared, indicating significant damage to the tree's growth and inevitable yield loss. While soil analysis generally shows a close relationship with the nutritional status of fruit trees, its correlation is not as direct as that of plant analysis. Therefore, there is an urgent need for a method that can more accurately assess the nutritional status of fruit trees without affecting their growth and yield.

[0003] Trees absorb and accumulate mineral elements from the soil and air during their growth, and the changes in these mineral elements, combined with the growth characteristics of tree rings, collectively reflect changes in the external environment. Currently, the use of information contained in tree rings for related research is widely applied in environmental science, climatology, and ecology. Some studies indicate that tree rings do not passively record changes in soil nutrients; rather, the content of mineral elements in tree rings is a comprehensive reflection of environmental changes. Compared to leaf nutrition, the content of some elements in wood shows a stronger correlation with the content of elements in the soil.

[0004] In view of this, the present invention proposes a new fertilization method. Based on dendrochronology, the nitrogen, phosphorus and potassium content of tree discs collected from jujube orchards in the Tarim Basin is measured. By constructing a multiple linear regression model, the interannual variation of nitrogen, phosphorus and potassium content in jujube tree rings is predicted, providing a theoretical basis for revealing the changes in mineral element content in jujube tree rings and for rational fertilization in jujube orchards. Summary of the Invention

[0005] The purpose of this invention is to provide a method for predicting the elemental content of jujube plants based on the interannual variation of elemental content in jujube tree rings. By utilizing the nitrogen, phosphorus, and potassium content in jujube tree rings, a multiple linear regression model is constructed to predict the interannual variation of nitrogen, phosphorus, and potassium content in jujube tree rings, thereby enabling balanced fertilization in jujube orchards.

[0006] To achieve the above objectives, the technical solution adopted is as follows:

[0007] A method for predicting plant element content based on interannual variations in jujube tree rings includes the following steps:

[0008] (1) Cut off the main trunk of the jujube tree, cross-date the annual rings and slice the jujube annual rings according to the year, measure the nitrogen, phosphorus and potassium content in each annual ring of the main trunk, determine the correlation coefficient between the nitrogen, phosphorus and potassium content index of each year in the annual ring and the element index of the predicted year, and screen according to the obtained correlation coefficient to obtain the screening index.

[0009] (2) The screening indicators obtained in step (1) are used to establish multiple linear regression models for nitrogen, phosphorus and potassium elements, respectively, for the prediction of nitrogen, phosphorus and potassium, and then for fertilization.

[0010] Furthermore, in step (1), the jujube tree must be at least 7 years old.

[0011] Furthermore, in step (1), at least three jujube trees from the same region with similar growth conditions in terms of tree height, crown, and diameter at breast height are selected for cutting.

[0012] Furthermore, in step (1), the N content is determined using a Kjeldahl nitrogen analyzer, and the P and K contents are determined using inductively coupled plasma atomic emission spectrometry (ICP-AES).

[0013] Furthermore, in step (2), at least 2 / 3 of the element content data obtained in step (1) is used as the training set to establish a multiple linear regression model for nitrogen, phosphorus, and potassium elements, and the remaining data is used as the validation set to verify the accuracy of the model.

[0014] Furthermore, in step (2), after removing variables with no significant differences, a multiple linear regression model for predicting the content of nitrogen, phosphorus, and potassium elements is established.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0016] The present invention provides a method for predicting plant element content based on the interannual variation of element content in jujube annual rings. It utilizes the nitrogen, phosphorus, and potassium content in jujube annual rings to construct a multiple linear regression model for prediction, thereby reducing errors and making these indicators easy to detect. Detailed Implementation

[0017] To further illustrate the method for predicting plant element content based on interannual variations in jujube tree ring element content according to the present invention, and to achieve the intended purpose of the invention, the following detailed description, in conjunction with preferred embodiments, details the specific implementation, structure, features, and effects of the method for predicting plant element content based on interannual variations in jujube tree ring element content proposed by the present invention. In the following description, different "one embodiment" or "embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] The following will provide a more detailed description of the method for predicting plant element content based on interannual variations in jujube tree ring element content, using specific embodiments as examples:

[0019] Example 1.

[0020] The specific steps are as follows:

[0021] (1) In May 2021, 32 representative jujube orchards were selected as sample plots in four prefectures around the Tarim Basin in Xinjiang: Aksu Prefecture, Kashgar Prefecture, Hotan Prefecture, and Bayingolin Mongol Autonomous Prefecture. The jujube trees were 8 to 10 years old. Based on the size and topography of the orchards, three trees with similar growth conditions (height, crown size, and diameter at breast height) were selected from each orchard for destructive sampling. All experimental trees were healthy, disease-free, and mature fruiting trees with good growth. The main trunks were cut 5 cm above the grafting point and placed in resealable bags and marked. A 3 cm thick disc was cut from the main trunk 5 cm above the cut. The discs were allowed to dry naturally, polished, and split. The age of the trees in each orchard was determined using a magnifying glass. Under a microscope, using a stainless steel scalpel, the annual rings were sequentially cut from the cambium to the medulla, year by year. Samples from the same year were mixed and numbered. The annual ring samples were rinsed three times with deionized water, placed in a 105℃ oven for 30 minutes to decompose, and then dried at 80℃ to constant weight. After pulverizing with a universal high-speed grinder, the samples were passed through a 60-mesh sieve and stored in resealable bags. Subsequently, the annual ring samples were digested by sulfuric acid-hydrogen peroxide and HNO3-HClO4, and the nitrogen, phosphorus, and potassium contents for each year from 2013 to 2020 were determined. The nitrogen content was determined using a Kjeldahl nitrogen analyzer, and the phosphorus and potassium contents were determined using inductively coupled plasma atomic emission spectrometry (ICP-AES).

[0022] The results of the measurements are shown in Table 1-3.

[0023] Table 1. Nitrogen content in jujube tree rings from 2013 to 2020 (unit: g / kg)

[0024]

[0025]

[0026]

[0027]

[0028] Table 2. Potassium content in jujube tree rings from 2013 to 2020 (unit: g / kg)

[0029]

[0030]

[0031]

[0032]

[0033] Table 3. Phosphorus content in jujube tree rings from 2013 to 2020 (unit: mg / kg)

[0034]

[0035]

[0036]

[0037]

[0038]

[0039] (2) The data were sorted out separately. 66 sets of data (data from orchards numbered 1-22) were used as the training set for the selection of indicators, the construction of the multiple linear regression model and the optimization of the model. The remaining 30 sets of data (data from orchards numbered 23-32) were used as the validation set to verify the accuracy of the model.

[0040] ① Construct a multiple linear regression model for nitrogen.

[0041] Table 4. Phenotypic correlation between nitrogen content in jujube tree rings from 2013 to 2019 and nitrogen content in 2020.

[0042]

[0043] Note: * P<0.05; ** P<0.01

[0044] The nitrogen content in the jujube tree rings from 2013 to 2020 was represented by different parameters, and the corresponding parameters are shown in Table 5 below.

[0045] Table 5

[0046]

[0047] Based on Table 4-5, the indicators were screened according to the obtained correlation coefficients. The multiple linear regression relationship between the screened indicators and the N element content in 2020 was analyzed to obtain the following model:

[0048] X=0.849+0.084X1+0.637X2-0.378X3-1.099X4+0.751X5+0.768X6+0.313X7

[0049] (R 2 =0.818, P<0.0001)

[0050] After removing indicators that contribute little to the model, we continue with the regression to obtain the following model:

[0051] X = 2.418 + 0.925X⁴ (R) 2 =0.608, P<0.0001)

[0052] ② Construct a multiple linear regression model for phosphorus.

[0053] Table 6. Phenotypic correlation between phosphorus (P) content in jujube tree rings from 2013 to 2019 and P content in 2020.

[0054]

[0055] Note: * P<0.05; ** P<0.01

[0056] The phosphorus (P) content in the annual rings of jujubes from 2013 to 2020 was represented by different parameters, as shown in Table 7 below.

[0057] Table 7

[0058]

[0059] Based on Table 6-7, the indicators were screened according to the obtained correlation coefficients. The multiple linear regression relationship between the screened indicators and the P element content in 2020 was analyzed to obtain the following model:

[0060] Y=5.853+0.328Y1+1.712Y2-1.835Y3+0.5Y4-0.603Y5+0.312Y6+1.328Y7

[0061] (R 2 =0.860, P<0.0001)

[0062] After removing indicators that contribute little to the model, we continue with the regression to obtain the following model:

[0063] Y=54.822+1.884Y2-1.686Y3+1.350Y7(R 2 =0.850, P<0.0001)

[0064] ③ Construct a multiple linear regression model for potassium.

[0065] Table 8. Phenotypic correlation between K content in jujube tree rings from 2013 to 2019 and K content in 2020.

[0066]

[0067] Note: * P<0.05; ** P<0.01

[0068] The K content in the jujube tree rings from 2013 to 2020 was represented by different parameters, as shown in Table 9 below.

[0069] Table 9

[0070]

[0071] Based on Tables 8-9, the indicators were screened according to the obtained correlation coefficients. The multiple linear regression relationship between the screened indicators and the K element content in 2020 was analyzed to obtain the following model:

[0072] Z=1.509+0.321Z3-0.521Z4-0.071Z5+0.974Z6+0.036Z7

[0073] (R 2 =0.534, P<0.0001)

[0074] After removing indicators that contribute little to the model, we continue with the regression to obtain the following model:

[0075] Z = 1.567 + 0.779Z6(R) 2 =0.475, P<0.0001)

[0076] (3) Validation of the accuracy of the multiple linear regression model

[0077] The remaining 30 sets of data were substituted into the prediction models for the interannual variations of nitrogen, phosphorus, and potassium content, and the predicted N, P, and K content were compared with the actual values.

[0078] Wherein, prediction accuracy = min(actual, prediction) / max(actual, prediction) × 100%

[0079] Table 10. Validation of the accuracy of the regression model for predicting the interannual variation of nitrogen content in jujube tree rings.

[0080]

[0081]

[0082] Table 11. Validation of the accuracy of the regression model for predicting the interannual variation of phosphorus content in jujube tree rings.

[0083]

[0084] Table 12 Validation of the accuracy of the regression model for predicting the interannual variation of potassium content in jujube tree rings.

[0085]

[0086] As shown in Tables 10-12, the prediction accuracy of nitrogen (N) content in jujube tree rings all exceeded 90%, with the unoptimized model achieving an even higher accuracy of 94.16%. The prediction accuracy of phosphorus (P) content all exceeded 85%, with the optimized model achieving an even higher accuracy of 86.38%. The prediction accuracy of potassium (K) content all exceeded 87%, with the optimized model achieving an even higher accuracy of 87.91%. Therefore, this model can be used to predict the interannual variations of nitrogen, phosphorus, and potassium content in jujube plants, enabling rational fertilization.

[0087] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A method for predicting the element content of a plant based on the interannual variation of the element content of the annual rings of Ziziphus jujuba, characterized in that, It comprises the following steps: (1) intercept the main stem of the jujube tree, cross-dating the annual rings and slice the jujube annual rings according to the year, determine the nitrogen, phosphorus and potassium element content in each annual ring of the main stem, determine the correlation coefficient of the nitrogen, phosphorus and potassium element content index in each annual ring and the element index of the predicted year, screen according to the obtained correlation coefficient to obtain the screening index; The correlation coefficient is the correlation coefficient of the phenotypic correlation of the nitrogen, phosphorus and potassium element content index in each annual ring and the element index of the predicted year; (2) the screening index obtained in the step (1) is used to establish a multiple linear regression model of nitrogen, phosphorus and potassium elements, and the best multiple linear regression model is obtained for the prediction of the interannual variation of nitrogen, phosphorus and potassium element content in the annual ring.

2. The method of claim 1, wherein, In step (1), the jujube tree is at least 7 years old.

3. The method of claim 1, wherein, In step (1), at least 3 trees with similar growth conditions of tree height, crown and diameter at breast height are selected for interception.

4. The method of claim 1, wherein, In step (1), the N content is determined by Kjeldahl nitrogen determination instrument, and the P and K contents are determined by inductively coupled plasma emission spectrometry.

5. The method of claim 1, wherein, In step (2), more than 2 / 3 of the element content data obtained in step (1) are used as a training set to establish a multiple linear regression model of nitrogen, phosphorus and potassium elements, and the remaining data are used as a validation set to verify the accuracy of the model.

6. The method of claim 1, wherein, In step (2), the multiple linear regression model for predicting the nitrogen, phosphorus and potassium element content is established after eliminating variables with no significant difference.

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