Growth model construction based evaluation method for branch pulling of trellised pear trees

Abstract

A growth model construction based evaluation method for branch pulling of trellised pear trees. A "double-armed parallel" trellised pear tree is taken as a research object, branch pulling treatment is carried out on one-year shoots of the pear tree, a linear or nonlinear regression equation is established by detecting relevant indexes of the length and thickness of the shoots and the growth of fruits, and the dynamic trend of fruit quality formation under different treatment conditions is analyzed. Results show that, in a trellised cultivation mode, different branch treatment angles are closely related to the transport efficiency of carbon from a "source" (branches and leaves) to a "sink" (fruits) of and the growth vigor of the pear tree. The nutritional management of the branches and the fruits can be coordinated and enhanced within 95-110 days after full blooming, so that the formation of the fruit quality and the stabilization of the tree vigor in the later period can both be ensured. The solution provides a theoretical basis for formulating rational technical measures for standardized and refined management of "Cuiguan" trellised pear tree bodies.

Description

A canopy pear tree branch pulling evaluation method based on a growth model TECHNICAL FIELD

[0001] The present application relates to the technical field of pear tree planting management, in particular to a canopy pear tree branch pulling evaluation method based on a growth model. BACKGROUND

[0002] At present, the pear orchard cultivation area in China is about 100.47 million mu, accounting for 70.85% of the world's pear cultivation area, ranking first in the world. With the sharp rise in labor costs, the cultivation mode of pear has changed from traditional manual management to labor-saving, mechanized and automated mode. Therefore, it is inevitable trend to develop a simple, high-quality and high-yield tree management mode. In recent years, the "double-arm forward type" pear canopy cultivation technology with the characteristics of labor-saving, machine-friendly and high quality has attracted much attention. Under the new cultivation mode, how to evaluate the influence of different manual management methods on the growth state of fruit trees has become an important issue.

[0003] It is known that branch pulling is a practical way to inhibit vegetative growth, enhance canopy light interception and improve fruit tree productivity. Due to the influence of inherent growth habits, different varieties have different physiological responses to different pulling times or angles, resulting in different distribution results of long and short branches in different parts or quantities. In the canopy pear cultivation mode, the growth of fruiting branches is controlled within a relatively fixed size, which has an important influence on the expansion of the tree canopy. At the same time, the number and length, thickness of fruiting branches on the trunk determine the recovery potential of the branches to a certain extent, control the number and attachment points of leaves, and are the basis for fruit formation this year or next year, and also the basis for further shaping the tree shape by pruning, so selecting the appropriate pulling angle has important practical significance.

[0004] There are few reports on the research of pear tree growth model in the prior art, especially on the new type of canopy cultivation mode "double-arm forward type" pear tree with strong growth polarity symmetry, and there are few reports on the influence of branch pulling on the branch characteristics and fruit quality. SUMMARY

[0005] The purpose of the present application is to provide a canopy pear tree branch pulling evaluation method based on a growth model. The present application takes "double-arm forward type" canopy pear tree as the research object, and performs branch pulling treatment on the 1-year-old new shoots. By detecting the length and thickness of the new shoots and the growth of the fruit, a linear or nonlinear regression equation is established, and the dynamic trend of fruit quality formation under different treatment conditions is analyzed. The present application can provide a theoretical basis for formulating reasonable technical measures for the standardization and fine management of 'Cui Guan' canopy pear tree.

[0006] The above-mentioned technical objective of this application is achieved through the following technical solution: a method for evaluating branch training of pear trees on trellises based on a growth model, comprising the following steps:

[0007] Step 1: Select the double-arm parallel pear tree in the trellis cultivation mode, select suitable branches and pull them at different angles for different experimental groups, and then fix them on the trellis;

[0008] Step 2: Branch trait determination. The initial budding date of the shoots is defined as day 0 of the initial growth stage, marked as D0. The length and thickness of the newly sprouted shoots on the branches are measured and recorded at regular intervals.

[0009] Step 3: Determination of fruit quality indicators. Fruits are picked according to the experimental group, and the fruit quality indicators are measured.

[0010] Step 4: Data processing and growth model construction. Plot a Logistic regression graph of the growth process of branch length and thickness. With date as x and branch length or thickness as y, the characteristic values ​​of new shoot growth are calculated according to equations (1)-(6):

[0011] In the formula: y is the branch length or thickness; y′ is the value of the Logistic model. Transform into a linear model The values ​​are defined later. t is the shoot growth time; k is the theoretical extreme value of shoot growth length; a and b are parameters; t1 is the start time of rapid shoot growth; t2 is the end time of rapid shoot growth; v m The maximum relative growth rate; t m The time when the maximum relative growth occurs. t1 and t2 are the two points where the rate of change in the amount of fertilizer is the fastest over consecutive days, that is, the dividing point from budding to rapid growth and then to slow growth. t2 to t1 is the peak growth period.

[0012] Scatter plots of fruit quality indicators were drawn, and univariate analysis was performed. Pearson correlation analysis was conducted, and the LSD test was used to evaluate the differences between the means (P<0.05). The full bloom period was defined as day 0 of fruit development and growth. The number of days after the full bloom period was x, and each fruit indicator was y. The growth rate equations corresponding to each fruit indicator were obtained by online differentiation. The inflection point prediction adopted -b / 2a (applicable to quadratic equations) and the second derivative f″(x)=0 (applicable to cubic equations).

[0013] Step 5: Construct a growth model for new shoot length and thickness under different branching angles. Use equation (1) to fit the growth data of new shoot length and thickness of the experimental group under different branching conditions to obtain the fitting curve. The correlation coefficient is greater than 0.9, indicating that the correlation between the fitting equation and the measured data is extremely significant. The constructed Logistic model has a reliable predictive reference for the development process of new shoots during this growth period.

[0014] Step six, the new shoot growth stage division under different branch pulling angles, using equations (3) (4) (5) (6) to calculate the branch shoot growth rate inflection point and other phenological parameters, the new shoot length and thickness growth can be divided into three stages of initial growth (0, t1), rapid growth period (t1, t2), and late growth (t2, t n );

[0015] Step seven, evaluating the change of new shoot length and thickness growth rate under different branch pulling angles, determining whether there is significant difference between different test groups in each growth stage;

[0016] Step eight, mathematical equation model construction of fruit growth under different branch pulling angles, using one-dimensional quadratic equation and one-dimensional cubic equation to fit the fruit related indexes with the days after full bloom;

[0017] Step nine, comparing the quality characteristics of mature fruits under different branch pulling angles, comparing whether there is obvious difference between different test groups of each fruit index.

[0018] The further setting of the present application is that in step one, the branch selection method is: at the position of 1.0-2.0 m away from the center trunk of each tree, 1-year-old branches with the same orientation, similar thickness and length and natural growth angle are selected for different angle pulling in different groups, and the angles are 60°, 30° and 0°.

[0019] The further setting of the present application is that in step two, the length and thickness of newly sprouted branches on the branches are measured and recorded every 6-10 days, the length is measured by a fixed ruler, the diameter is measured by an electronic vernier caliper, and then the growth thickness is calculated according to the area formula.

[0020] The further setting of the present application is that in step three, the Cui Guan fruits without obvious mechanical damage and pests and diseases are picked according to the test groups, the fruit quality is weighed by an electronic balance, the fruit length and width are measured by a vernier caliper, the fruit shape index is calculated, the fruit shape index = maximum longitudinal diameter / maximum transverse diameter; the fruit hardness is measured by a fruit hardness meter at the maximum transverse diameter of the fruit, 3 times are measured for each group, and the average value is taken; the soluble solid content is measured by a sugar tester; the titratable acid content is measured by an acidimeter, each sample is measured 3 times, and the average value is taken.

[0021] The further setting of the present application is that in step four, the k value is determined according to the three-point rule, the observation values (t a ,y a ), (t b ,y b ) and (t c ,y c ) are taken, so that:

[0022] The further setting of the application is that in step four, the duration of rapid growth T (T = t2-t1), the initial growth Rapid growth period Late growth According to the k value and the y value, a series of y' values corresponding to different time points are obtained, then a straight line regression equation is fitted with time as the horizontal coordinate and y' as the vertical coordinate, and a determination coefficient R is obtained 2 value.

[0023] The further setting of the application is that in step eight, the five growth indexes of the fruit growth process, i.e., the transverse diameter, the soluble solid content, the hardness, the weight and the longitudinal diameter, are analyzed under each test group, a quadratic equation is fitted for the soluble solid content index, the weight index and the longitudinal diameter index, and a cubic equation is fitted for the transverse diameter and the hardness index to construct the corresponding fitting model.

[0024] The further setting of the application is that in step eight, curves are drawn according to the time points of 78d, 87d, 100d, 112d, 119d and 127d after the flowering period.

[0025] The beneficial effects of the application are that the application takes the "double-arm forward type" shed-framed pear tree as the research object, and the one-year-old new shoots are treated by pulling branches (T1 = 60°, T2 = 30°, T3 = 0°), the length and thickness of the new shoots and the growth of the fruit related indexes (fruit weight, transverse diameter, longitudinal diameter, hardness, soluble solid content (also known as sugar content), titratable acid, sugar acid ratio) are detected, a linear or nonlinear regression equation is established, and the dynamic trend of the fruit quality formation under different treatment conditions is analyzed. The test results of the application prove that under the shed-framed cultivation mode, different branch treatment angles are closely related to the output efficiency of the reserve carbon "source" (shoots, leaves) to the "sink" (fruit) and the growth potential of the pear tree. Coordinating and enhancing the nutrition management of the shoots and the fruit within 95-110 days after the flowering period may be beneficial to the formation of the fruit quality and the stabilization of the tree potential in the later period. The application can provide a theoretical basis for formulating reasonable technical measures for the standardization and fine management of the 'Cui Guan' shed-framed pear tree. BRIEF DESCRIPTION OF DRAWINGS

[0026] Fig. 1 is a schematic diagram of the test design of the application (A in Fig. 1), and the shed frame is a pear tree before being put on the frame (B in Fig. 1);

[0027] Fig. 2 is a schematic diagram of the shed frame for different pulling branch angle treatments of the pear tree;

[0028] Figure 3 is the growth length (A in Figure 3), thickness (B in Figure 3) fitting curve of the one-year-old new shoots of the 'Cuiguan' pear of the application, T1 = 60° branch pulling treatment, T2 = 30° branch pulling treatment, T3 = 0° branch pulling treatment, and each point represents the average value of the branch and shoot growth determination results of T1-T3 treatment groups;

[0029] Figure 4 is the variation law of the longitudinal diameter of the fruit of the application;

[0030] Figure 5 is the variation law of the transverse diameter growth dynamic of the fruit of the application;

[0031] Figure 6 is the dynamic variation law of the fruit weight of the application;

[0032] Figure 7 is the dynamic variation law of the soluble solids of the fruit of the application;

[0033] Figure 8 is the dynamic variation law of the fruit hardness of the application;

[0034] Figure 9 is the difference in the quality of the mature fruit of the 'Cuiguan' pear under different branch pulling angles of the application. DETAILED DESCRIPTION

[0035] EMBODIMENT

[0036] 1. Materials and methods

[0037] 1.1 Test site overview

[0038] The test site is located in Jiangxia District, Wuhan City, Hubei Province, and is located in the transition section from Jianghan Plain to E'nan Hilly, with soil type of yellow-brown soil, an altitude of 30 m (N 30°17'24"E 114°8'55"), belonging to subtropical monsoon climate, with an average annual temperature of 15.9-17.9°C, and an average annual precipitation of 1260.6 mm.

[0039] 1.2 Test materials

[0040] The test was carried out in the double-arm forward type shed frame pear test base of the Fruit and Tea Institute of Hubei Academy of Agricultural Sciences. The test tree species were all 1-year-old seedling grafts planted in January 2019, the test variety was 'Cuiguan' (Pyrus pyrifolia nakai cv. Cuiguan), the pollination variety was 'Wonhwang' (P. pyrifolia Nakai cv. Wonhwang), and the 'Cuiguan' double-arm mode pear trees with healthy and uniform tree vigor were selected and labeled, and the standardization of water and fertilizer management was carried out according to the technical regulations of 'double-arm pear'.

[0041] 1.3 Test design

[0042] Three experimental plots were set up in the plantation, each plot including 8-9 ‘CuiGuan’ trees with healthy growth and consistent vigor (a1, 9 trees; a2, 9 trees; a3, 8 trees), totaling 26 trees (A in FIG. 1), and the trees were treated by pulling branches and setting up in early February 2023 (B in FIG. 1). The selection method of branches: at a distance of 1.0-2.0 m from the center trunk on both arms of each tree, 1-year-old branches with similar orientation, thickness, and length and natural growth angle were selected for different angle pulling branches, with angles of 60° (T1), 30° (T2), and 0° (T3) (i.e., nearly parallel to the ground), and then fixed on the shelf (as shown in FIG. 2). The number of branches pulled in each angle treatment on each tree was 10-15, and the measurement position was marked. The thickness measurement point was about 3 cm from the base of the branch, and the length was the distance from the base of the branch to the terminal bud. The length and thickness of newly sprouted branches were measured and recorded every 6-10 days.

[0043] 1.4 Experimental methods

[0044] 1.4.1 Branch trait determination

[0045] The initial sprouting of CuiGuan branches in 2023 occurred on March 18, which was defined as the initial growth day 0, marked as D0. The flowering period was on March 20, which was defined as the 0th day of fruit development growth. According to the branch hanging number on the test tree, the length and diameter of the newly sprouted branches were measured and recorded. The length was measured with a fixed ruler, and the diameter was measured with an electronic vernier caliper, and then the growth thickness (i.e., cross-sectional area S, Cross-sectional area of branch base, CSAB) was calculated according to the area formula (S = π·(d / 2) 2 .

[0046] 1.4.2 Fruit quality index determination

[0047] CuiGuan fruits without obvious mechanical damage and pests and diseases were picked according to the experimental groups, and the fruit quality was determined. The fruit quality was determined by electronic balance, and the fruit shape index was calculated (fruit shape index = maximum longitudinal diameter / maximum transverse diameter). The fruit hardness was measured using a GY-4 digital fruit hardness tester (Zhejiang Topuynong Technology Co., Ltd.), and the average value was taken from 3 measurements. The soluble solid content was measured using a PAL-1 portable digital sugar meter [produced by ATAGO (Ato) Scientific Instruments Co., Ltd., Japan], and the titratable acid content was measured using a PAL-Easy portable digital acidity meter [produced by ATAGO (Ato) Scientific Instruments Co., Ltd., Japan]. Each sample was measured 3 times, and the average value was taken.

[0048] 1.5 Data processing and growth model construction

[0049] Data were arranged by Excel 2013, and the Logistic model of branch growth was calculated according to the following equation. The Logistic regression graph of branch length and thickness growth process was drawn by Origin 9.0 software (with date as x, and branch length or thickness as y), and the characteristic value of new shoot growth was calculated according to equations (1)-(6). The scatter plot of fruit weight, transverse diameter, longitudinal diameter, hardness, etc. was drawn by GraphPad 8 software, and single factor ANOVA (ANOVA) was performed by SPSS 20.0 software. Pearson method was used for correlation analysis, and LSD test was used to evaluate the difference between the mean values (P<0.05). The growth rate equation of each fruit index was obtained by using Wolfram Alpha online derivative with the number of days after full bloom as x and each fruit index as y, and the inflection point prediction used-b / 2a (for quadratic term equation) and second derivative f''(x)=0 (for cubic term equation).

[0050] The value of k was determined according to the three-point rule. The observation values (t a ,y a ), (t b ,y b ) and (t c ,y c ) were taken at equal intervals, so that:

[0051] The duration of rapid growth T (T=t2-t1), the initial growth period of rapid growth late growth According to the value of k and y, a series of y' values corresponding to different time points were obtained. Then the time was taken as the horizontal coordinate and y' as the vertical coordinate to fit the linear regression equation, and the determination coefficient R 2 value was obtained.

[0052] In the formula: y is the length or thickness of the branch; t is the growth time of the branch; k is the theoretical maximum value of the length of the branch growth; a and b are parameters; t1 is the starting time of rapid growth of the branch; t2 is the termination time of rapid growth of the branch; v m is the maximum relative growth rate; t m is the time when the maximum relative growth rate occurs. t1 and t2 are the two points with the fastest rate of change in consecutive days, i.e. the dividing point from germination to rapid growth into slow growth, and t2-t1 is the peak growth period.

[0053] 2 Results and analysis

[0054] 2.1 Construction of new shoot length and thickness growth model under different pulling branch angles

[0055] The growth of new shoot length and diameter in trellis pear trees can be fitted using formula (1), where the fitted curves for length and diameter growth are shown in Figure 3. It can be seen that the new shoots under different branching conditions exhibit an S-shaped growth trend of "slow-fast-slow (stable)". The growth data of new shoot length and diameter in other treatment groups under different branching conditions were fitted, and the correlation coefficients all exceeded 0.9, indicating that the correlation between the fitted equation and the measured data reached a highly significant level. The theoretical extreme value k is also very close to the measured value (see Table 1). Therefore, the constructed Logistic model has a reliable predictive reference for the development process of new shoots during this growth period.

[0056] 2.2 Classification of new shoot growth stages under different branch pulling angles

[0057] Based on formulas (3), (4), (5), and (6) in data processing section 1.4, the inflection point of shoot growth rate and other phenological parameters were calculated (Table 2). The growth of new shoot length and thickness can be divided into the initial growth stage (0, t1), the rapid growth stage (t1, t2), and the later growth stage (t2, t3). n The three stages (Table 3) show that, in terms of length growth, although the inflection point of the rapid growth phase in group T1 was delayed by about 2 days compared to T2 and T3 (April 14th) (April 16th), there was no significant difference in the duration of the initial growth phase and the rapid growth phase among the three treatments, and the maximum relative growth rate v m There was no significant difference (P>0.05). In terms of girth development, the rapid growth termination time t2 of group T3 was significantly shorter than that of groups T1 and T2 (P<0.05), and the duration of the rapid growth period was also significantly shorter than that of groups T1 and T2 (P<0.05), which means that group T3 entered the slow growth state earliest.

[0058] Table 1. Logistic model parameters and test indices for the growth of new shoots of 'Crimson Crown' under the 'Double-Armed Pear' tree shape.

[0059] (Note: The p-values ​​for all the above processed data are less than 0.01. Length unit: cm, thickness unit: mm) 2 )

[0060] Meanwhile, as shown in Table 2, under different treatments, the rapid growth initiation time (t1) of length growth gradually advanced as the branch angle decreased; conversely, the rapid growth initiation time of thickness growth gradually delayed. Among the thickness growth characteristics, the inflection point of maximum relative growth (t1)... m The T3 group emerged nearly a week earlier (6.14 days) than the T1 group, and the former's maximum relative growth rate v m It is about 2.02 times faster than the latter, and the overall trend is T3 > T2 > T1, but this trend is not significant in length growth (P > 0.05).

[0061] Table 2 New shoot length and diameter growth characteristics

[0062] t1 is the fast growth initiation time, d; t2 is the fast growth termination time, d; v m is the maximum relative growth rate; t m is the time of maximum relative growth, d. The new shoot length and diameter growth values of the three zone groups (a1, a2, a3) of pear trees are shown as the average value ± standard error of each treatment (n = 30-45 branches / treatment). Different letters in each column indicate significant differences between treatments (P < 0.05).

[0063] 2.3 Changes in the length and diameter growth rates of new shoots under different pulling angles

[0064] The "double-arm forward" shed pear trees have the main axis in the east-west or north-south direction, and the important feature of symmetrical growth distribution of branches and leaves. The growth rate of the shoots on the main branches determines the sustainable expansion structure of the crown to a certain extent. Table 4 shows that in the early growth period, there is no significant difference in the average growth rate of length among the three groups (P > 0.05), and the average growth rate of diameter of T3 is significantly higher than that of T1 and T2; in the fast growth period, the average growth rate of length is T2 > T1 > T3, and there is a significant difference between T3 and T2 (P < 0.05), and the average growth rate of diameter of T3 is significantly higher than that of T1 and T2, similar to the case in the early growth period; in the late growth period, the average growth rate of length is T2 > T1 > T3, and there is a significant difference between T3 and T2 (P < 0.05), and the average growth rate of diameter shows a trend of T3 > T2 > T1, and there is a significant difference among the three (P < 0.05). Overall, in terms of length growth rate, there is no significant difference between T1 and T3 groups in the three periods, and T2 has a relatively high average growth rate in the fast growth period and the late growth period. However, in terms of diameter growth, T3 group is significantly higher than T1 and T2 groups, especially in the late growth period.

[0065] Table 3 New shoot length and diameter growth development process

[0066] Table 4 Comparison of average growth rates of new shoot length and diameter

[0067] The new shoot length and diameter growth rate values of the three zone groups (a1, a2, a3) of pear trees are shown as the average value ± standard error of each treatment (n = 30-45 branches / treatment). Different letters in each column indicate significant differences between treatments (P < 0.05). Set March 18 as the starting date to calculate t0 = 0, and August 1 as the cutoff date for the late growth period, t0 = 0.

[0068] 2.4 Mathematical equation model construction of fruit growth under different pulling branch angles

[0069] The monomial quadratic equation and the monomial cubic equation were used to fit the fruit-related indicators and days, which had good fitting degree and could study the change law of the related indicators in the fruit growth cycle. Through the analysis of the growth of the fruit in the process of the transverse diameter, sugar content, hardness, weight and longitudinal diameter under three different angle treatments, the curves were drawn according to the time points of 78d (June 7), 87d (June 16), 100d (June 29), 112d (July 11), 119d (July 18) and 127d (July 26) after the flowering period.

[0070] The monomial quadratic equation was used to fit the sugar content, weight and longitudinal diameter, and the monomial cubic equation was used to fit the transverse diameter and hardness indicators and construct the corresponding fitting model, and the related parameters were shown in Table 5. The results showed that the weight, longitudinal diameter and transverse diameter had higher data fitting degree, R 2 The fitting degree was close to 0.90. The corresponding fitting curve and derivative function graph were shown in FIG. 6, FIG. 4 and FIG. 5. From the fruit transverse diameter fitting curve (FIG. 5), the T1, T2 and T3 fitting curve trends were basically similar, the fruit transverse diameter increased with the increase of time, and the increase rate of the three treatment groups showed a downward trend; from the sugar content fitting curve (FIG. 7), the T1, T2 and T3 fitting curve trends were basically similar, the T3 fitting curve had a lower growth rate than T1 and T2 in the early stage, but exceeded T1 and T2 in the later stage, and from the growth rate, the fruit sugar content growth rate of T1 and T2 showed a downward trend, while 90° showed an upward trend; from the fruit hardness fitting curve (FIG. 8), the T1 and T3 fitting curve trends were basically similar, showing a positive “U” shape, and the T2 fitting curve trend showed a negative “U” shape, the fruit hardness increased with the increase of time, and from the growth rate, the increase rate of T1 and T3 showed an upward trend, while T2 showed a slow downward trend; from the fruit weight fitting curve (FIG. 6) and the fruit longitudinal diameter fitting curve (FIG. 4), the T1, T2 and T3 fitting curve trends were basically similar, the fruit weight and longitudinal diameter increased with the increase of time, and from the growth rate, the three groups showed a downward trend.

[0071] Table 5 Fruit growth model parameters and test indexes under different pulling branch angles

[0072] 2.5 Comparison of mature fruit quality characteristics under different pulling branch angles

[0073] The fruit quality and the length and diameter of the fruit can directly reflect the size of the fruit. The relationship between the different pulling angles and the fruit quality of 'CuiGuan' pear was compared, including the fruit weight, fruit shape index, length, diameter, soluble solids, titratable acid, sugar-acid ratio and fruit firmness. The results showed that the fruit weight, fruit shape index, length, diameter and soluble solids had no significant difference among the three pulling angles (p>0.05). The titratable acid content of T1 group was significantly higher than that of T2 and T3 groups (p<0.05). The sugar-acid ratio of T2 group had no significant difference with that of T1 and T3 groups, but the sugar-acid ratio of T3 group was significantly higher than that of T1 group (p<0.05). The fruit firmness of T2 and T3 groups was significantly lower than that of T1 group (p<0.05). The comprehensive quality of 'CuiGuan' fruit in T3 group was better than that in T1 and T2 groups.

[0074] The tree structure is the key of orchard management and production, and the branch pulling is an important method to change the tree structure, which plays an important role in improving the light reception, inhibiting the vegetative growth, inducing the flower bud germination and promoting the accumulation of secondary metabolites. The relationship between the growth index of plant branches or fruit and the development time was analyzed by using the Logistic equation and the polynomial regression method, which is an effective method to evaluate the tree growth, fruit yield and quality. In this study, the curve fitting equation and the derivative function constructed by the length and diameter of the branch could accurately reflect the growth dynamics of the branch, which provided a method to quantitatively evaluate the growth potential of the branch of the pear tree under the shed frame. Meanwhile, the relationship between the branch growth rate and the fruit quality formation was preliminarily determined by comparing the effects of three pulling angles on the fruit quality formation.

[0075] In the early stage of the branch growth and fruit growth of 'CuiGuan' pear, the growth rhythm and trend of the branch were basically consistent with those of the fruit. The length of the branch grew rapidly from the middle of April to the middle and late of May, and the length growth of the branch accounted for more than 90% of the annual length growth of the branch (Fig. 3). After entering June, the branch growth of each treatment group was slow, and the length and diameter growth of the branch appeared a temporary period. The diameter growth was relatively insignificant, but it maintained a relatively long period of time, which might be due to the shift of the nutrient allocation center from vegetative growth to reproductive growth. This situation was more typical in T3 group (0°). It indicated that the fruit growth of 'CuiGuan' pear depended on the leaf growth of the new shoots to produce more nutrients, and this trend was more obvious under the management condition of inhibiting the vegetative growth by pulling the branch downward.

[0076] All three branch length treatments exhibited an "S" curve growth pattern, while the trend in branch thickness was gentler in groups T1 and T2, and a very typical "S" shape in group T3. The results demonstrate that different branch angles affect the biomass of new shoots, with a much greater impact on the rate of branch thickness growth than on length. In terms of length development, group T3 entered the rapid growth phase earliest, 2-3 days earlier than group T1; while in terms of thickness development, group T3 entered the rapid growth phase latest, also about 2-3 days later than group T1. Furthermore, Table 2 shows that the onset time of rapid length growth becomes increasingly earlier as the branch angle decreases. In terms of thickness growth characteristics, the maximum relative growth rate v... m The inflection point occurred nearly a week earlier in group T3 than in group T1, and the former's maximum relative growth rate v m The growth rate was 2.02 times faster than the latter, with an overall trend of T3 > T2 > T1, but this trend was not obvious in length growth (Table 2). Regarding fruit quality, testing of fully mature *Cuiguan* fruits revealed that although there was no significant difference in soluble sugar content among the three treatments, the titratable acid content of group T1 (0.21% ± 0.07%) was significantly higher than that of groups T2 (0.19% ± 0.04%) and T3 (0.18% ± 0.04%), with the sugar-acid ratio showing a trend of T3 > T2 > T1. Correspondingly, the average growth rate of the branch cross-sectional area in the later stages of growth was T3 (11.69 mm). 2 / d)>T2(10.54mm 2 / d)>T1(9.47mm 2 This further suggests that, under the branch-pulling conditions of group T3, the branches entered the rapid growth phase earlier, had a higher maximum relative growth rate in thickness (cross-section), and stopped growing relatively earlier (72.16 days). This facilitated the rapid output of carbon from the "source" (leaves) to the "sink" (fruit), causing organic acids (malic acid, citric acid, etc.) in the fruit pulp cells to complete the conversion and accumulation of sugar compounds earlier, thus significantly increasing the sugar-acid ratio (Figure 9). At the same time, it also promoted the accelerated transport of important mineral elements such as calcium, resulting in relatively lower fruit pulp firmness. This may suggest that branch-pulling may mainly regulate the growth and development of pear fruiting branches by changing the radial transport of nutrients (the direction of the branch cross-section diameter) rather than the axial (the direction perpendicular to the branch cross-section), thereby affecting the synthesis and transport of secondary metabolites in the fruit pulp.

[0077] Although the above embodiments have provided a detailed description of this application, they are only some embodiments of this application, not all embodiments. Other embodiments can be obtained based on these embodiments without creative intent, and these embodiments all fall within the protection scope of this application.

Claims

1. A method for evaluating the pulling of branches of a pear tree based on a growth model, characterized in that: The method comprises the following steps: Step one, selecting the double-arm forward mode of the arbor cultivation mode, selecting the appropriate branches to pull the branches at different test group angles, and fixing the pulled branches on the shelf; Step two, new sprout trait determination: the initial sprouting day of the branch is defined as the initial growth day 0, marked as D0, and the length and thickness of the newly sprouted branch are measured and recorded every certain period of time; Step three, fruit quality index determination: the fruits are picked according to the test groups, and the fruit quality indexes are measured; Step four, data processing and growth model construction: draw the growth process Logistic regression graph of the length and thickness of the newly sprouted branches, with date as x, the length or thickness of the newly sprouted branches as y, and the characteristic value of the growth of the newly sprouted branches calculated according to equations (1) to (6): In the formula: y is the length or thickness of newly germinated shoots; t is the growth time of newly germinated shoots; k is the theoretical maximum value of the growth length of newly germinated shoots; a, b are parameters; t1 is the starting time of rapid growth of newly germinated shoots; t2 is the ending time of rapid growth of newly germinated shoots; v m is the maximum relative growth rate; t m is the time of occurrence of the maximum relative growth; t1 and t2 are the two points with the fastest daily change rate, that is, the demarcation points from germination to rapid growth and into slow growth, and t2-t1 is the growth peak period. A scatter plot of the fruit quality indexes is drawn, single factor analysis is performed on the scatter plot of the fruit quality indexes, Pearson method is used for correlation analysis, LSD test is used to evaluate the difference between the average values, P<0.05, the full bloom period is defined as the fruit development growth day 0, the number of days after the full bloom period is x, and the fruit quality indexes are 'y', the growth rate equation of the fruit quality indexes is obtained by online derivation, the inflection point prediction adopts -b / 2a, the inflection point prediction is suitable for the quadratic term equation, the second derivative f''(x)=0 is suitable for the cubic term equation; Step five, new sprout length and thickness growth model construction under different branch pulling angles: the new sprout length and thickness growth data under different branch pulling conditions are fitted using equation (1) to obtain the fitting curve; Step six, the division of the growth stages of new sprouting branches under different pulling angles: using equations (3) (4) (5) (6) to calculate the growth rate inflection point and other phenological parameters of new sprouting branches, and dividing the growth of the length and thickness of new sprouting branches into three growth stages: the initial growth stage (0, t1), the rapid growth stage (t1, t2), and the late growth stage (t2, t n ) Step seven, evaluation of the change of the growth rate of the new sprout length and thickness under different branch pulling angles: it is determined whether there is a significant difference between different test groups at each growth stage; Step eight, fruit growth mathematical equation model construction under different branch pulling angles: the fruit quality related indexes and the number of days after the full bloom period are fitted using the one-dimensional quadratic equation and the one-dimensional cubic equation; Step nine, comparison of the mature fruit quality characteristics under different branch pulling angles: whether there is a significant difference between different test groups of each mature fruit index is compared.

2. The method according to claim 1, wherein the method is characterized by: In step one, the branch selection method is as follows: at the position of 1.0-2.0 m away from the center trunk of each tree, 1-year-old branches with the same orientation, similar thickness and length and natural growth angle are selected for branch pulling at different angles, and the different angles are 60°, 30° and 0°.

3. The method according to claim 1, wherein the method is characterized by: In step two, the certain period of time is 6-10 days, the length is measured by a fixed ruler, the thickness is calculated according to the area formula by the diameter, and the diameter is measured by an electronic vernier caliper.

4. The method according to claim 1, wherein the method is characterized by: In step three, the fruits are Cui Guan fruits without obvious mechanical damage and pests and diseases, the fruit quality indexes include fruit weight, fruit shape index, fruit hardness, soluble solid content and titratable acid content; the fruit weight is obtained by electronic balance weighing, the fruit shape index is calculated by the formula: fruit shape index = maximum longitudinal diameter / maximum transverse diameter, the longitudinal and transverse diameters of the fruit are measured by a vernier caliper; the fruit hardness is the hardness of the peeled fruit pulp at the maximum transverse position of the fruit, the fruit hardness is measured by a fruit hardness meter, 3 times are measured for each group, and the average value is taken; the soluble solid content is measured by a sugar tester; the titratable acid content is measured by an acidimeter, each sample is measured 3 times, and the average value is taken.

5. The method according to claim 1, wherein the method is characterized by: In step four, the value of k is determined according to the three-point rule, taking the observation values (t a ,y a ), (t b ,y b ) and (t c ,y c ) equidistant in time, such that:

6. The method according to claim 1 or 5, wherein the method is characterized by: In step four, the growing stage is the fast growing duration, the fast growing duration T, T = t2-t1, the time of the early growing stage is the time of the fast growing stage is the time of the late growing stage is According to the k value and the y value, a series of y' values corresponding to different time points are obtained, then a straight line regression equation is fitted with time as the horizontal coordinate and y' as the vertical coordinate, and a determination coefficient R 2 value is obtained.

7. The method according to claim 1, wherein the method is characterized by: In step eight, the five growth indexes of the fruit growth process in each test group, including the horizontal diameter, soluble solids content, hardness, weight and longitudinal diameter, are analyzed, the soluble solids content index, weight index and longitudinal diameter index are fitted by using a quadratic equation, and the horizontal diameter index and hardness index are fitted by using a cubic equation to construct the corresponding fitting models.

8. The method according to claim 1 or 7, wherein the method is for evaluating the growth of a pear tree based on a growth model. In step eight, curves are drawn according to the time points of 78d, 87d, 100d, 112d, 119d and 127d after the flowering stage.

9. A growth model used in a method for evaluating branch training of pear trees under a pergola, characterized in that, The growth model is a growth model of newly germinated shoots of double-arm forward pear trees after the branches are pulled in a shed cultivation mode, and the growth model comprises an equation of characteristic values of the growth of the newly germinated shoots. The characteristic value of the new sprout shoot growth is calculated according to equations (1)-(6): In the formula: y is the length or thickness of newly germinated shoots; t is the growth time of newly germinated shoots; k is the theoretical maximum value of the growth length of newly germinated shoots; a, b are parameters; t1 is the starting time of rapid growth of newly germinated shoots; t2 is the ending time of rapid growth of newly germinated shoots; v m is the maximum relative growth rate; t m is the time of occurrence of the maximum relative growth; t1 and t2 are the two points with the fastest daily change rate, that is, the demarcation points from germination to rapid growth and into slow growth, and t2-t1 is the growth peak period.

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