CN-122023052-A - Planting method and system based on agricultural planting environment data acquisition

CN122023052ACN 122023052 ACN122023052 ACN 122023052ACN-122023052-A

Abstract

The invention provides a planting method and a system based on agricultural planting environment data acquisition, and relates to the technical field of agricultural data analysis, wherein the method comprises the steps of firstly dividing three growth stages of crops, designing growth indexes, presetting candidate microelements and candidate beneficial bacteria, and setting three areas with equal areas in test soil; screening target microelements and determining comparison data and reference indexes through a first area experiment, carrying out a concentration gradient experiment on the target microelements to correct and determine an optimal configuration concentration interval, carrying out an absolute abundance gradient experiment on candidate beneficial strains in a third area to define target beneficial strains, determine an optimal absolute abundance interval and beneficial strains to be observed, correcting the beneficial strains to be observed through a plurality of groups of verification experiments based on a forward response rule and a response experiment duty ratio, and finally determining the target microelements and the target beneficial strains as core data acquisition categories.

Inventors

XIE MIN
Mi Jiawen
CHEN TIANQI
CAO FUZHONG
LIU XUEPING
FAN LI
Ji Minjia
ZHANG PENG
YUE SHOUCHENG
CUI YING
PANG YAJUAN

Assignees

内蒙古农业大学

Dates

Publication Date: 20260512
Application Date: 20260126

Claims (10)

1. The planting method based on the agricultural planting environment data acquisition is characterized by comprising the following specific steps of: Dividing crops into three growth stages, designing growth indexes, presetting candidate microelements and candidate beneficial strains, setting first, second and third areas with equal areas in test soil, taking the candidate beneficial strains existing in the first area without crops as the existing beneficial strains, and taking the concentration variation of the candidate microelements as comparison data; during the first area crop planting period, acquiring the concentration variation of the candidate microelements and the absolute abundance of the candidate beneficial strains in each growth stage, synchronously acquiring the growth indexes as reference indexes, and comparing the concentration variation of the candidate microelements with comparison data in three growth stages to screen target microelements; Designing a concentration gradient experiment aiming at the target trace element in a second area, comparing the growth index under each gradient with a reference index, correcting the target trace element according to whether the growth index meets a forward response rule, and determining an optimal configuration concentration interval of the target trace element; Designing absolute abundance gradient experiments aiming at candidate beneficial strains in the soil of a third area, comparing growth indexes under each gradient with reference indexes, defining the candidate beneficial strains with growth indexes meeting forward response rules as target beneficial strains, determining an optimal absolute abundance interval of the candidate beneficial strains, and listing the existing beneficial strains with growth indexes not meeting the forward response rules as beneficial strains to be observed; Setting a plurality of groups of experiments of target trace elements in an optimal configuration concentration interval and target beneficial bacteria in an optimal absolute abundance interval, aiming at each beneficial bacteria to be observed, taking the experiment with the highest absolute abundance as a reference experiment, taking the growth index of the reference experiment as a benchmark, taking the experiment meeting the forward response rule as a response experiment, analyzing and correcting the target beneficial bacteria based on the proportion of the response experiment to all experiment groups, and taking the target trace elements and the target beneficial bacteria as target acquisition contents of a planting environment.
2. The planting method based on agricultural planting environment data acquisition according to claim 1, wherein the method for dividing crops into three growth stages and designing growth indexes is as follows: the first growing stage takes crop sowing as a stage starting judgment standard and takes at least 3 crop leaves as a stage ending judgment standard; the second growth stage takes the end of the first growth stage as a stage start judgment standard and takes the crop before bud emergence as a stage end judgment standard; A third growth stage, namely taking the end of the second growth stage as a stage start judgment standard and crop harvesting as a stage end judgment standard; The growth indexes comprise the survival rate of crops at the end of a first growth stage, the duration of a second growth stage and the quality index of the crops at the end of a third growth stage, wherein the quality index is a quantitative result of scoring by adopting an expert scoring method, the scoring value is positively correlated with the quality of the crops, and the larger the value is, the better the quality is represented.
3. The planting method based on the agricultural planting environment data acquisition according to claim 2, wherein the method for taking the concentration variation of the candidate microelements as comparison data is as follows: Setting a first time interval duration which does not exceed the duration of any one of the three growth stages and which is an integral multiple of the first time interval duration, dividing the first area crop-free period into a plurality of subintervals with the length being the first time interval duration at equal intervals, calculating the difference value of candidate trace element concentrations at the starting time and the ending time of each subinterval, and taking the average value as comparison data.
4. The planting method based on agricultural planting environment data acquisition of claim 3, wherein the method for screening target microelements by comparing the concentration variation of candidate microelements in three growth stages with comparison data is as follows: For each growth stage, pushing the starting time backwards for a first time interval time length to determine the ending time, and taking the candidate microelement concentration difference value between the starting time and the ending time as the candidate microelement concentration variation quantity of the corresponding growth stage; For each growth stage, when the difference between the concentration variation of the candidate trace element and the comparison data of the growth stage is larger than a preset variation threshold value, judging that the candidate trace element is utilized by crops in the corresponding growth stage and is used as a target trace element, and if a certain candidate trace element is not detected in the first area, incorporating the candidate trace element into the target trace element.
5. The planting method based on the agricultural planting environment data acquisition, as set forth in claim 1, characterized in that concentration gradient experiments and absolute abundance gradient experiments are designed, each set of concentration gradient experiments is only aimed at one target trace element, and each set of absolute abundance gradient experiments is only aimed at one candidate beneficial strain.
6. The planting method based on agricultural planting environment data acquisition of claim 4, wherein the method for correcting the target trace elements and determining the optimal configuration concentration interval of the target trace elements according to whether the forward response rule is satisfied is as follows: Setting a forward response rule, namely respectively calculating the deviation percentage of the growth index of each growth stage and the reference index of the corresponding stage, wherein the first growth stage takes the survival rate deviation percentage larger than a preset survival threshold value as a forward response judgment condition, the second growth stage takes the duration deviation percentage smaller than a preset duration threshold value as a forward response judgment condition, the third growth stage takes the quality index deviation percentage larger than a preset quality threshold value as a forward response judgment condition, and the growth index meets the forward response rule under the condition of meeting any forward response judgment condition; And eliminating target trace elements, wherein all gradients of the gradient group do not meet the forward response rule, retaining target trace elements, at least one gradient of which meets the forward response rule, finishing the correction of the target trace elements, extracting all concentration gradients meeting the forward response rule in a concentration gradient experiment of each target trace element, screening the concentration gradient with the maximum forward response degree of the growth index from the concentration gradients, and taking the concentration gradient and the immediately previous concentration gradient as the upper limit and the lower limit of the optimal configuration concentration interval of the target trace elements respectively.
7. The planting method based on agricultural planting environment data acquisition according to claim 6, wherein the method for defining the candidate beneficial bacteria whose growth index meets the forward response rule as the target beneficial bacteria and determining the optimal absolute abundance interval thereof is as follows: Rejecting candidate beneficial strains of which all gradients do not meet the forward response rule, reserving candidate beneficial strains of which at least one gradient meets the forward response rule in the gradient group as target beneficial strains, extracting all absolute abundance gradients meeting the forward response rule in absolute abundance gradient experiments of each target beneficial strain, screening absolute abundance gradients with the maximum forward response degree of growth indexes from the absolute abundance gradients, and taking the absolute abundance gradients and the immediately adjacent upper absolute abundance gradients as the upper limit and the lower limit of the optimal absolute abundance interval of the target beneficial strains respectively.
8. The planting method based on the agricultural planting environment data acquisition according to claim 1, wherein the method for taking the experiment meeting the forward response rule as the response experiment is as follows: taking the growth index of the reference experiment as a guiding index and the growth index of other experiments as a preferable index; Calculating the deviation percentage of the optimal index and the guiding index by taking the guiding index as a reference, wherein the survival rate deviation percentage is larger than a preset survival threshold value in the first growth stage as a forward response judging condition, the duration deviation percentage is smaller than a preset duration threshold value in the second growth stage as a forward response judging condition, the quality index deviation percentage is larger than a preset quality threshold value in the third growth stage as a forward response judging condition, and any forward response judging condition is met, namely, the forward response rule is judged to be met, and an experiment meeting the forward response rule is taken as a response experiment.
9. The planting method based on the agricultural planting environment data acquisition of claim 8, wherein the method for correcting the target beneficial bacteria based on the proportional analysis of the response experiment to the number of all the experiment groups is as follows: extracting absolute abundance of each beneficial strain to be observed under each group of experiments; Extracting absolute abundance gradient values of the beneficial bacteria to be observed in absolute abundance gradient experiments to define a plurality of absolute abundance intervals, determining absolute abundance intervals in which the beneficial bacteria to be observed fall under reference experiments as reference absolute abundance intervals, and determining absolute abundance intervals in which the beneficial bacteria to be observed fall under each response experiment as response absolute abundance intervals; the specific process of presetting the experiment proportion threshold and counting the number of response experiment groups is as follows: And taking the experimental group number of which the response absolute abundance interval is lower than the reference absolute abundance interval as the response experimental group number, calculating the proportion of the response experimental group number to all the experimental group numbers, and taking the beneficial strain to be observed as a target beneficial strain when the proportion is greater than an experimental proportion threshold value.
10. A planting system based on agricultural planting environment data acquisition, characterized in that the system is used for executing the planting method based on agricultural planting environment data acquisition according to any one of claims 1 to 9: The data extraction module is used for dividing crops into three growth stages, designing growth indexes, presetting candidate microelements and candidate beneficial strains, setting first, second and third areas with equal areas in test soil, taking the candidate beneficial strains existing in the period of no crops in the first area as the existing beneficial strains, and taking the concentration variation of the candidate microelements as comparison data; the data screening module is used for acquiring the concentration variation of the candidate microelements and the absolute abundance of the candidate beneficial strains in each growth stage during the crop planting period in the first area, synchronously collecting the growth indexes as reference indexes, and comparing the concentration variation of the candidate microelements with the comparison data in the three growth stages to screen target microelements; The data comparison module is used for designing a concentration gradient experiment aiming at the target trace element in the second area, comparing the growth index under each gradient with the reference index, correcting the target trace element according to whether the growth index meets the forward response rule, and determining the optimal configuration concentration interval of the target trace element; The data analysis module is used for designing absolute abundance gradient experiments aiming at candidate beneficial strains in the soil of the third area, comparing the growth indexes under each gradient with the reference indexes, defining the candidate beneficial strains with the growth indexes meeting the forward response rule as target beneficial strains, determining the optimal absolute abundance interval of the candidate beneficial strains, and listing the existing beneficial strains with the growth indexes not meeting the forward response rule as beneficial strains to be observed; The data correction module is used for setting a plurality of groups of experiments of target trace elements in an optimal configuration concentration interval and target beneficial bacteria in an optimal absolute abundance interval, aiming at each beneficial bacteria to be observed, taking the experiment with the highest absolute abundance as a reference experiment, taking the growth index of the reference experiment as a benchmark, taking the experiment meeting the forward response rule as a response experiment, correcting the target beneficial bacteria based on the proportion analysis of the response experiment accounting for all experiment groups, and taking the target trace elements and the target beneficial bacteria as target acquisition contents of a planting environment.

Description

Planting method and system based on agricultural planting environment data acquisition Technical Field The invention relates to the technical field of agricultural data analysis, in particular to a planting method and a planting system based on agricultural planting environment data acquisition. Background With the increasing sophistication of agricultural production, growers have increasingly recognized that microbial community structure in soil has an important impact on crop growth status, yield formation, and quality performance in addition to conventional nutrient conditions. In the prior art, the soil microbial environment is usually improved by applying organic fertilizers, biofertilizers or inoculating functional bactericides and the like, so as to improve the crop growth performance, for example, in the application of biofertilizers, the prior art can screen adaptive functional flora (such as azotobacter and phosphate-dissolving bacteria) according to the crop major types (such as Gramineae and Leguminosae), prepare special biofertilizers after industrial propagation, directionally strengthen the specific nutrient conversion function in the soil, in the field of functional microbial inoculum inoculation, various application modes such as seed dressing, root irrigation, leaf surface spraying and the like have been developed, and the matched measures such as soil pH value adjustment, temperature and humidity regulation and the like are combined, so that the colonization rate of exogenous functional bacteria is improved, the problem of the unbalance of the soil micro-ecology is rapidly improved, and the special biological fertilizer has positive effects on improving the integral growth vigor of crops in practice, but certain limitations still exist. Different planting bodies have differences on production targets of crops, such as different emphasis on yield, quality, taste or nutrition indexes, meanwhile, the microorganism composition difference under different soil conditions is large, the prior art mostly adopts a general microbial inoculum or an empirical configuration mode, and it is difficult to accurately judge which microorganisms in a specific soil environment have actual promotion effects on the required crop production targets, so that the data acquisition lacks pertinence, and the actual requirements of accurate planting regulation are difficult to meet, therefore, a technical means capable of combining specific growth responses and carrying out pertinence analysis and screening on soil nutrient conditions and microorganism factors is needed. The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art. Disclosure of Invention The invention aims to provide a planting method and a planting system based on agricultural planting environment data acquisition, so as to solve the problems in the background technology. In order to achieve the above purpose, the present invention provides the following technical solutions: the planting method based on the agricultural planting environment data acquisition comprises the following specific steps: Dividing crops into three growth stages, designing growth indexes, presetting candidate microelements and candidate beneficial strains, setting first, second and third areas with equal areas in test soil, taking the candidate beneficial strains existing in the first area without crops as the existing beneficial strains, and taking the concentration variation of the candidate microelements as comparison data; during the first area crop planting period, acquiring the concentration variation of the candidate microelements and the absolute abundance of the candidate beneficial strains in each growth stage, synchronously acquiring the growth indexes as reference indexes, and comparing the concentration variation of the candidate microelements with comparison data in three growth stages to screen target microelements; Designing a concentration gradient experiment aiming at the target trace element in a second area, comparing the growth index under each gradient with a reference index, correcting the target trace element according to whether the growth index meets a forward response rule, and determining an optimal configuration concentration interval of the target trace element; Designing absolute abundance gradient experiments aiming at candidate beneficial strains in the soil of a third area, comparing growth indexes under each gradient with reference indexes, defining the candidate beneficial strains with growth indexes meeting forward response rules as target beneficial strains, determining an optimal absolute abundance interval of the candidate beneficial strains, and listing the existing beneficial strains with growth indexes not meeting the forward