CN102592201A - Method for summarizing rice regional test information rapidly - Google Patents
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Abstract
The invention discloses a method for summarizing rice regional test information rapidly. The method comprises the steps of: (1) collecting and managing element data from each test point according to a standard element data table format and recording the element data in corresponding element data tables; (2) respectively copying and sticking the data in each element data table into an Excel electronic table; (3) setting an Excel electronic table template group to automatically generate data needed by the summarization of the regional tests; (4) calculating a comparative value between the growth period of each variety and the growth period of a check variety; (5) calculating a comparative value between the yield of each variety and the yield of the check variety; (6) calculating a comparative value between the daily output of each variety and the daily output of the check variety; (7) performing an analysis of variance; and (8) generating a table and carrying out a summarization. The method for summarizing the rice regional test information rapidly, disclosed by the invention, solves the current situation that the traditional method has a great calculation workload, is easy to make mistakes and the like, can be popularized to the summarization of regional test information of other crops, and has the advantages of having wide application prospect, being simple and easy, shorting calculation time, improving accuracy and the like.
Description
Technical field
The present invention relates to the Computer-aided Design Technology field; Be particularly related to present situations such as a kind of change classic method amount of calculation is big, process is loaded down with trivial details, be prone to make mistakes, the method that a kind of paddy rice zone testing data during the regional testing data that extends to other crop gathers gathers fast.
Background technology
The crops regional testing be before the crop varieties authorization must be through program, its fundamental purpose is the principal character characteristic of objective qualification new varieties, for the new varieties authorization provides foundation and data target, and confirms optimum promoting region for improved seeds.Annual each testing site is reported to test findings to form gathers getting much time of summary; The staff need draw data at short notice; And the task of crops regional testing is heavy, workload is big, data are many, amount of calculation is big; Aggregation process is very loaded down with trivial details, causes the staff usually to work extra shifts or extra hours because of in a hurry.
The concrete following technological deficiency of existing crops regional testing:
(1) be collection with crops regional testing result with each testing site at present after, point then carries out weighted mean with the same proterties of same kind in a some ground.With rice in Sichuan province hybrid rice regional testing is example, and 13～15 test group are arranged every year, 10 of the testing sites of each group, and 14 of every group tested varieties, the proterties that each test is put down in writing has 25.Carry out weighted average calculation so one by one.Its method length consuming time, workload are big, and process is very loaded down with trivial details.Especially yield data must carry out the arrangement again and the conversion of data layout in order to carry out the variance analysis of crop regional testing, needs to re-enter by manual work, and process is very loaded down with trivial details;
(2) because the work that the crops regional testing gathers is that minority entity and individual are in operation for a long time; Do not cause enough attention, cause this computing method effectively not improved, therefore; Traditional method amount of calculation is big; And very loaded down with trivial details, in actual mechanical process because of getting much time, appearance situation such as repeat to do over again because of makeing mistakes usually.
Summary of the invention
The object of the invention promptly is to overcome the deficiency of prior art; A kind of paddy rice zone method that testing data gathers fast is provided, has saved many heavy operation links, changed present situations such as the classic method amount of calculation is big, process is very loaded down with trivial details, be prone to make mistakes; It is a significant improvement of paddy rice zone testing data method of summary; During the regional testing data that can be generalized to other crop gathers, have broad application prospects, have simple; Shorten computing time, improved advantages such as accuracy.
The objective of the invention is to realize through following technical scheme: the method that a kind of paddy rice zone testing data gathers fast, adopt pre-designed standardized meta data form and template, to calculate fast and gather paddy rice zone test figure, it may further comprise the steps:
(1) collects from each testing site and the arrangement metadata according to the standardized meta data table format; And be entered in the metadata corresponding form; Collect from each testing site and put at least one group metadata form in order, described metadata form comprises field investigation table, species test and yield result table at least;
(2) data in each metadata form are duplicated respectively paste in the excel spreadsheet lattice; Data in the field investigation table that is about to collect from each testing site wait successively to duplicate with gap by the testing site numbering and paste in the excel spreadsheet lattice worksheet 1, and the species test that will collect from each testing site and the data in the yield result table are by duplicating the correspondence position that pastes the excel spreadsheet lattice worksheet 2 with the same method of field investigation epiphase;
(3) excel spreadsheet grid template collection being set generates district examination automatically and gathers desired data; Other Main Agronomic Characters mean value, each kind that automatic each kind of generation template generation promptly is set in worksheet 1 show in the resistance field of each testing site; Described economical character comprise basic seedling (ten thousand/mu), Gao Miao (ten thousand/mu), effectively fringe (ten thousand/mu), the percentage of earbearing tiller (%), plant height (cm), breeding time (day), described each kind shows in the resistance field of each testing site and comprises banded sclerotial blight, leaf blast, panicle blast, bacterial leaf-blight, false smut, lodging property;
Output and yield component mean value that automatic generation template generates each kind, each kind vertical array data form at each cell production of each testing site is set in worksheet 2, and described output and yield component comprise average yield per mu (kilogram), spike length (cm), total grain number (grain)/fringe, number (grain)/fringe, setting percentage (%), mass of 1000 kernel (g), day output (kg), minimum output (kg), production peak (kg) and each kind be in each testing site output and increase and decrease situation in fact;
(4) in worksheet 1 through " each kind breeding time-check variety breeding time ", calculate the fiducial value of each kind breeding time and check variety;
(5) in worksheet 2, pass through " (each kind per mu yield-check variety per mu yield)/check variety per mu yield * 100 ", calculate the fiducial value of each variety yield and check variety;
(6) in worksheet 2, pass through " (each kind day output-check variety day output)/check variety day output * 100 ", calculate the fiducial value of each kind day output and check variety;
(7) each kind is duplicated at vertical array data form of each cell production of each testing site paste in " district's examination 99 " or " DPS " system, carry out variance analysis;
(8) generation form and entering gather summary.
Data and the data in the worksheet 2 in the worksheet 1 described in the present invention are interchangeable; Be that worksheet 1, worksheet 2 can be respectively any one in field investigation table, species test and the yield result table; When worksheet 1 is the field investigation table; Worksheet 2 is species test and yield result table, and when worksheet 1 was species test and yield result table, worksheet 2 was the field investigation table.
The invention has the beneficial effects as follows: the present invention provides a kind of paddy rice zone method that testing data gathers fast, has saved many heavy operation links, has changed present situations such as the classic method amount of calculation is big, process is very loaded down with trivial details, be prone to make mistakes; It is a significant improvement of paddy rice zone testing data method of summary; During the regional testing data that can be generalized to other crop gathers, have broad application prospects, have simple; Shorten computing time, improved advantages such as accuracy.
Description of drawings
Fig. 1 is a process flow diagram of the present invention.
Embodiment
Below in conjunction with accompanying drawing and form the present invention is done further description, but protection scope of the present invention is not limited to the following stated, institute's column data is merely used for example in each form of the present invention, and the data in the form are not limited to the following stated.
Method as shown in Figure 1, that a kind of paddy rice zone testing data gathers fast adopts pre-designed standardized meta data form and template, calculates fast and gathers paddy rice zone test figure, and it may further comprise the steps:
(1) collects from each testing site and the arrangement metadata according to the standardized meta data table format; And be entered in the metadata corresponding form; Collect from each testing site and put at least one group metadata form in order, described metadata form comprises field investigation table, species test and yield result table at least;
(2) data in each metadata form are duplicated respectively paste in the excel spreadsheet lattice; Data in the field investigation table that is about to collect from each testing site wait successively to duplicate with gap by the testing site numbering and paste in the excel spreadsheet lattice worksheet 1; The species test that to collect from each testing site and the data in the yield result table are by duplicating the correspondence position that pastes the excel spreadsheet lattice worksheet 2 with field investigation epiphase method together; This leading case is that to participate in the experiment with 10 a little be example; Be less than 10 if actual test is counted, then fill out neat data field with the space form;
(3) excel spreadsheet grid template collection is set and generates district examination automatically and gather desired data, Other Main Agronomic Characters mean value that automatic generation template generates each kind, each kind promptly are set in worksheet 1 in the performance of the resistance field of each testing site; Described economical character comprise basic seedling (ten thousand/mu), Gao Miao (ten thousand/mu), effectively fringe (ten thousand/mu), the percentage of earbearing tiller (%), plant height (cm), breeding time (day), described each kind shows in the resistance field of each testing site and comprises banded sclerotial blight, leaf blast, panicle blast, bacterial leaf-blight, false smut, lodging property;
Output and yield component mean value that automatic generation template generates each kind, each kind vertical array data form at each cell production of each testing site is set in worksheet 2, and described output and yield component comprise average yield per mu (kilogram), spike length (cm), total grain number (grain)/fringe, number (grain)/fringe, setting percentage (%), mass of 1000 kernel (g), day output (kg), minimum output (kg), production peak (kg) and each kind be in each testing site output and increase and decrease situation in fact;
(4) in worksheet 1 through " each kind breeding time-check variety breeding time ", calculate the fiducial value of each kind breeding time and check variety;
(5) in worksheet 2, pass through " (each kind per mu yield-check variety per mu yield)/check variety per mu yield * 100 ", calculate the fiducial value of each variety yield and check variety;
(6) in worksheet 2, pass through " (each kind day output-check variety day output)/check variety day output * 100 ", calculate the fiducial value of each kind day output and check variety;
(7) each kind is duplicated at vertical array data form of each cell production of each testing site paste in " district's examination 99 " or " DPS " system, carry out variance analysis;
(8) generation form and entering gather summary.
Be exemplified below: with rice in Sichuan province hybrid rice regional testing is example, and the code test point of every group of test is 10 (L1～L10), 14 of tested varieties.All tests that is less than this parameter all are fit to the method and calculate; As surpassing the test of this parameter, do suitable adjustment, still available this method.
The main contents of present embodiment realized by following each step:
(1) data acquisition of each testing site and record standard must be filled in by the form of the basic demand of rice in Sichuan province regional testing design; Shown in following table 1, table 2; Wherein, table 1 is the field investigation table, and table 2 is species test and yield result table; Gather the data of 10 testing sites in the present embodiment, the data of these 10 testing sites are all carried out typing by the form shown in table 1, the table 2;
Table 1 field investigation table
Table 2 species test and yield result table
The data of the table 1 that (2) will collect from each testing site are duplicated the fixed position that pastes the excel spreadsheet lattice Sheetl, and the data that are about to L1～L10 (representing pilot 1～10 respectively) in the table 1 paste the assigned address of A2, A22, A42, A62, A82, A102, A122, A142, A162, A182 among the form Sheet1 respectively;
The data of the table 2 that will collect from each testing site are duplicated the fixed position that pastes the excel spreadsheet lattice Sheet2, and the data that are about to L1～L10 (representing pilot 1～10 respectively) in the table 2 paste the assigned address of A2, A22, A42, A62, A82, A102, A122, A142, A162, A182 among the form Sheet2 respectively;
(3) excel spreadsheet grid template collection being set generates regional testing automatically and gathers desired data; Other Main Agronomic Characters mean value that automatic generation template generates each kind automatically, each kind are set in the performance of the resistance field of each testing site among the excel spreadsheet lattice Sheet1 that wherein, the field investigation table metadata is corresponding;
As shown in table 3; Described economical character comprise at least basic seedling (ten thousand/mu), Gao Miao (ten thousand/mu), effectively fringe (ten thousand/mu), the percentage of earbearing tiller (%), plant height (cm), breeding time (day) and with the fiducial value of check variety in any one or any several kinds combination, below each ck in showing represent check variety;
Each kind economical character table of table 3
Shown in table 4～9, described resistance field performance comprises any one or any several kinds combination in banded sclerotial blight, leaf blast, panicle blast, bacterial leaf-blight, false smut, the lodging property at least;
Each kind of table 4 is in the performance of the field of the each point banded sclerotial blight of participating in the experiment
Each kind of table 5 is in the performance of the field of the each point leaf blast of participating in the experiment
Each kind of table 6 is in the performance of the field of the each point panicle blast of participating in the experiment
Each kind of table 7 is in the performance of the field of the each point bacterial leaf-blight of participating in the experiment
Each kind of table 8 is in the performance of the field of the each point false smut of participating in the experiment
Each kind of table 9 is in the field performance of each point lodging property of participating in the experiment
Shown in table 10, table 11, table 12; Output and yield component mean value that automatic generation template generates each kind automatically, each kind vertical array data form at each cell production of each testing site is set among the corresponding excel spreadsheet lattice Sheet2 of species test and yield result table metadata, and the output of described each kind and yield component comprise average yield per mu (kilogram), spike length (cm), total grain number (grain)/fringe, number (grain)/fringe, setting percentage (%), mass of 1000 kernel (g), day output (kg), minimum output (kg), production peak (kg) and each kind any one or any several kinds combination in each testing site output and increase and decrease situation in fact at least; The vertical permutation table of cell production is as shown in table 12; Wherein, Table 12 is made up of this six sub-table of table 12-1～table 12-6 order successively; In form Sheet2, will generate the vertical array data form of each kind, be the data among the S2～S211 and T2～T211 among the form Sheet2 at each cell production of each testing site;
Table 10 output and yield component table
Table 11 each point output and output increase and decrease information slip
Table 12-1
Table 12-2
Table 12-3
Table 12-4
Table 12-5
Table 12-6
(4) after the automatic generation regional testing of accomplishing the above table template set gathers required data; Formula in the I202 of form Sheet1 should be imported " numerical value of=H202-H215 "; Automatically fill from I203 to I215 with mouse drag then, promptly obtain the fiducial value of each kind breeding time and check variety;
(5) formula in the I202 of form Sheet2 should be imported " the numerical value * 100 of numerical value/H215 of=H202-H215 ", fills from I203 to I215 automatically with mouse drag then, promptly obtains the fiducial value of each variety yield and check variety;
(6) formula in the L202 of form Sheet2 should be imported " the numerical value * 100 of numerical value/K215 of=K202-K215 ", fills from L203 to L215 automatically with mouse drag then, promptly obtains the fiducial value of each kind day output and check variety;
(7) each kind that generates among the form Sheet2 is S2～S211 and the interior data of T2～T211 among the form Sheet2 at vertical array data form of each cell production of each testing site, and wherein data are respectively in these five testing sites of L1～L5 in S2～S211; Being arranged in order of data in the cell production I of each kind, II, III promptly obtains through following formula respectively: " S2=I5 ", " S3=J5 "; " S4=K5 ", " S5=I6 " ..., " S209=I98 "; " S210=J98 ", the data in " S211=K98 ", T2～T211 are respectively in these five testing sites of L6～L10; Being arranged in order of data in the cell production I of each kind, II, III promptly obtains through following formula respectively: " T2=I105 ", " T3=J105 "; " T4=K105 ", " T5=I106 " ..., " T209=I198 "; " T210=J198 "; " T211=K198 " duplicates each kind among the Sheet2 and to paste in " district's examination 99 " or " DPS " system at vertical array data form of each cell production of each testing site, can carry out variance analysis;
(8) generation form and entering gather summary.
Claims (1)
1. the method that paddy rice zone testing data gathers fast adopts pre-designed standardized meta data form and template, calculates fast and gathers paddy rice zone test figure, and it is characterized in that: it may further comprise the steps:
(1) collects from each testing site and the arrangement metadata according to the standardized meta data table format; And be entered in the metadata corresponding form; Collect from each testing site and put at least one group metadata form in order, described metadata form comprises field investigation table, species test and yield result table at least;
(2) data in each metadata form are duplicated respectively paste in the excel spreadsheet lattice; Data in the field investigation table that is about to collect from each testing site wait successively to duplicate with gap by the testing site numbering and paste in the excel spreadsheet lattice worksheet 1, and the species test that will collect from each testing site and the data in the yield result table are by duplicating the correspondence position that pastes the excel spreadsheet lattice worksheet 2 with the same method of field investigation epiphase;
(3) excel spreadsheet grid template collection being set generates district examination automatically and gathers desired data; Other Main Agronomic Characters mean value, each kind that automatic each kind of generation template generation promptly is set in worksheet 1 show in the resistance field of each testing site; Described economical character comprises basic seedling (ten thousand/mu), Gao Miao (ten thousand/mu), effectively fringe (ten thousand/mu), the percentage of earbearing tiller (%), plant height ㎝), breeding time (day), described each kind shows in the resistance field of each testing site and comprises banded sclerotial blight, leaf blast, panicle blast, bacterial leaf-blight, false smut, lodging property;
Output and yield component mean value that automatic generation template generates each kind, each kind vertical array data form at each cell production of each testing site is set in worksheet 2, and described output and yield component comprise average yield per mu (kilogram), spike length "-f " flag ㎝), total grain number (grain)/fringe, number (grain)/fringe, setting percentage (%), mass of 1000 kernel (g), day output 1-amino-2-naphthol-4-sulfonic acid ㎏ in fact), minimum output 1-amino-2-naphthol-4-sulfonic acid ㎏), production peak 1-amino-2-naphthol-4-sulfonic acid ㎏) and each kind in each testing site output and increase and decrease situation;
(4) in worksheet 1 through " each kind breeding time-check variety breeding time ", calculate the fiducial value of each kind breeding time and check variety;
(5) in worksheet 2, pass through " (each kind per mu yield-check variety per mu yield)/check variety per mu yield * 100 ", calculate the fiducial value of each variety yield and check variety;
(6) in worksheet 2, pass through " (each kind day output-check variety day output)/check variety day output * 100 ", calculate the fiducial value of each kind day output and check variety;
(7) each kind is duplicated at vertical array data form of each cell production of each testing site paste in " district's examination 99 " or " DPS " system, carry out variance analysis;
(8) generation form and entering gather summary.
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Cited By (7)
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| CN104463687A (en) * | 2014-11-14 | 2015-03-25 | 浙江省农业科学院 | New method for selecting crop seeds |
| CN105093092A (en) * | 2015-07-09 | 2015-11-25 | 无锡中微腾芯电子有限公司 | Excel adopted method to realize the Summary standardization in wafer test |
| CN105812373A (en) * | 2016-03-29 | 2016-07-27 | 北京派得伟业科技发展有限公司 | Crop variety regional trial data collection and management method |
| CN105872037A (en) * | 2016-03-29 | 2016-08-17 | 北京派得伟业科技发展有限公司 | Crop variety regional test data processing method |
| CN106952154A (en) * | 2017-03-30 | 2017-07-14 | 国网河南禹州市供电公司 | A kind of automatic accreditation method |
| CN111460777A (en) * | 2020-03-12 | 2020-07-28 | 中国农业科学院蔬菜花卉研究所 | Plant variety DUS test method |
| CN111524022A (en) * | 2020-03-12 | 2020-08-11 | 中国农业科学院蔬菜花卉研究所 | Plant variety DUS test method |
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| CN104463687A (en) * | 2014-11-14 | 2015-03-25 | 浙江省农业科学院 | New method for selecting crop seeds |
| CN105093092A (en) * | 2015-07-09 | 2015-11-25 | 无锡中微腾芯电子有限公司 | Excel adopted method to realize the Summary standardization in wafer test |
| CN105093092B (en) * | 2015-07-09 | 2018-01-05 | 无锡中微腾芯电子有限公司 | The method that wafer sort Summary standardization is realized using Excel |
| CN105812373A (en) * | 2016-03-29 | 2016-07-27 | 北京派得伟业科技发展有限公司 | Crop variety regional trial data collection and management method |
| CN105872037A (en) * | 2016-03-29 | 2016-08-17 | 北京派得伟业科技发展有限公司 | Crop variety regional test data processing method |
| CN105872037B (en) * | 2016-03-29 | 2019-03-15 | 北京派得伟业科技发展有限公司 | A kind of Regional Tests of Crop Varieties data processing method |
| CN106952154A (en) * | 2017-03-30 | 2017-07-14 | 国网河南禹州市供电公司 | A kind of automatic accreditation method |
| CN111460777A (en) * | 2020-03-12 | 2020-07-28 | 中国农业科学院蔬菜花卉研究所 | Plant variety DUS test method |
| CN111524022A (en) * | 2020-03-12 | 2020-08-11 | 中国农业科学院蔬菜花卉研究所 | Plant variety DUS test method |
| CN111524022B (en) * | 2020-03-12 | 2023-04-25 | 中国农业科学院蔬菜花卉研究所 | Plant variety DUS testing method |
| CN111460777B (en) * | 2020-03-12 | 2023-11-14 | 中国农业科学院蔬菜花卉研究所 | Plant variety DUS testing method |
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