CN102592201B - Method for summarizing rice regional test information rapidly - Google Patents
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- CN102592201B CN102592201B CN201210036865.4A CN201210036865A CN102592201B CN 102592201 B CN102592201 B CN 102592201B CN 201210036865 A CN201210036865 A CN 201210036865A CN 102592201 B CN102592201 B CN 102592201B
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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 Computer-aided Design Technology field, be particularly related to a kind of present situations such as classic method amount of calculation is large, process is loaded down with trivial details, easily make mistakes that change, the method that a kind of paddy rice region testing data during the regional testing data that extends to other crop gathers gathers fast.
Background technology
Crops regional testing be before Cultuvar registration must be through program, its fundamental purpose is the principal character characteristic of objective qualification new varieties, for new varieties authorizations provides foundation and data target, and determines optimum promoting region for improved seeds.Annual each testing site is reported to test findings to form gathers getting much time of summary, staff need to draw data at short notice, and the task of crops regional testing is heavy, workload is large, data are many, amount of calculation is large, aggregation process is very loaded down with trivial details, causes 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 now by after the collection of each testing site by crops regional testing result, a point is then weighted the same proterties of same kind on average on a some ground.Taking rice in Sichuan province Regional Trail on Hybrid Rice as example, there are every year 13～15 test group, 10 of the testing sites of each group, 14 of the tested varieties of every group, the proterties that each test is recorded has 25.Be weighted so one by one average computation.Its method length consuming time, workload are large, and process is very loaded down with trivial details.Especially yield data, in order to carry out the variance analysis of regional trial, must carry out rearranging and changing of data layout, needs by manually re-entering, and process is very loaded down with trivial details;
(2) work gathering due to crops regional testing 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 large, and very loaded down with trivial details, in actual mechanical process, because getting much time, the situation such as usually occur repeating to do over again because makeing mistakes.
Summary of the invention
Object of the present invention is to overcome the deficiencies in the prior art, a kind of paddy rice region method that testing data gathers is fast provided, many heavy operation links are saved, the present situations such as classic method amount of calculation is large, process is very loaded down with trivial details, easily make mistakes are changed, it is a significant improvement of paddy rice region 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 the advantages such as accuracy.
The object of the invention is to be achieved through the following technical solutions: the method that a kind of paddy rice region testing data gathers fast, adopt pre-designed standardized meta data form and template, to calculate and gather paddy rice region test figure fast, it comprises the following steps:
(1) collect and arrange metadata from each testing site according to standardized meta data table format, and be entered in corresponding metadata form, collect and arrange at least one group metadata form from each testing site, described metadata form at least comprises field investigation table, species test and yield result table;
(2) data in each metadata form are copied respectively and pasted in excel spreadsheet lattice, wait to copy with gap successively by testing site numbering by the data in the field investigation table of collecting from each testing site to paste in excel spreadsheet lattice worksheet 1, the data in the species test of collecting from each testing site and yield result table are copied to the correspondence position pasting excel spreadsheet lattice worksheet 2 by the method identical with field investigation table;
(3) excel spreadsheet grid template collection being set automatically generates district examination and gathers desired data, automatic generation template is set in worksheet 1 and generates the Other Main Agronomic Characters mean value of each kind, each kind is in the performance of 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 (cm), breeding time (my god), described each kind comprises banded sclerotial blight in the performance of the resistance field of each testing site, leaf blast, panicle blast, bacterial leaf-blight, false smut, lodging property,
Automatic generation template is set in worksheet 2 and generates the output of each kind and yield component mean value, the each kind longitudinal arrangement data layout at each cell production of each testing site, described output and yield component comprise average yield per mu (kilogram), spike length (cm), total grain number (grain)/fringe, real 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;
(4) in worksheet 1, pass 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 " (per mu yield of each kind per mu yield-check variety)/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 copied at the longitudinal arrangement data layout of each cell production of each testing site and paste in " district's examination 99 " or " DPS " system, carry out variance analysis;
(8) generate form and enter and gather summary.
Data in data and worksheet 2 in 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 yield result table, in the time that worksheet 1 is field investigation table, worksheet 2 is species test and yield result table, in the time that worksheet 1 is species test and yield result table, worksheet 2 is field investigation table.
The invention has the beneficial effects as follows: the invention provides the method that a kind of paddy rice region testing data gathers fast, many heavy operation links are saved, the present situations such as classic method amount of calculation is large, process is very loaded down with trivial details, easily make mistakes are changed, it is a significant improvement of paddy rice region 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 the advantages such as accuracy.
Brief description of the drawings
Fig. 1 is process flow diagram of the present invention.
Embodiment
Below in conjunction with accompanying drawing and form, the present invention will be further described, but protection scope of the present invention is not limited to the following stated, and in the each form of the present invention, institute's column data is only for used for example, and the data in form are not limited to the following stated.
As shown in Figure 1, the method that a kind of paddy rice region testing data gathers fast, adopts pre-designed standardized meta data form and template, calculates and gathers paddy rice region test figure fast, and it comprises the following steps:
(1) collect and arrange metadata from each testing site according to standardized meta data table format, and be entered in corresponding metadata form, collect and arrange at least one group metadata form from each testing site, described metadata form at least comprises field investigation table, species test and yield result table;
(2) data in each metadata form are copied respectively and pasted in excel spreadsheet lattice, wait to copy with gap successively by testing site numbering by the data in the field investigation table of collecting from each testing site and paste in excel spreadsheet lattice worksheet 1, data in the species test of collecting from each testing site and yield result table are copied to the correspondence position pasting excel spreadsheet lattice worksheet 2 by the method identical with field investigation table, this leading case is to participate in the experiment a little as example taking 10, if counting, actual test is less than 10, fill out neat data field with space form,
(3) excel spreadsheet grid template collection is set and automatically generates district examination and gather desired data, the Other Main Agronomic Characters mean value that automatic generation template generates each kind, each kind 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;
Automatic generation template is set in worksheet 2 and generates the output of each kind and yield component mean value, the each kind longitudinal arrangement data layout at each cell production of each testing site, described output and yield component comprise average yield per mu (kilogram), spike length (cm), total grain number (grain)/fringe, real 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;
(4) in worksheet 1, pass 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 " (per mu yield of each kind per mu yield-check variety)/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 copied at the longitudinal arrangement data layout of each cell production of each testing site and paste in " district's examination 99 " or " DPS " system, carry out variance analysis;
(8) generate form and enter and gather summary.
Be exemplified below: taking rice in Sichuan province Regional Trail on Hybrid Rice as example, 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, are all applicable to the method and calculate; As exceed the test of this parameter, and make the appropriate adjustments, still can use this method.
The main contents of the present embodiment realize by following step:
(1) data acquisition of each testing site and Recording criteria must be filled in by the form of the basic demand of rice in Sichuan province regional testing design, as shown in following table 1, table 2, wherein, table 1 is field investigation table, table 2 is species test and yield result table, in the present embodiment, gather the data of 10 testing sites, the data of these 10 testing sites are all carried out typing by the form shown in table 1, table 2;
Table 1 field investigation table
Table 2 species test and yield result table
(2) data Replica of the table 1 collecting from each testing site is pasted to the fixed position excel spreadsheet lattice Sheetl, paste respectively the assigned address of A2, A22, A42, A62, A82, A102, A122, A142, A162, A182 in form Sheet1 by the data of L1～L10 in table 1 (representing respectively pilot 1～10);
The data Replica of the table 2 collecting from each testing site is pasted to the fixed position excel spreadsheet lattice Sheet2, paste respectively the assigned address of A2, A22, A42, A62, A82, A102, A122, A142, A162, A182 in form Sheet2 by the data of L1～L10 in table 2 (representing respectively pilot 1～10);
(3) the automatic formation zone test of excel spreadsheet grid template collection is set and gathers desired data, automatic generation template is set in the excel spreadsheet lattice Sheet1 that wherein, field investigation table metadata is corresponding and automatically generates the Other Main Agronomic Characters mean value of each kind, each kind in the performance of the resistance field of each testing site;
As shown in table 3, described economical character at least 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) and with the fiducial value of check variety in any one or any several combination, the ck in following table represents check variety;
The each kind economical character of table 3 table
As shown in table 4～9, the performance of described resistance field at least comprises any one or several combination arbitrarily in banded sclerotial blight, leaf blast, panicle blast, bacterial leaf-blight, false smut, lodging;
The each kind of table 4 is in the performance of the field of the each point banded sclerotial blight of participating in the experiment
The each kind of table 5 is in the performance of the field of the each point leaf blast of participating in the experiment
The each kind of table 6 is in the performance of the field of the each point panicle blast of participating in the experiment
The each kind of table 7 is in the performance of the field of the each point bacterial leaf-blight of participating in the experiment
The each kind of table 8 is in the performance of the field of the each point false smut of participating in the experiment
The each kind of table 9 is in the field performance of each point lodging property of participating in the experiment
As table 10, table 11, shown in table 12, output and yield component mean value that automatic generation template generates each kind are automatically set in excel spreadsheet lattice Sheet2 corresponding to species test and yield result table metadata, each kind is at the longitudinal arrangement data layout of each cell production of each testing site, the output of described each kind and yield component at least comprise average yield per mu (kilogram), spike length (cm), total grain number (grain)/fringe, real grain number (grain)/fringe, setting percentage (%), mass of 1000 kernel (g), day output (kg), minimum output (kg), any one or the arbitrarily several combination in each testing site output and increase and decrease situation of production peak (kg) and each kind, cell production longitudinal arrangement table is as shown in table 12, wherein, table 12 is made up of these six sublists of table 12-1～table 12-6 successively order, in form Sheet2, will generate each kind at the longitudinal arrangement data layout of each cell production of each testing site, be the data in S2～S211 and T2～T211 in form Sheet2,
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 formation zone test that completes above table template set gathers required data, formula in the I202 of form Sheet1 should be inputted " numerical value of=H202-H215 ", then use mouse drag automatic filling from I203 to I215, obtain the fiducial value of each kind breeding time and check variety;
(5) formula in the I202 of form Sheet2 should be inputted " the numerical value * 100 of numerical value/H215 of=H202-H215 ", then uses mouse drag automatic filling from I203 to I215, obtains the fiducial value of each variety yield and check variety;
(6) formula in the L202 of form Sheet2 should be inputted " the numerical value * 100 of numerical value/K215 of=K202-K215 ", then uses mouse drag automatic filling from L203 to L215, obtains the fiducial value of each kind day output and check variety;
(7) the each kind generating in form Sheet2 is at the longitudinal arrangement data layout of each cell production of each testing site, be the data in S2～S211 and T2～T211 in form Sheet2, wherein in S2～S211, data are respectively in these five testing sites of L1～L5, the cell production I of each kind, II, in III, data is arranged in order, obtain by following formula respectively: " S2=I5 ", " S3=J5 ", " S4=K5 ", " S5=I6 " " S209=I98 ", " S210=J98 ", " S211=K98 ", data in T2～T211 are respectively in these five testing sites of L6～L10, the cell production I of each kind, II, in III, data is arranged in order, obtain by following formula respectively: " T2=I105 ", " T3=J105 ", " T4=K105 ", " T5=I106 " " T209=I198 ", " T210=J198 ", " T211=K198 ", each kind in Sheet2 is copied at the longitudinal arrangement data layout of each cell production of each testing site and paste in " district's examination 99 " or " DPS " system, can carry out variance analysis,
(8) generate form and enter and gather summary.
Claims (1)
1. the method that paddy rice region testing data gathers fast, adopts pre-designed standardized meta data form and template, calculates and gathers paddy rice region test figure fast, it is characterized in that: it comprises the following steps:
(1) collect and arrange metadata from each testing site according to standardized meta data table format, and be entered in corresponding metadata form, collect and arrange at least one group metadata form from each testing site, described metadata form at least comprises field investigation table, species test and yield result table;
(2) data in each metadata form are copied respectively and pasted in excel spreadsheet lattice, wait to copy with gap successively by testing site numbering by the data in the field investigation table of collecting from each testing site to paste in excel spreadsheet lattice worksheet 1, the data in the species test of collecting from each testing site and yield result table are copied to the correspondence position pasting excel spreadsheet lattice worksheet 2 by the method identical with field investigation table;
(3) the automatic formation zone test of excel spreadsheet grid template collection is set and gathers desired data, automatic generation template is set in worksheet 1 and generates the Other Main Agronomic Characters mean value of each kind, each kind is in the performance of 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 (my god), described each kind comprises banded sclerotial blight in the performance of the resistance field of each testing site, leaf blast, panicle blast, bacterial leaf-blight, false smut, lodging property,
Automatic generation template is set in worksheet 2 and generates the output of each kind and yield component mean value, the each kind longitudinal arrangement data layout at each cell production of each testing site, described output and yield component comprise average yield per mu (kilogram), spike length (㎝), total grain number (grain)/fringe, real number (grain)/fringe, setting percentage (%), mass of 1000 kernel (g), day output (㎏), minimum output (㎏), production peak (㎏) and each kind in each testing site output and increase and decrease situation;
(4) in worksheet 1, pass 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 " (per mu yield of each kind per mu yield-check variety)/check variety per mu yield * 100 ", calculate the fiducial value of each kind per mu 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 copied at the longitudinal arrangement data layout of each cell production of each testing site and paste in " district's examination 99 " or " DPS " system, carry out variance analysis;
(8) generate form and enter and gather summary.
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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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
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| CN102138468A (en) * | 2010-01-28 | 2011-08-03 | 长江大学 | Method for periodical evaluation of result of field test of rice and wheat crops |
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| CN102138468A (en) * | 2010-01-28 | 2011-08-03 | 长江大学 | Method for periodical evaluation of result of field test of rice and wheat crops |
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