Evaluation Model of Yellow Peach Climatic Quality Rating in Hilly Mountainous Areas

The study of evaluation indexes for yellow peach climate quality and its meteorological factor model can provide technical support to ensure high-quality production and facilitate rural revitalization. Taking "Jinxiu" variety of yellow peach as the research object, based on the yellow peac...

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Veröffentlicht in:Ying yong qi xiang xue bao = Quarterly journal of applied meteorology 2024-07, Vol.35 (4), p.456-466
Hauptverfasser: Wang, Tianying, Li, Minhua, Wu, Zhongchi, Huang, Anfeng, Yang, Changshun, Yang, Pinling, Wang, Tianke
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container_title Ying yong qi xiang xue bao = Quarterly journal of applied meteorology
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creator Wang, Tianying
Li, Minhua
Wu, Zhongchi
Huang, Anfeng
Yang, Changshun
Yang, Pinling
Wang, Tianke
description The study of evaluation indexes for yellow peach climate quality and its meteorological factor model can provide technical support to ensure high-quality production and facilitate rural revitalization. Taking "Jinxiu" variety of yellow peach as the research object, based on the yellow peach quality observations from 221-1300 m altitude and temperature and rainfall data from 13 meteorological stations near orchards at the middle section of Luoxiao Mountains and the west side of Xuefeng Mountain during 2019-2023, a climatic quality evaluation index for yellow peach and meteorological factorial regression model for its quality elements are constructed by using the methods of weighted summation, Pearson's correlation, regression analysis and multiple covariance analysis, and examined with independent samples. Effects of different altitudes and harvest dates on the climatic quality ratings of yellow peaches are further investigated based on the constructed model. Results show that the main meteorological influencing factors for yellow peach soluble solids content(SS) is the average air temperature 80 d before harvest, for titratable acid content(AT) is the total rainfall 40 d before harvest, and for fruit shape index(IS) are the average air temperature from 1 May to 10 June, total rainfall from 1 May to 10 June, the average air temperature 10 d before harvest and total rainfall 10 d before harvest. Mean absolute error between the simulated and measured values of SS, AT, and IS of validation samples is 0.397%, 0.093%, and 0.010, respectively, and the root mean square error is 0.072%, 0.014%, and 0.001, respectively, and r is 0.649(p=0.05), 0.718(p=0.01), and 0.957(p=0.01), respectively. The simulated quality ratings for 75% of validation samples match the actual climatic quality ratings, while 25% differs by 1 level. Simulation based on the constructed model reveals that the total frequency of superior and excellent quality in the study area shows an increasing and then decreasing trend with both the elevation and the harvesting period, among which the best quality is found in the mid-high elevation areas of 600-820 m or the harvest from 31 July to 10 August. Fruits harvested in high elevation areas above 1300 m or harvested from 21 August to 31 August appear to have a high frequency of lower quality.
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Taking "Jinxiu" variety of yellow peach as the research object, based on the yellow peach quality observations from 221-1300 m altitude and temperature and rainfall data from 13 meteorological stations near orchards at the middle section of Luoxiao Mountains and the west side of Xuefeng Mountain during 2019-2023, a climatic quality evaluation index for yellow peach and meteorological factorial regression model for its quality elements are constructed by using the methods of weighted summation, Pearson's correlation, regression analysis and multiple covariance analysis, and examined with independent samples. Effects of different altitudes and harvest dates on the climatic quality ratings of yellow peaches are further investigated based on the constructed model. Results show that the main meteorological influencing factors for yellow peach soluble solids content(SS) is the average air temperature 80 d before harvest, for titratable acid content(AT) is the total rainfall 40 d before harvest, and for fruit shape index(IS) are the average air temperature from 1 May to 10 June, total rainfall from 1 May to 10 June, the average air temperature 10 d before harvest and total rainfall 10 d before harvest. Mean absolute error between the simulated and measured values of SS, AT, and IS of validation samples is 0.397%, 0.093%, and 0.010, respectively, and the root mean square error is 0.072%, 0.014%, and 0.001, respectively, and r is 0.649(p=0.05), 0.718(p=0.01), and 0.957(p=0.01), respectively. The simulated quality ratings for 75% of validation samples match the actual climatic quality ratings, while 25% differs by 1 level. Simulation based on the constructed model reveals that the total frequency of superior and excellent quality in the study area shows an increasing and then decreasing trend with both the elevation and the harvesting period, among which the best quality is found in the mid-high elevation areas of 600-820 m or the harvest from 31 July to 10 August. Fruits harvested in high elevation areas above 1300 m or harvested from 21 August to 31 August appear to have a high frequency of lower quality.</description><identifier>ISSN: 1001-7313</identifier><identifier>DOI: 10.11898/1001-7313.20240406</identifier><language>chi ; eng</language><publisher>Beijing: China Meteorological Press</publisher><subject>Air temperature ; Altitude ; Altitude effects ; Climate models ; Climatic indexes ; Elevation ; Error analysis ; Fruits ; High frequency ; hilly mountainous area ; Hydrologic data ; meteorological influential factors ; Mountain regions ; Mountainous areas ; Mountains ; Peaches ; Precipitation ; Quality assessment ; quantitative simulation ; Rainfall ; Rainfall data ; Ratings ; Regeneration ; Regression analysis ; Regression models ; spatio-temporal variation characteristics ; Weather stations ; yellow peach quality</subject><ispartof>Ying yong qi xiang xue bao = Quarterly journal of applied meteorology, 2024-07, Vol.35 (4), p.456-466</ispartof><rights>Copyright China Meteorological Press 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,27903,27904</link.rule.ids></links><search><creatorcontrib>Wang, Tianying</creatorcontrib><creatorcontrib>Li, Minhua</creatorcontrib><creatorcontrib>Wu, Zhongchi</creatorcontrib><creatorcontrib>Huang, Anfeng</creatorcontrib><creatorcontrib>Yang, Changshun</creatorcontrib><creatorcontrib>Yang, Pinling</creatorcontrib><creatorcontrib>Wang, Tianke</creatorcontrib><title>Evaluation Model of Yellow Peach Climatic Quality Rating in Hilly Mountainous Areas</title><title>Ying yong qi xiang xue bao = Quarterly journal of applied meteorology</title><description>The study of evaluation indexes for yellow peach climate quality and its meteorological factor model can provide technical support to ensure high-quality production and facilitate rural revitalization. Taking "Jinxiu" variety of yellow peach as the research object, based on the yellow peach quality observations from 221-1300 m altitude and temperature and rainfall data from 13 meteorological stations near orchards at the middle section of Luoxiao Mountains and the west side of Xuefeng Mountain during 2019-2023, a climatic quality evaluation index for yellow peach and meteorological factorial regression model for its quality elements are constructed by using the methods of weighted summation, Pearson's correlation, regression analysis and multiple covariance analysis, and examined with independent samples. Effects of different altitudes and harvest dates on the climatic quality ratings of yellow peaches are further investigated based on the constructed model. Results show that the main meteorological influencing factors for yellow peach soluble solids content(SS) is the average air temperature 80 d before harvest, for titratable acid content(AT) is the total rainfall 40 d before harvest, and for fruit shape index(IS) are the average air temperature from 1 May to 10 June, total rainfall from 1 May to 10 June, the average air temperature 10 d before harvest and total rainfall 10 d before harvest. Mean absolute error between the simulated and measured values of SS, AT, and IS of validation samples is 0.397%, 0.093%, and 0.010, respectively, and the root mean square error is 0.072%, 0.014%, and 0.001, respectively, and r is 0.649(p=0.05), 0.718(p=0.01), and 0.957(p=0.01), respectively. The simulated quality ratings for 75% of validation samples match the actual climatic quality ratings, while 25% differs by 1 level. Simulation based on the constructed model reveals that the total frequency of superior and excellent quality in the study area shows an increasing and then decreasing trend with both the elevation and the harvesting period, among which the best quality is found in the mid-high elevation areas of 600-820 m or the harvest from 31 July to 10 August. Fruits harvested in high elevation areas above 1300 m or harvested from 21 August to 31 August appear to have a high frequency of lower quality.</description><subject>Air temperature</subject><subject>Altitude</subject><subject>Altitude effects</subject><subject>Climate models</subject><subject>Climatic indexes</subject><subject>Elevation</subject><subject>Error analysis</subject><subject>Fruits</subject><subject>High frequency</subject><subject>hilly mountainous area</subject><subject>Hydrologic data</subject><subject>meteorological influential factors</subject><subject>Mountain regions</subject><subject>Mountainous areas</subject><subject>Mountains</subject><subject>Peaches</subject><subject>Precipitation</subject><subject>Quality assessment</subject><subject>quantitative simulation</subject><subject>Rainfall</subject><subject>Rainfall data</subject><subject>Ratings</subject><subject>Regeneration</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>spatio-temporal variation characteristics</subject><subject>Weather stations</subject><subject>yellow peach quality</subject><issn>1001-7313</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNo9kE1LAzEQhnNQsNT-Ai8Bz1snX5vkWEq1QsWvXjwt2Wa2psRN3e0q_fcGK56GeYf34WEIuWIwZcxYc8MAWKEFE1MOXIKE8oyM_sMLMun7UAOAKTk3ekReF18uDu4QUksfksdIU0PfMMb0TZ_Qbd7pPIaPfN_Q58HFcDjSl7y1WxpaugwxHnNtaA8utGno6axD11-S88bFHid_c0zWt4v1fFmsHu_u57NV4a1URSMEqJJb4cGgaBzTtVC6lhZRetCouFRWaEDGrFK2VLoEXhuoG-tqKb0Yk_sT1ie3q_Zd1uyOVXKh-g1St61cl8UjVrXkaKTLLc2kkcp5hVqUBj3zouQqs65PrH2XPgfsD9UuDV2b7SuRfwXZQCnxA2taZ9w</recordid><startdate>20240701</startdate><enddate>20240701</enddate><creator>Wang, Tianying</creator><creator>Li, Minhua</creator><creator>Wu, Zhongchi</creator><creator>Huang, Anfeng</creator><creator>Yang, Changshun</creator><creator>Yang, Pinling</creator><creator>Wang, Tianke</creator><general>China Meteorological Press</general><general>Editorial Office of Journal of Applied Meteorological Science</general><scope>7QH</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>H97</scope><scope>KL.</scope><scope>L.G</scope><scope>DOA</scope></search><sort><creationdate>20240701</creationdate><title>Evaluation Model of Yellow Peach Climatic Quality Rating in Hilly Mountainous Areas</title><author>Wang, Tianying ; 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Taking "Jinxiu" variety of yellow peach as the research object, based on the yellow peach quality observations from 221-1300 m altitude and temperature and rainfall data from 13 meteorological stations near orchards at the middle section of Luoxiao Mountains and the west side of Xuefeng Mountain during 2019-2023, a climatic quality evaluation index for yellow peach and meteorological factorial regression model for its quality elements are constructed by using the methods of weighted summation, Pearson's correlation, regression analysis and multiple covariance analysis, and examined with independent samples. Effects of different altitudes and harvest dates on the climatic quality ratings of yellow peaches are further investigated based on the constructed model. Results show that the main meteorological influencing factors for yellow peach soluble solids content(SS) is the average air temperature 80 d before harvest, for titratable acid content(AT) is the total rainfall 40 d before harvest, and for fruit shape index(IS) are the average air temperature from 1 May to 10 June, total rainfall from 1 May to 10 June, the average air temperature 10 d before harvest and total rainfall 10 d before harvest. Mean absolute error between the simulated and measured values of SS, AT, and IS of validation samples is 0.397%, 0.093%, and 0.010, respectively, and the root mean square error is 0.072%, 0.014%, and 0.001, respectively, and r is 0.649(p=0.05), 0.718(p=0.01), and 0.957(p=0.01), respectively. The simulated quality ratings for 75% of validation samples match the actual climatic quality ratings, while 25% differs by 1 level. Simulation based on the constructed model reveals that the total frequency of superior and excellent quality in the study area shows an increasing and then decreasing trend with both the elevation and the harvesting period, among which the best quality is found in the mid-high elevation areas of 600-820 m or the harvest from 31 July to 10 August. Fruits harvested in high elevation areas above 1300 m or harvested from 21 August to 31 August appear to have a high frequency of lower quality.</abstract><cop>Beijing</cop><pub>China Meteorological Press</pub><doi>10.11898/1001-7313.20240406</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record>
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subjects Air temperature
Altitude
Altitude effects
Climate models
Climatic indexes
Elevation
Error analysis
Fruits
High frequency
hilly mountainous area
Hydrologic data
meteorological influential factors
Mountain regions
Mountainous areas
Mountains
Peaches
Precipitation
Quality assessment
quantitative simulation
Rainfall
Rainfall data
Ratings
Regeneration
Regression analysis
Regression models
spatio-temporal variation characteristics
Weather stations
yellow peach quality
title Evaluation Model of Yellow Peach Climatic Quality Rating in Hilly Mountainous Areas
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