Construction And Effect Verification Of Newhall Navel Orange Ecological Environment Adaptability Evaluation Algorithm

China’s citrus industry,the world’s largest,has entered a period of rapid development in the 21 st century and has become an essential pillar industry for rural revitalization in the south.A main citrus cultivar,the Newhall navel orange is highly adaptable and can be found throughout the South.Using 23 Chinese Newhall orchards in different ecological settings as materials,we studied and analyzed the differences in fruit quality between different locations and used various analytical methods to develop a comprehensive evaluation model and grading criteria for fruit quality in different Chinese Newhall navel orange orchards.Based on the method of partial least squares regression,the internal relationship between quality and meteorological factors was analyzed,and aimed to establish the response evaluation model of meteorological factors of fruit comprehensive quality,clarify the comprehensive grade of fruit quality and their corresponding meteorological characteristics from different Newhall navel orange(Citrus sinensis [L.] Osb.cv.Newhall)orchards in China,and provide a reference for the ecological environment adaptability and suitable planting.The main findings are as follows.1.The distribution and ecological environment characteristics of various grades of Newhall navel oranges were expanded,and a meteorological response algorithm model was constructed for fruit core indicators.Core indicators were identified by measuring external and internal fruit quality indicators and using correlation analysis,principal component analysis and cluster analysis,including integrated color index,fruit weight,soluble solids,solid acid ratio and vitamin C content.The comprehensive evaluation models of fruit quality were established by analytic hierarchy process(AHP),principal component analysis(PCA)and fuzzy comprehensive appraisal(FCA),respectively.Verified with sensory quality evaluation to determine the AHP model with the optimal for the Newhall fruit comprehensive evaluation by combining the eigenvalues of each principal component to achieve automatic assignment of AHP judgment matrix: Y(comprehensive value)=0.06× comprehensive color index + 0.26× single fruit weight +0.16× soluble solid content +0.42× solid acid ratio +0.11× vitamin C content(standardized value).The comprehensive fruit quality indicators of different Newhall orchards were ranked,and the classification threshold was determined as follows: ≥0.60 was a first class orchard;0.45—0.60 was a second class orchard;0.30—0.45 was a third class orchard;<0.30 was a fourth class orchard.2.The distribution and ecological environment characteristics of the various grades of Newhall navel orange orchards were expanded,and a meteorological response algorithm model for the fruit core indicators were constructed.The distribution and ecological environment characteristics of different grades of Newhall navel orange orchards were clarified using a comprehensive evaluation algorithm model of fruit quality.First class orchards,mainly concentrated in southern Jiangxi,southern Hunan,and eastern Guangdong,with active accumulation temperature,effective accumulation temperature,maximum sunshine hours,and surface temperature;Second class orchards,mostly concentrated in northern Guangxi and western Fujian,are characterized by higher temperature accumulation and rainfall;Third class orchards,mainly concentrated in western Hunan and the middle and upper reaches of the Yangtze River,have relatively low rainfall and temperature accumulation;Fourth class orchards,mainly located in southern Zhejiang,receive the highest rainfall.Partial least square regression was used to analyze the core index of fruit quality and the effect weight of the response algorithm model for meteorological factors at different development stages.The dominant meteorological factors for each core index are screened and an algorithm model between them is constructed to enable a quantitative analysis of the impact of the dominant meteorological factors on the core quality indicators.3.The Newhall navel orange fruit integrated quality meteorological factor response algorithm model was constructed to complete the internal validation.The Newhall navel orange comprehensive evaluation algorithm model was used to analyze the fruit comprehensive quality of Newhall navel orange in different ecological regions,and the partial least squares regression analysis algorithm model was constructed to analyze the fruit comprehensive quality meteorological factor response evaluation algorithm model: Y=-0.00011*A3(rainfall in July)-0.00022*A5(rainfall in September)+ 0.0031*B6(surface temperature in October)+ 0.0043*B10(annual average surface temperature)+ 0.0005*C3(sunlight hours in July)+ 0.00001*D10(annual average active accumulated temperature)+ 0.00001*E10(annual effective accumulated temperature)-0.0011*F3(relative humidity in July)-0.0013*F5(relative humidity in September)-0.0001*G4(August runoff)-0.006*G6(October runoff)-0.0009*G8(December runoff)+ 0.0049*H3(average temperature in July)+0.0051*H10(annual average temperature)+ 0.0027*I4(lowest temperature in August)+ 0.0025*J7(the highest temperature in November)+ 0.0036* J8(the highest temperature in December)+ 0.0077* J10(annual highest temperature)+ 0.0003*K4(temperature difference in August)-0.401;The model was validated using 2022 Newhall navel orange fruit quality and meteorological data.The results show that the relative error of the Newhall navel orange integrated quality meteorological factor response algorithm model is less than 20 percent,and the accuracy of the classification of the orchard is 87.5 percent.