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2017 ASHS Annual Conference

Effects of Precipitation on Apple Phenology in Addition to Air Temperature

Friday, September 22, 2017
Kona Ballroom (Hilton Waikoloa Village)
Jung Gun Cho, Colorado State University, Fort Collins, CO
Patrick Martin, Colorado State University, Fort Collins, CO
Sunil Kumar, USDA, Raleigh, NC
Hyun-Hee Han, Rural Development Administration, Wanju, Korea, Republic of (South)
Spring phenology of apple (Malus pumila var. domestica) is well explained and predicted by the effect of temperature in many previous studies. Although the temperature is a predominant factor, we know also other environmental factors, e.g. precipitation, light intensity, and photoperiod, affect on phenological events. However, there are not many studies on these additional factors. In this study, we tested the effect of precipitation in addition to the temperature influenced on phenology.
We selected 42 apple orchards including 8 experiment orchards in the research stations and 34 commercial orchards managed by experienced growers across South Korea. We observed the dates of three phases of spring phenology; budding, flowering, and full bloom for 4 years from 2011 to 2014. Monthly climate data in the each research site were calculated by the spatial interpolation methods from the 90 weather stations by Korea Meteorological Administration. Mean air temperatures in March were processed by the inverse distance weight interpolation with 30 meter resolution digital elevation model. And precipitations in March were processed by the Kriging interpolation. Linear regression analyses were used to build models which were compared by Akaike information criteria(AIC).
In all phenologcial events, the multiple regression models with the both of temperature and precipitation were all improved from the models with only temperature. In the model of budding dates, the determination of coefficient(R2) in the precipitation adding model was 0.77(P<0.001, AIC=59.91) compared to 0.60(P<0.001, AIC=77.14) of the temperature only model. The R2 of the flowering date model with precipitation was 0.77(P<0.001, AIC=68.66) compared to 0.64(P<0.001, AIC=85.32) of the model without it. Also, the R2 of the full blooming date model with precipitation(R2=0.68, P<0.001, AIC= 70.06) was improved from the model without it(R2=0.59, P<0.001, AIC=78.21). Budding date responded to the linear trend at -2.2 day°C-1 of temperature and -0.079 day·mm-1 of precipitation. Also, flowering date and full bloom date showed linear trends at -2.7 day°C-1 with -0.086 day·mm-1 and -2.8 day°C-1 with -0.061 day·mm-1, respectively
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