Assessment of causality between climate variables and production for whole crop maize using structural equation modeling
0
조회
0
다운로드
6
인용
0
참고문헌
키워드
초록
This study aimed to assess the causality of different climate variables on the production of whole crop maize (Zea mays L.; WCM) in the central inland region of the Korea. Furthermore, the effect of these climate variables was also determined by looking at direct and indirect pathways during the stages before and after silking. The WCM metadata (n = 640) were collected from the Rural Development Administration’s reports of new variety adaptability from 1985–2011 (27 years). The climate data was collected based on year and location from the Korean Meteorology Administration’s weather information system. Causality, in this study, was defined by various cause-and-effect relationships between climatic factors, such as temperature, rainfall amount, sunshine duration, wind speed and relative humidity in the seeding to silking stage and the silking to harvesting stage. All climate variables except wind speed were different before and after the silking stage, which indicates the silking occurred during the period when the Korean season changed from spring to summer. Therefore, the structure of causality was constructed by taking account of the climate variables that were divided by the silking stage. In particular, the indirect effect of rainfall through the appropriate temperature range was different before and after the silking stage. The damage caused by heat-humidity was having effect before the silking stage while the damage caused by night-heat was not affecting WCM production. There was a large variation in soil surface temperature and rainfall before and after the silking stage. Over 350 mm of rainfall affected dry matter yield (DMY) when soil surface temperatures were less than 22℃ before the silking stage. Over 900 mm of rainfall also affected DMY when soil surface temperatures were over 27℃ after the silking stage. For the longitudinal effects of soil surface temperature and rainfall amount, less than 22℃ soil surface temperature and over 300 mm of rainfall before the silking stage affected yield through over 26℃ soil surface temperature and less than 900 mm rainfall after the silking stage, respectively.
Abstract
This study aimed to assess the causality of different climate variables on the production of whole crop maize (Zea mays L.; WCM) in the central inland region of the Korea. Furthermore, the effect of these climate variables was also determined by looking at direct and indirect pathways during the stages before and after silking. The WCM metadata (n = 640) were collected from the Rural Development Administration’s reports of new variety adaptability from 1985–2011 (27 years). The climate data was collected based on year and location from the Korean Meteorology Administration’s weather information system. Causality, in this study, was defined by various cause-and-effect relationships between climatic factors, such as temperature, rainfall amount, sunshine duration, wind speed and relative humidity in the seeding to silking stage and the silking to harvesting stage. All climate variables except wind speed were different before and after the silking stage, which indicates the silking occurred during the period when the Korean season changed from spring to summer. Therefore, the structure of causality was constructed by taking account of the climate variables that were divided by the silking stage. In particular, the indirect effect of rainfall through the appropriate temperature range was different before and after the silking stage. The damage caused by heat-humidity was having effect before the silking stage while the damage caused by night-heat was not affecting WCM production. There was a large variation in soil surface temperature and rainfall before and after the silking stage. Over 350 mm of rainfall affected dry matter yield (DMY) when soil surface temperatures were less than 22℃ before the silking stage. Over 900 mm of rainfall also affected DMY when soil surface temperatures were over 27℃ after the silking stage. For the longitudinal effects of soil surface temperature and rainfall amount, less than 22℃ soil surface temperature and over 300 mm of rainfall before the silking stage affected yield through over 26℃ soil surface temperature and less than 900 mm rainfall after the silking stage, respectively.
참고문헌 (37)
- Morgan N, "South Korea: determinants of corn import demand", US Department of Agriculture, Economic Research Service, ~ (1994)
- Smith S, "From agriscience to agribusiness. Innovation, technology, and knowledge management", pp.119~130 (2018), Springer International
- Carrie J. Butts-Wilmsmeyer, "Weather During Key Growth Stages Explains Grain Quality and Yield of Maize", Agronomy, 9(1), pp.16~ (2019), MDPI AG[DOI]
- PENG JINGLUN, "사일리지용 옥수수의 건물수량에 영향을 미치는 기후요인 탐색", 한국농림기상학회지, 17(3), pp.261~269 (2015), 한국농림기상학회[DOI]
- Befekadu Chemere, "Detecting dry matter yield trend of whole crop maize considering the climatic factors in the Republic of Korea", Grassland Science, 65(2), pp.116~124 (2019), Wiley[DOI]
- Kim M, "Effect of heavy rainfall events on the dry matter yield trend of whole crop maize (Zea mays L.)", Agriculture, 9(4), pp.75~ (2019), MDPI AG[DOI]
- J.W Jones, "The DSSAT cropping system model", European Journal of Agronomy, 18(3-4), pp.235~265 (2003), Elsevier BV[DOI]
- Gerrit Hoogenboom, "From genome to crop: integration through simulation modeling", Field Crops Research, 90(1), pp.145~163 (2004), Elsevier BV[DOI]
- Dean P. Holzworth, "APSIM – Evolution towards a new generation of agricultural systems simulation", Environmental Modelling & Software, 62, pp.327~350 (2014), Elsevier BV[DOI]
- Basso B, "Review of crop yield forecasting methods and early warning system", Proceedings of the First Meeting of the Scientific Advisory Committee of the Global Strategy to Improve Agricultural and Rural Statistics, pp.41~ (2013)
- Jöreskog KG, "LISREL 8: user’s reference guide" (1996), Scientific Software International;
- Van Montfort K, "Recent developments on structural equation models: theory and applications", pp.19~ (2004), Springer Science & Business Media
- Grace JB, "Structural equation modeling and natural systems" (2006), Cambridge University Press
- Li XY, "Planting density and irrigation timing affects cleistogenes songorica seed yield sustainability", Agron J, 106, pp.1690~1696 (2014)[DOI]
- Tao Zhang, "Structural equation modeling of the Canadian flax (Linum usitatissimum L.) core collection for multiple phenotypic traits", Canadian Journal of Plant Science, 94(8), pp.1325~1332 (2014), Canadian Science Publishing[DOI]
- 김문주, "구조방정식 모형을 이용한 이탈리안 라이그라스 생산량에 대한 기후요인의 연구", 응용통계연구, 27(7), pp.1187~1196 (2014), 한국통계학회
- 김문주, "Causality between climatic and soil factors on Italian ryegrass yield in paddy field via climate and soil big data", 한국축산학회지, 61(6), pp.324~332 (2019), 한국축산학회[DOI]
- Moonju Kim, "Comparison of causality of temperature and precipitation on Italian ryegrass (Lolium multiflorum Lam.) yield between cultivation fields via multi-group structural equation model analysis in the republic of Korea", Agriculture, 9(12), pp.254~ (2019), MDPI AG[DOI]
- 김문주, "청보리 생산량의 기후요인 분석을 위한 베이지안 구조방정식 모형", 응용통계연구, 29(2), pp.331~344 (2016), 한국통계학회
- Moonju Kim, "Causality of climate and soil factors affecting whole crop rye (Secale cereale L.) yield as part of natural ecosystem structure via longitudinal structural equation model in the Republic of Korea", Grassland Science, 66(2), pp.110~115 (2020), Wiley[DOI]
- McWilliams DA, "Corn growth and management quick guide" (1999), North Dakota State University
- Ko JW, "The characteristics of spatial distribution of temperature and regionalization in Korea", J Clim Res, 1, pp.3~14 (2006)
- Dunson DB, "Bayesian structural equation modeling", Statistical and Applied Mathematical Sciences Institute, ~ (2005)
- Ki-Seon Choi, "Changma onset definition in Korea using the available water resources index and its relation to the Antarctic oscillation", Climate Dynamics, 38(3-4), pp.547~562 (2012), Springer Science and Business Media LLC[DOI]
- Lee WS, "Interannual variability of heat waves in South Korea and their connection with large‐scale atmospheric circulation patterns", Int J Climatol, 36, pp.4815~4830 (2016)[DOI]
- Soyoung Park, "Soil erosion risk in Korean watersheds, assessed using the revised universal soil loss equation", Journal of Hydrology, 399(3-4), pp.263~273 (2011), Elsevier BV[DOI]
- 문일주, "객관적인 태풍 통계자료 구축을 위한 ‘한반도 근접 태풍’의 정의 및 기준 설정", 대기, 21(2), pp.45~55 (2011), 한국기상학회
- Johnson RA, "Applied multivariate statistical analysis" (2002), Prentice Hall
- Lydolph PE, "The climate of the earth" (1985), Government Institutes, Rowman & Littlefield
- Jin Huang, "Monthly precipitation-temperature relations and temperature prediction over the United States", Journal of Climate, 6(6), pp.1111~1132 (1993), American Meteorological Society[DOI]
- D. B. Peters, "Effect of night air temperature on grain yield of corn, wheat, and soybeans", Agronomy Journal, 63(5), pp.809~809 (1971), Wiley[DOI]
- Jason W. Haegele, "Row arrangement, phosphorus fertility, and hybrid contributions to managing increased plant density of maize", Agronomy Journal, 106(5), pp.1838~1846 (2014), Wiley[DOI]
- Mineo MINAMI, "Effects of lodging on dry matter production, grain yield and nutritional composition at different growth stages in maize (Zea mays L.)", Jpn J Crop Sci, 60(1), pp.107~115 (1991), Crop Science Society of Japan[DOI]
- W. O. Willis, "Corn Growth as Affected by Soil Temperature and Mulch 1", Agronomy Journal, 49(6), pp.323~328 (1957), Wiley[DOI]
- Growth and production of maize: traditional low-input cultivation. Land use, land cover and soil sciences, "Verheye W. Growth", UNESCO-EOLSS, ~ (2010)
- Leonard, D. K., "Soils, crops, and fertilizer use: what, how, and why guide" (1980), Peace Corps, Information Collection & Exchange
- Lee S, "Local effects of climate change over South Korea with a high-resolution climate scenario", Clim Res, 54, pp.85~93 (2012)[DOI]