Kim Moonju, Peng Jing-Lun, Sung Kyungil
Institute of Animal Resources, Kangwon National University, Chuncheon 24341, Korea.
Department of Animal Industry Convergence, College of Animal Life Sciences, Kangwon National University, Chuncheon 24341, Korea.
J Anim Sci Technol. 2019 Nov;61(6):324-332. doi: 10.5187/jast.2019.61.6.324. Epub 2019 Nov 30.
This study aimed to identify the causality between climatic and soil variables affecting the yield of Italian ryegrass ( Lam., IRG) in the paddy field by constructing the pathways via structure equation model. The IRG data (n = 133) was collected from the National Agricultural Cooperative Federation (1992-2013). The climatic variables were accumulated temperature, growing days and precipitation amount from the weather information system of Korea Meteorological Administration, and soil variables were effective soil depth, slope, gravel content and drainage class as soil physical properties from the soil information system of Rural Development Administration. In general, IRG cultivation by the rice-rotation system in paddy field is important and unique in East Asia because it contributes to the increase of income by cultivating IRG during agricultural off-season. As a result, the seasonal effects of accumulated temperature and growing days of autumn and next spring were evident, furthermore, autumnal temperature and spring precipitation indirectly influenced yield through spring temperature. The effect of autumnal temperature, spring temperature, spring precipitation and soil physics factors were 0.62, 0.36, 0.23, and 0.16 in order ( < 0.05). Even though the relationship between soil physical and precipitation was not significant, it does not mean there was no association. Because the soil physical variables were categorical, their effects were weakly reflected even with scale adjustment by jitter transformation. We expected that this study could contribute to increasing IRG yield by presenting the causality of climatic and soil factors and could be extended to various factors.
本研究旨在通过结构方程模型构建路径,确定影响稻田意大利黑麦草(Lolium multiflorum Lam.,IRG)产量的气候和土壤变量之间的因果关系。IRG数据(n = 133)收集自韩国全国农业协同组合联合会(1992 - 2013年)。气候变量包括韩国气象厅天气信息系统中的积温、生长天数和降水量,土壤变量包括农村发展管理局土壤信息系统中作为土壤物理性质的有效土壤深度、坡度、砾石含量和排水等级。一般来说,东亚地区稻田采用稻麦轮作系统种植IRG很重要且具有独特性,因为在农业淡季种植IRG有助于增加收入。结果表明,秋季和次年春季积温与生长天数的季节效应明显,此外,秋季温度和春季降水通过春季温度间接影响产量。秋季温度、春季温度、春季降水和土壤物理因素的影响依次为0.62、0.36、0.23和0.16(P < 0.05)。尽管土壤物理性质与降水量之间的关系不显著,但这并不意味着没有关联。由于土壤物理变量是分类变量,即使通过抖动变换进行尺度调整,它们的影响也反映得较弱。我们期望本研究通过呈现气候和土壤因素的因果关系,有助于提高IRG产量,并可扩展到各种因素。