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

Abstract

In this study, the causality of climate and soil factors affecting the whole crop rye yield was identified via structural equation model, such as the seasonal effect between autumn and next spring, the indirect effect of the precipitation and the relationship between soil physical and climate factors. To identify the causality under the part of natural ecosystem, the structure was modeled with climates (autumnal accumulated temperature, autumnal growing days, spring accumulated temperature, spring growing days, spring amount of precipitation, and spring days with precipitation) and soil physical properties (drainage classes, effective soil depth, slope, and gravel content). As a result, we could estimate various specific relationships: First, the seasonal effect of accumulated temperature and growing days between autumn and next spring was obvious for the yield. Second, the precipitation had indirectly influenced the yield through suitable temperature in next spring. Final, the soil physical factor was related to the only precipitation, which means the effect of soil factor was significant through the spring precipitation. The structure could be modeled with climate and soil physical factors as a part of natural ecosystem, which was performed at the first time in the Republic of Korea and will be helpful to extend the structure with various factors in the future study.

Causality between climatic and soil factors on Italian ryegrass yield in paddy field via climate and soil big data

“…Therefore, we concluded that the precipitation effect on yield was effective based on sufficient temperature in the spring (14.18°C or more, at least 7.42°C or more). According to Kim et al [23], the yield increased with increasing temperature, and the effect of precipitation on yields fluctuated significantly only at high temperature. The optimum growing temperature was in the range of 15°C–18°C, and IRG could maintain growth down to 4°C [29].…”

“…The climate information from the prototyped IRG model could be used as good prior information in cases of a small sample of cool-season forage crops. Causality of both climatic and soil factors on yield were identified initially by SEM for whole crop rye ( Secale cereale L.) [23]. They found that the variation of precipitation was significally effective under the range of high temperature.…”

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

“…This clear tendency was, therefore, certain to reflect both direct and indirect effects on yield in the upland fields. According to Kim et al [17], the fluctuation of precipitation effect on DMY of whole crop rye increased at daily mean temperatures above 8 • C, which means that precipitation affected yield at appropriate temperatures.…”

“…In the Republic of Korea, IRG has mainly been cultivated in paddy fields under the rice-rotation system, accounting for 81.4% of the total IRG cultivation areas (21,700 ha) in 2007 [3,4]. IRG utilization has expanded gradually to 56.3% of the total area used for forage production, and the area is restricted temperature was less relevant [17]. However, these studies did not take into account the field types closely related to climate, soil, and cultivation techniques.…”

“…Furthermore, multi-group SEM has been performed to compare the causality between two or more groups. Since SEM is used to check various cause-and-effect relationships simultaneously, it could contribute to an understanding of various climatic and soil factors, and of the causality between these factors for whole crop rye (Secale cereale L.) as part of the natural ecosystem [17]. The effect and flow of climates on crop productivity in the natural eco-system are more extremely complex because of the mixed factors.…”