Yield Prediction Modeling for Sorghum–Sudangrass Hybrid Based on Climatic, Soil, and Cultivar Data in the Republic of Korea

Jinglun Peng, Moonju Kim and Kyungil Sung
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Jinglun Peng: Institute of Animal Resources, Kangwon National University, Chuncheon 24341, Korea
Moonju Kim: Institute of Animal Resources, Kangwon National University, Chuncheon 24341, Korea
Kyungil Sung: College of Animal Life Sciences, Kangwon National University, Chuncheon 24341, Korea;

Agriculture, 2020, vol. 10, issue 4, 1-11

Abstract: The objective of this study was to construct a sorghum–sudangrass hybrid (SSH) yield prediction model based on climatic, soil, and cultivar information in the southern area of the Korean Peninsula. Besides, the effects of climatic factors on SSH yield were investigated simultaneously. The SSH dataset ( n = 105), including Dry Matter Yield (DMY, kg/ha), Seeding-Harvest Accumulated Temperature (SHaAT, °C), Seeding–Harvest Accumulated Precipitation (SHAP, mm), Seeding–Harvest Sunshine Duration (SHSD, h), Soil Suitability Score (SSS), and cultivar maturity information, was developed for model construction. Subsequently, using general linear modeling method, the SSH yield prediction model was constructed as follows: DMY = 6.5SHaAT – 4.9SHAP + 13.8SHSD – 54.4SSS – 1036.4 + Maturity. The impacts of the accumulated thermal climatic variables and accumulated precipitation during crop growth on the variance of SSH yield in this region were confirmed. The summer-concentrated precipitation in the southern area of the Korean Peninsula exceeded the proper range of SSH water requirement and led to stresses to its yield production. Furthermore, to improve the data quality for high fitness model construction, the standard schedule for forage crop cultivation experiment in this region was recommended to be developed, especially under the data requirement in the context of the big data era.

Keywords: sorghum–sudangrass hybrid; climatic factors; soil; cultivar maturity; general linear model (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2020
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