Influence of climatic variables on soybean yield in Yogyakarta, Indonesia / Putu Sudira.

Putu Sudira

Date

1985

Abstract

The second and fourth degree multiple regression were fitted to the data obtained the effect of climatic variables independently on soybean yield at different stages of crop development. Likewise, the selected crop stages method using the stepwise regression procedure was utilized to establish a general prediction model for soybean yield. An attempt was made to compare the results obtained from the stepwise regression method with the results of the second and fourth degree multiple regression technique. The results obtained in the second and fourth degree multiple regression showed that only maximum temperature and sunshine duration equation model for the first growing season were significant at 5% level of significance. On the other hand, the stepwise regression model identified only the most significant climatic variables that affect the yield of soybean. The results showed that for the first growing season, out of twelve climatic variable entered, 6 variables were only considered which explains 97.93% of the variation of the soybean yield and found to be significant at 5% level. For the second growing season, 6 variables were also considered which explains 99.79% of the variation of the soybean yield, and it was significant at 1% level. The second and fourth degree regression model appear to be sufficiently reliable for practical purpose. However, the selected crop stages method using the stepwise regression procedure gave a relatively better result than that of the second and fourth degree multiple regression in predicting the yield of soybean

Document Type

Master Thesis

Language

English

Location

UPLB Main Library Special Collections Section (USCS)

Call Number

LG 995 1985 A38 P88

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