Rice Research: Open Access
Open Access

The rice productivity was affected significantly and positively by the factors such as; education level of the household head in level of schooling years, method rice sowing, experience in rice production in years and frequency of farm visit. While variables such as: total rice sowing land size and extension contact has significant and negative relationship with rice productivity [1]. It is continuous variable measured in years of schooling which was expected to have positive relationship in determining the rice productivity. As the result of the multiple linear regression model, the variable had significant at 1% significant level with positive relationship in determining rice productivity that is consistent with the result found by Hadush. The coefficient could interpret as; holding the other variables constant this study is 99% confident that rice productivity of the farmers who have one year of schooling higher could increase by 0.029 tons relatively from those farmers one year of schooling lower. The reason for this contribution could be that, as the farmer’s education level is relatively higher it enables them to make good agronomic management practice and apply necessary inputs.

This is categorical variable valued as: ‘1’for rice sown in broadcast and ‘2’ for rice sown in row. Based on the theoretical perspective that rice sown in row gets more pace, lower resource competition, good for follow up and management, etc [2].

Based on these perspectives, this study hypothesized that sowing in row have positive relationship in determining rice productivity. Keeping this hypothesis the MLR model is indicating that, this variable had significant at 1% significance level and positive relationship in determining rice productivity. This result is in-line with the agronomic recommendations provided by agronomy researchers [3]. The coefficient can be interpreted as, this study is 99% confident that the farmers who sow rice in row scored 0.33 tone more rice productivity compared to those farmers who sow in broadcast; keeping the other variables constant.

It is continuous variable, measured in hectare that was hypothesized to have negative relationship with rice productivity [4]. This relationship is expected for the reason that as the land size is being larger, the management power could be dividend so as effective corrective measures may not be taken on time so that it leads to lower productivity. As expected, this variable had significant at 1% significance level and negative relationship with rice productivity. This study is so 99% confident that as the rice sown area in district increases by one hectare, rice productivity could decrease by 0.4.3 tons; keeping the other variables constant.

It is continuous variable measured in number of years of the farmer passes in rice production. Based on the theoretical perspective that as the farmers become experienced it is to meant that they learn well and get more know how about its production, so it was expected this variable to have positive relationship with rice productivity [5]. The result of MLR, is indicating that this variable has significant and positive relationship to rice productivity.

According to the result obtained, keeping the other variables constant this study is 99% confident that rice productivity increases by 0.056 tons as the farmers become one year more experienced relatively to the other farmers.

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4. Rugumamu CP (2014). Empowering smallholder rice farmers in Tanzania to increase productivity for promoting food security in Eastern and Southern Africa. Agric Food Secur NY :1-8.

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5. Emmanuel D, Enoch OS, Victor O, Henry J (2016). Impact of row-planting adoption on productivity of rice farming in Northern Ghana. RAAE EU 19 :19-28

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