Influence of decision-making factors on paddy production of farmers in selected integrated agriculture development areas, Malaysia

Malaysian rice industry is carefully monitored by several relevant agencies as it is a major concern in relation to the nation‟s food security agenda. The Department of Agriculture Selangor (DOA) in 2009 had classified the granary areas or Integrated Agriculture Development Area (IADA) under three categories, namely;poor yield (KADA, Krian Sungai Manik, and Kemasin Semerak), average yield (MADA, KETARA, and Seberang Perak) and high yield (North West Selangor and Penang IADA). Meanwhile, during the Tenth Malaysian Plan (2011 – 2015) period, the government had set a target for every paddy farmer of 10 mt/ha, to ensure that the availability and accessibility of rice are maintained and sufficient. However, the latest numbers from 2011 revealed that the average production per farmer from the main granary areas was still 4.77 mt/ha, not much different from 2008 as resulted as 4.02 mt/ha, whereas in certain parts of the country such as in Sekinchan Selangor, farmers had achieved up to 12 mt/ha. What is the cause of this disparity in production? Despite similarities in facilities,land area, and resources, major differences remain in production. Although there are a multitude of factors that could be relevant to this situation, this study focuses on the factors governing the rice growers‟ decision-making ability that contribute to their readiness to employ the appropriate crop husbandry practices leading to increase in productivity. Structured questionnaires were administrated to 320 respondents from six IADA in Malaysia. Demographically, majority of the respondents was aging farmers and not interested in attending structured training sessions. In fact, they were keen towards hands-on training, like the extension clinic. In terms of productivity level, based on the classification that was fixed by DOA, revealed that only 17.2% farmers achieved higher productivity, where the production range from 7 mt/ha and above while majority of farmers were at the moderate level because they achieved the production between 4.1 to 7 mt/ha, with a mean of 5.35 mt/ha. This situation indicates that our farmers fall under the moderate level of productivity. Nine factors were identified as the decision-making variables, through mental model of farming that was introduced previously by Eckert & Bell (2005) and Krauss et. al (2009). From the results, two variables (farming knowledge and motivational values) denoted a significant and positive relationship towards farmers‟ productivity. Although they are weak contributions, but still it can be express that the productivity is more likely to increase when farming knowledge and motivation also increase. The study also revealed that only two predictor variables were found to be significance in explaining farmers‟ productivity, which are farming knowledge and motivational value and the two predictor variables explained about 6% of the variance in the farmers‟ productivity. On top of that, farming knowledge makes the strongest unique contribution followed by motivational value in explaining the farmers‟ productivity, when the variance explained by all other predictor variables in the model is controlled for. From the study, it can be suggested that knowledge play an important role in farming practices, as well as motivation since both of these factors may contribute on farmers‟ decision-making, which directly will reflect on productivity. Besides,there is a dire need to get the best approaches to make rice farming more attractive to the youth, since the majority of the rice farmers are aging farmers. It is also necessary to strengthen the extension strategies especially on the extension agent competencies in order to equip farmers with the right approaches. The ability to integrate the elements of decision-making would help the government and related stakeholders to revitalize the agriculture sector to become more effective and efficient in years to come.

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