The central theme of this research endeavour was to compute the cost and net returns of wheat crop. This study has also highlighted the significant variables contributing in wheat productivity. The study universe was two focused villages namely Malok-Korona and Peer-Qila of Ekaghund Tehsil, Mohmand Agency. The proportional allocation sampling technique was used to get the required sample size of 70 respondents. However, 26 respondents from Malok-Korona and 44 respondents from Peer-Qila were interviewed through face to face interview technique. The marked findings of this study divulge that vast majority of the farmers (61.43%) were using certified seed and the study area was predominantly dependent upon rainfall as reported by 60 % of the respondents. It is further revealed that the mean cost of production incurred by the sampled growers was estimated as Rs. 30,000 per acre. Income trend observed by 70 per cent of the respondent through wheat crop was found Rs.40000 per acre. The average income of farmers through wheat crop was Rs.35286 per acre. The estimated results of regression analysis corroborate the expected sign of the majority of coefficient of explanatory variables. Among explanatory variables seed, irrigation and labor days were significant while urea and FYM were found insignificant for crop yield. The study recommends that attempts for awareness, supply of loans, inputs like fertilizer, pesticide, apt agriculture approaches, demonstration plots and training programs should be made available to farmers for higher wheat production in Mohmand Agency.
The agriculture sector is deemed as more vulnerable to climate change as its variation can directly affect the crop’s productivity. However, climate change impact and farmers adaptation strategies were not figured out in Khyber Pakhtunkhwa Province, Pakistan by previous researchers and formed the rationale for this research endeavor. This research has assessed the Climate Change impact on wheat productivity and farmers adaptability strategies. The non-climatic variables (wheat yield and area under wheat cultivation) and climatic variables (temperature, precipitation and humidity) were taken into consideration. The Panel Data of thirty years (1985–2015) about non climatic and climatic variables was obtained from different secondary sources; however, primary data was collected from sampled farmers. The econometric diagnostic tests were encompassed to confirm the validity of the data. Chow test was used to underscore the structural breaks. Fixed Effect Model was adopted as suggested by Hausman Test. The salient findings express that temperature has inverse relationship with wheat productivity. This implies that by soaring one Celsius degree Centigrade (°C) temperature can plunge down the wheat productivity by 0.074 percent. Similarly, the association of precipitation was also observed negative with wheat. Contrary to this, humidity is observed as positively associated with wheat. The study concludes the substantial association of climate change with wheat crop, whereas, farmers had less awareness about the adoptability strategies. It is recommended that high temperature resistant wheat varieties may be provided to farmers and disseminates the exalted adaptation strategies with respect to climate change to overhaul their existing crop management practices.
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