Technical Efficiency of Rice Farmers in Northern Ghana

Examining the level of farm-specific technical efficiency of farmers growing irrigated and non-irrigated rice in Northern Ghana, this study fitted cross-sectional data into a transcendental logarithmic (translog) production frontier. The study concludes that rice farmers are technically inefficient. There is no significant difference in mean technical efficiencies for non-irrigators (53%) and irrigators (51%). The main determinants of technical efficiency in the study area are education, extension contact, age and family size. Providing farmers with both formal and informal education will be a useful investment and a good mechanism for improving efficiency in rice farming. There is also need for training more qualified extension agents and motivating them to deliver

Interactively modelling land profitability to estimate European agricultural and forest land use under future scenarios of climate, socio-economics and adaptation

Studies of climate change impacts on agricultural land use generally consider sets of climates combined with fixed socio-economic scenarios, making it impossible to compare the impact of specific factors within these scenario sets. Analysis of the impact of specific scenario factors is extremely difficult due to prohibitively long run-times of the complex models. This study produces and combines metamodels of crop and forest yields and farm profit, derived from previously developed very complex models, to enable prediction of European land use under any set of climate and socio-economic data. Land use is predicted based on the profitability of the alternatives on every soil within every 10' grid across the EU. A clustering procedure reduces 23,871 grids with 20+ soils per grid to 6,714 clusters of common soil and climate. Combined these reduce runtime 100 thousand-fold. Profit thresholds define land as intensive agriculture (arable or grassland), extensive agriculture or managed forest, or finally unmanaged forest or abandoned land. The demand for food as a function of population, imports, food preferences and bioenergy, is a production constraint, as is irrigation water available. An iteration adjusts prices to meet these constraints. A range of measures are derived at 10' grid-level such as diversity as well as overall EU production. There are many ways to utilise this ability to do rapidWhat-If analysis of both impact and adaptations. The paper illustrates using two of the 5 different GCMs (CSMK3, HADGEM with contrasting precipitation and temperature) and two of the 4 different socio-economic scenarios ("We are the world", "Should I stay or should I go" which have contrasting demands for land), exploring these using two of the 13 scenario parameters (crop breeding for yield and population) . In the first scenario, population can be increased by a large amount showing that food security is far from vulnerable. In the second scenario increasing crop yield shows that it improves the food security problem

Optimal irrigation water allocation using a genetic algorithm under various weather conditions

Growing water scarcity, due to growing populations and varying natural conditions, puts pressure on irrigation systems, which often are the main consumptive water users. Therefore, water resources management to improve the allocation of limited water supplies is essential. In this study, a non-linear programming optimization model with an integrated soil/water balance is developed to determine the optimal reservoir release policies and the optimal cropping pattern around Doroudzan Dam in the South-West of Iran. The proposed model was solved using a genetic algorithm (GA). Four weather conditions were identified by combining the probability levels of rainfall, evapotranspiration and inflow. Moreover, two irrigation strategies, full irrigation and deficit irrigation were modeled under each weather condition. The results indicate that for all weather conditions the total farm income and the total cropped area under deficit irrigation were larger than those under full irrigation. In addition, our results show that when the weather conditions and the availability of water changes the optimal area under corn and sugar beet decreases sharply. In contrast, the change in area cropped with wheat is small. It is concluded that the optimization approach has been successfully applied to Doroudzan Dam region. Thus, decision makers and water authorities can use it as an effective tool for such large and complex irrigation planning problems

DETERMINANTS OF IRRIGATION TECHNOLOGY CHOICE

Two discrete choice models relate the probability of choosing two water-saving irrigation technologies - —sprinkler and tailwater recovery pits- —to the underlying physical and economic attributes of the farming using a national cross section of farm level data. The results show that small farm size, high water or labor costs, and soils with low water-holding capacity increase the likelihood of adopting sprinkler irrigation. For gravity irrigators, large farms, high water costs, and solid with high water-holding capacity increase the probability of recirculating field runoff. In both models soil characteristics and, to a lesser extent, climate dominate the selection probabilities.Farm Management,

Changing farm types and irrigation as an adaptation to climate change in Latin American agriculture

This paper estimates a model of a farm that treats the choice of crops, livestock, and irrigation as endogenous. The model is composed of a multinomial choice of farm type, a binomial choice of irrigation, and a set of conditional land value functions. The model is estimated across over 2,000 farmers in seven Latin America countries. The results quantify how farmers adapt their choice of farm type and irrigation to their local climate. The results should help governments develop effective adaptation policies in response to climate change and improve the forecasting of climate effects. The paper compares the predicted effects of climate change using both endogenous and exogenous models of farm choice.Climate Change,Crops&Crop Management Systems,Livestock&Animal Husbandry,Agriculture&Farming Systems,Rural Development Knowledge&Information Systems

Smallholder Participation in Agricultural Value Chains: Comparative Evidence from Three Continents

Supermarkets, specialized wholesalers, and processors and agro-exporters’ agricultural value chains have begun to transform the marketing channels into which smallholder farmers sell produce in low-income economies. We develop a conceptual framework through which to study contracting between smallholders and a commodity-processing firm. We then conduct an empirical meta-analysis of agricultural value chains in five countries across three continents (Ghana, India, Madagascar, Mozambique, and Nicaragua). We document patterns of participation, the welfare gains associated with participation, reasons for non-participation, the significant extent of contract non-compliance, and the considerable dynamism of these value chains, as farmers and firms enter and exit frequently.

Reducing Irrigation Water Demand with Cotton Production in West Texas

Due to declining water availability from the Ogallala Aquifer and increasing pumping costs, irrigation management options for cotton are analyzed. The study concludes that supplemental irrigation while meeting crop ET requirements is the most profitable option. Switching from corn to cotton production may reduce irrigation water demand in the region.Ogallala Aquifer, irrigated cotton, irrigation efficiency, water response function, input use optimization, ET, Texas Panhandle, Crop Production/Industries, Resource /Energy Economics and Policy,

Internal Design of a Hydroponics Greenhouse for Tri Cycle Farms

Hydroponics is the agricultural technique of growing plants without soil, using other growing media and added nutrients in a solvent. It is an attractive agricultural method over conventional agriculture because it is more water efficient, is less labor intensive, yields higher quality crops in less time, and is easier to control. According to the Digital Journal, “hydroponics crop value is anticipated to grow to USD 27.29 Billion by 2022 at an estimated CAGR of 6.39% from 2015 to 2020” (Sawant, 2016). Alongside this growing market acceptance for hydroponics, there is also a local demand that requires only a small transportation cost. For the past several years, Tri Cycle Farms - a 501-(c)(3) non-profit urban farm in Fayetteville - has dreamt of building a hydroponics greenhouse because it would provide a source of sustainable financial income, a location for educational programming, and a means of battling food insecurity. Since August 2017, I have been working with Tri Cycle Farms to help make the hydroponics greenhouse project a reality. The objectives of this section of the overall project are 1) to determine desirable crops to be produced, 2) design the internal layout of the chosen greenhouse, and 3) design one hydroponics system using engineering design and fluid mechanics. This thesis report outlines the process of fulfilling these objectives, the justification behind the design decisions, and a discussion of the potential implications moving forward