Nigeria presents a unique case study on differences in agricultural productivity between men and women. This study, which captures a comprehensive picture of agriculture across the nation, shows that female farmers produce 16 percent less per hectare than their male counterparts, when plot size, farmer characteristics, and inputs are taken into account. This gender gap is driven by the North East and Central zones located in the Northern region of the country, where female farmers are 28 percent less productive than male farmers. In this region, women, particularly those who are older, farm on smaller plots and have lower levels of key inputs, notably fertilizer and labor, which is a well-documented pattern in many African contexts. The Southern region, however, does not fit this established pattern. When controlling for key characteristics and factors of production, in the South no gender gap in productivity is observed, though female farmers will benefit from additional herbicide and female labor. The notably different patterns in these two regions of the same country provide ample space for further study. Thus, in order to decrease the country-wide gender gap in production, the authors recommend extending access to fertilizer, hired labor, and cash crops to women - particularly those in the North.

Agriculture is an important sector in South Africa, and the impact that education and human development would have made in this sector via non-white small scale farming was limited through biased policies of the apartheid era. Due to apartheid laws, South Africa found itself with high levels of unskilled labour force. This study seeks to find the impacts of literacy rate and human development indices on agricultural production using Auto Regressive Distributed Lag (ARDL) Bounds Test approach to co-integration. A long run relationship among the variables, agricultural production (agriculture GDP), literacy rate and human development indices were found. Literacy rate has a positively significant effect on agricultural production in the long run while Human Development Index has a positive and significant impact in the short run. This indicates that the apartheid regime fell short in recognizing the positive effect of education in the agricultural sector by denying a descent education to the majority of non-whites which were farm labourers or small scale farmers. This study provides some policy recommendations.

Generally, when a certain type of agricultural production is optimized, an interaction is said to exist between two factors when the response (the yield of agricultural production) at the different levels of one factor is affected by the level of the other factor present. Thus, the combined effect of the two factors is not simply the sum of their separate effects, but either more than this sum (synergistic interaction) or less than this sum (antagonistic interaction). A 3 factor interaction between the factor f1, f2, and f3 occurs when the nature of the interaction between f1 and f2 is different at the various levels of f3. Higher order interactions can be similarly defined but these become increasingly more difficult to interpret. A disadvantage of this approach is that it explores each of the agricultural sub-process unrelated to the follow-up sub-process (e.g., this approach optimizes the process of fertilization without links to the crops distribution process and unrelated to the price optimization). This is because each sub-process has a different response unit that is the subject of optimization. Therefore, it is appropriate to investigate the interaction of agricultural production in its integrated form, through a universal response of variables (e.g., in the form of utility from the response). This new approach is introduced in the paper. Thus, the objective of the paper is to present a new method for the formal determination of synergistic effects of the agricultural enterprises management.

It is needed to evaluate the biogas and energy potential from different biomass, including manure, wastewater sludge, energy plants, and food and biofuel processing waste in Latvia. Biogas output from different biomass was investigated in laboratory scale digesters operated at 38 ºC. Biomass mixed with inoculums (fermented cow manure) was investigated for biogas production in fifteen digesters, operated in batch mode at temperature 38 ± 1.0 ºC. Average methane yield per unit of dry organic matter added (dom) from ryegrass silage was 316 l·kgdom E-1 and average methane (CH4) content was 58.36 %. Average methane yield from oat middlings was 244 l·kgdom E-1 and average methane content was 60.72 %. Average methane yield from jam was 728 l·kgdom E-1 and average methane content was 62.77 %. All investigated biomass can be successfully cultivated for energy production in Latvia.

Nigeria′s Biofuels Policy introduced in 2007 mandates a 10% blend (E10) of bioethanol with gasoline. This study investigates the potential for the development of a cellulosic ethanol industry based on the availability of agricultural residues and models the number of commercial processing facilities that could be sited in the six Geo-political zones. The potential for cellulosic ethanol production from agricultural residues in Nigeria is 7556km³ per annum exceeding the mandate of 10% renewable fuel required and providing the potential for 12 large- and 11 medium-scale processing facilities based on the use of a single feedstock. Cassava and yam peelings provided in excess of 80% of the process residues available with enough feedstock to supply 10 large-scale facilities with a fairly even distribution across the zones. Sorghum straw, millet straw and maize stalks represented 75% of the potential resource available from field residues with the potential to supply 2 large- and 7 medium-scale processing facilities, all of which would be located in the north of the country. When a multi-feedstock approach is used, this provides the potential for either 29 large- or 58 medium-scale facilities based on outputs of 250 and 125km³ per annum respectively.

The aim of the paper was to assess the relation between agricultural production factors and effectiveness in European Union’s agriculture. For each country two synthetic coefficients were calculated using TOPSIS method. The first one characterises production factors relations, the latter one displays effectiveness of production factors. The objective of the research was to verify the correlation between these indices. The analysis proved that in many analysed countries the agricultural potential is correlated positively with the agricultural effectiveness. 

Generally, when a certain type of agricultural production is optimized, an interaction is said to exist between two factors when the response (the yield of agricultural production) at the different levels of one factor is affected by the level of the other factor present. Thus, the combined effect of the two factors is not simply the sum of their separate effects, but either more than this sum (synergistic interaction) or less than this sum (antagonistic interaction). A 3 factor interaction between the factor f₁, f₂, and f₃ occurs when the nature of the interaction between f₁and f₂ is different at the various levels of f₃. Higher order interactions can be similarly defined but these become increasingly more difficult to interpret. A disadvantage of this approach is that it explores each of the agricultural sub-process unrelated to the follow-up sub-process (e.g., this approach optimizes the process of fertilization without links to the crops distribution process and unrelated to the price optimization). This is because each sub-process has a different response unit that is the subject of optimization. Therefore, it is appropriate to investigate the interaction of agricultural production in its integrated form, through a universal response of variables (e.g., in the form of utility from the response). This new approach is introduced in the paper. Thus, the objective of the paper is to present a new method for the formal determination of synergistic effects of the agricultural enterprises management.  

In order to facilitate interdisciplinary design and appraisal of agricultural policies, a comprehensive database covering both geophysical and socioeconomic information related to agricultural production has been constructed for all 3,773 agricultural communities in Japan's Chiba Prefecture. The database covers four categories of information layers: (a) current and historic data on agricultural production (the “dependents”); (b) data on geophysical factors affecting agricultural production (the “unchangeables”); (c) data on man-made infrastructures affecting agricultural production (the “long-term changeables”); and (d) data on other socioeconomic factors affecting agricultural production (the “short-term changeables”). Three applications using the database are also introduced.

The objectives of this study were to estimate the potential biomass yield by using the biomass conversion index and evaluate the potential energy production by using the energy conversion index of biomass. Estimating the total biomass yield in Korea showed 9,646.3 thousand tons produced in 2012. Subsequent evaluation of the potential energy production using the estimated biomass yield in 2012 indicated that the calorific values were varied from 3,800 to 4,500 kcal kg-1 for crop- and from 4,100 to 4,300 kcal kg-1 for woody-based biomass, respectively. Among the examined biomass materials, the pruned branch of a nut tree appeared to be the greatest in bio-energy production showing 6,300 kcal kg-1 in calorific value. Total potential energy production from agricultural by-products was estimated approximately at 3,966,000 TOE. Among the agricultural by-products examined, rice straw showed the greatest energy production potential being at 2,321,000 TOE. Furthermore, it might contribute to establishing the countermeasures of biomass utility in agricultural sector based on regional distribution chart of the potential biomass and energy yields in Korea.