From Subsistence Agriculture to Commercial Enterprise: Community management of green technologies for resilient food production

The aim of this paper is to emphasize the capacity and resilience of rural communities in regard to sustainable food security by adopting innovative approaches to irrigation. The shift from subsistence to commercial agriculture is promoted as a means to sustainable development. An analysis of the efficacy of irrigation schemes in Zimbabwe suggests that, in terms of providing sustainable agricultural production, they have neither been cost-effective nor have they provided long-term food security to their beneficiaries. This is certainly true of Shashe Scheme and most others in Beitbridge District. The Shashe Irrigation Scheme project represents a bold attempt at developing a fresh approach to the management of communal land irrigation schemes through a Private Public Community Partnership. The model illustrated represents a paradigm shift from subsistence agriculture to a system based on new technologies, market linkages and community ownership that build resilience and lead to sustainable food security and economic prosperity.

Integrated bioenergy and food production

Rising global energy needs and limited fossil fuel reserves have led to increased use of renewable energies. In Germany, this has entailed massive exploitation of agricultural biomass for biogas generation, associated with unsustainable farming practices. Organic agriculture not only reduces negative environmental impacts, organic farmers were also prime movers in anaerobic digestion (AD) in Germany. This study’s aim was to identify the structure, development, and characteristics of biogas production associated with organic farming systems in order to estimate further development, as well as energetic and associated agronomic potentials. Surveys were conducted among organic farms with AD technology. 144 biogas plants could be included in the analysis. Total installed electrical capacity was 30.8 MWel, accounting for only 0.8% of the total installed electrical capacity in the German biogas sector. Recently, larger plant types (>250 kWel) with increased use of (also purchased) energy crops have emerged. Farmers noticed increases in yields (22% on average) and quality of cash crops in arable farming through integrated biogas production. In conclusion, although the share of AD in organic farming is relatively small it can provide various complementary socio-ecological benefits such as the enhancement of food output through digestate fertilization without additional need for land, while simultaneously reducing greenhouse gas emissions from livestock manures and soils. However, to achieve this eco-functional intensification, AD systems and their management have to be well adapted to farm size and production focus and based primarily on residue biomass.

Tanzanian Food Origins and Protected Geographical Indications

As the world`s population is constantly growing, food security will remain on the policy Agenda, particularly in Africa. At the same time, global food systems experience a new wave focusing on local foods and food sovereignty featuring high quality food products of verifiable geographical origin. This article argues that Geographical Indications (GI´s) hold the potential to help transform the Tanzanian agriculture-dependent economy through the tapping of value from unique products, attributing taste and colour to place or regional geography. This study aims to identify the existence and characteristics of food origin products in Tanzania that have potential for GI certification. The hypothesis was that there are origin products in Tanzania whose unique characteristics are linked to the area of production. Geographical indications can be useful policy instruments contributing to food security and sovereignty and quality within an efficient marketing system with the availability of government support, hence the need to identify key candidates for GI certification. Five Tanzanian origin products were selected from 14 candidate agricultural products through a scoping study. Rice from Kyela, Aloe vera, Coffee and Sugar from Kilimanjaro and Cloves from Zanzibar are some of the product cases investigated and provides for in-depth case study, as ´landscape´ products incorporating ´taste of place´. Interviews were conducted to collect quantitative and qualitative data. Data was collected on the production area, product quality perceived by the consumer in terms of taste, flavour, texture, aroma, appearance (colour, size) and perceptions of links between geography related factors (soil, land weather characteristics) and product qualities. A qualitative case study analysis was done for each of the (five) selected Tanzanian origin products investigated with plausible prospects for Tanzania to leapfrog into exports of Geographical Indications products. Framework conditions for producers creating or capturing market value as stewards of cultural and landscape values, environments, and institutional requirements for such creation or capturing to happen, including presence of export opportunities, are discussed. Geographical indication is believed to allow smallholders to create employment and build monetary value, while stewarding local food cultures and natural environments and resources, and increasing the diversity of supply of natural and unique quality products and so contribute to enhanced food security.

Applying Least Absolute Shrinkage Selection Operator and Akaike Information Criterion Analysis to Find the Best Multiple Linear Regression Models between Climate Indices and Components of Cow’s Milk

This study focuses on multiple linear regression models relating six climate indices (temperature humidity THI, environmental stress ESI, equivalent temperature index ETI, heat load HLI, modified HLI (HLI new), and respiratory rate predictor RRP) with three main components of cow’s milk (yield, fat, and protein) for cows in Iran. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Uncertainty estimation is employed by applying bootstrapping through resampling. Cross validation is used to avoid over-fitting. Climatic parameters are calculated from the NASA-MERRA global atmospheric reanalysis. Milk data for the months from April to September, 2002 to 2010 are used. The best linear regression models are found in spring between milk yield as the predictand and THI, ESI, ETI, HLI, and RRP as predictors with p-value < 0.001 and R2 (0.50, 0.49) respectively. In summer, milk yield with independent variables of THI, ETI, and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. This method is suggested for the impact studies of climate variability/change on agriculture and food science fields when short-time series or data with large uncertainty are available.