Climate smart crops for food and nutritional security for semi-arid zones of Zimbabwe

Southern Africa smallholder farmers continue to be the most affected by the challengesof climate change and variability. The variability of climate demands the use of avariety of agronomic strategies and crop choices. Traditional drought tolerant cerealcrops such as sorghum and millets are often chosen when drought seasons areanticipated. However, there are certain crops, originating elsewhere, that could help thesmallholder farmers increase diversity of crops that can be grown in changed climates.Trials were conducted to test a basket of known and introduced climate smart crops inthe field. The cereal crops tested were maize, sorghum, pearl and finger millet, andlegumes: tepary bean (Phaseolus acutifolias), cowpea (Vigna unguiculata), Bambaranut (Vigna subterranea), groundnut (Arachis hypogaea) and pigeon pea (Cajanuscajan. A second experiment was conducted to determine the effects of inorganicfertilizer and rhizobium inoculation on the growth and grain yield of field grown teparybean. Both experiments were laid out in a randomized complete block design with threereplications. Due to drought conditions during the growing season, cereal crops couldnot produce grain yield, as there was no grain filling. Despite this, cereal biomass was5t ha-1 for maize, followed by sorghum (1.3t ha-1) and millet (1.2t ha-1). Legume cropsproduced grain with cowpea yielding 568.1kg ha-1 of grain, followed by tepary bean(245.9kg ha-1) and common bean (227kg ha-1). This is important for food, nutrition andhealth security of smallholder communities. Tepary bean inoculated with rhizobiumand had fertilizer applied produced higher grain yield than those without fertilizer orrhizobium inoculant (P≤0.05). In conclusion, resource poor farmers, affected bydrought effects of climate change, can adopt both cereals and legumes climate smartcrops, in order to create food and nutritional security. This is crucial for food andnutritional security of vulnerable households affected by climate change and variability.Key words: tepary bean, climate smart crop, drought, smallholder farmer

Smallholder Farmer Perceptions on Climate Change and Variability: A Predisposition for their Subsequent Adaptation Strategies

Smallholder farmers are facing several climate-related challenges. Projected changes in climate are expected to aggravate the existing challenges. This study was conducted in Chiredzi district, Masvingo, Zimbabwe. The study objective was to examine farmer perceptions on climate variability, current adaptive strategies and establish factors influencing smallholder farmers’ adaptation to climate change. A survey was conducted with 100 randomly selected respondents from four wards. Additionally, data was collected through focus group discussions and key informant interviews. The results showed that farmers perceived that there has been a decrease in annual rainfall and an increase in average temperatures. A linear trend analysis of rainfall and temperature data from 1980 to 2011 corroborated the farmers’ perceptions. Farmers’ adaptation options included adjusting planting dates and crop diversification. Off-farm income has reduced the dependence of the farmers on agriculture. A multinomial regression analysis showed that socioeconomic factors such as gender, age, number of cattle owned, land size and average crop yields influenced farmer adaptation strategies. The study concludes that although farmers are diverse in their socio-economic attributes, they exhibit homogeneous perceptions on changes in climate, which are consistent with observations of empirical climate data. These perceptions help to shape smallholder farmer coping and adaptation strategie

Accurate Binding of Sodium and Calcium to a POPC Bilayer by Effective Inclusion of Electronic Polarization

Binding affinities and stoichiometries of Na+ and Ca2+ ions to phospholipid bilayers are of paramount significance in the properties and functionality of cellular membranes. Current estimates of binding affinities and stoichiometries of cations are, however, inconsistent due to limitations in the available experimental and computational methods. In this work, we improve the description of the binding details of Na+ and Ca2+ ions to a 1-palmitoyl-2-oleoyl-phosphatidylcholine (POPC) bilayer by implicitly including electronic polarization as a mean field correction, known as the electronic continuum correction (ECC). This is applied by scaling the partial charges of a selected state-of-the-art POPC lipid model for molecular dynamics simulations. Our improved ECC-POPC model reproduces not only the experimentally measured structural parameters for the ion-free membrane, but also the response of lipid headgroup to a strongly bound cationic amphiphile, as well as the binding affinities of Na+ and Ca2+ ions. With our new model, we observe on the one side negligible binding of Na+ ions to POPC bilayer, while on the other side stronger interactions of Ca2+ primarily with phosphate oxygens, which is in agreement with the previous interpretations of the experimental spectroscopic data. The present model results in Ca2+ ions forming complexes with one to three POPC molecules with almost equal probabilities, suggesting more complex binding stoichiometries than those from simple models used to interpret the NMR data previously. The results of this work pave the way to quantitative molecular simulations with realistic electrostatic interactions of complex biochemical systems at cellular membranes.Peer reviewe

Building climate change resilience through adaptation in smallholder farming systems in semi-arid Zimbabwe

Purpose This study aimed to determine factors that increase resilience and cause smallholder farmers to adapt better to climate change and vulnerability. Design/methodology/approach In this study, the authors used the vulnerability to resilience model and binary logit model to analyse the factors influencing household decisions to adapt. Findings Households with increased access to climate information through extension services were likely to have better adaptation abilities. It was also shown that younger farmers were likely to adapt to climate change given their flexibility to adopt new techniques and their access and use of modern information and technology. Larger households were found to have higher probability of adapting as most adaptation strategies are labour intensive. Household’s possession of livestock and access to credit significantly enhanced adaptation. However, households with higher farm income have lesser incentives to adapt to because their current farming practices might already be optimum. Research limitations/implications Given that most of the smallholder farmers are vulnerable, such as women-headed households and the elderly, who are labour constrained, there is need for research and development of labour saving technologies to increase resilience to climate change and vulnerability. Originality/value These findings underscore the importance of enabling farmer access to information and better technologies which enable them to increase adaptive capacity and resilience

Contextual vulnerability of rainfed crop-based farming communities in semi-arid Zimbabwe: A case of Chiredzi District

Purpose The purpose of this paper is to assess smallholder farmers’ vulnerability to climate change and variability based on the socioeconomic and biophysical characteristics of Chiredzi District, a region that is susceptible to the adverse effects of climate change and variability. Design/methodology/approach Vulnerability was assessed using the Vulnerability to Resilience and the Climate Vulnerability and Capacity frameworks. Findings The major indicators and drivers of vulnerability were identified as droughts, flash floods, poor soil fertility and out-migration leaving female- and child-headed households. From sensitivity analysis, it was shown that different areas within the district considered different biophysical and socioeconomic indicators to climate change and variability. They also considered different vulnerability indicators to influence the decisions for adaptation to climate change and variability. Originality/value The results of this study indicate that the area and cropping systems are greatly exposed and are sensitive to climatic change stimuli, as shown by the decline in main cereal grain yield. These results also showed that there is a need to define and map local area vulnerability as a basis to recommend coping and adaptation measures to counter climate change hazards

Parallel symbolic state-space exploration is difficult, but what is the alternative?

State-space exploration is an essential step in many modeling and analysis problems. Its goal is to find the states reachable from the initial state of a discrete-state model described. The state space can used to answer important questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a starting point for sophisticated investigations expressed in temporal logic. Unfortunately, the state space is often so large that ordinary explicit data structures and sequential algorithms cannot cope, prompting the exploration of (1) parallel approaches using multiple processors, from simple workstation networks to shared-memory supercomputers, to satisfy large memory and runtime requirements and (2) symbolic approaches using decision diagrams to encode the large structured sets and relations manipulated during state-space generation. Both approaches have merits and limitations. Parallel explicit state-space generation is challenging, but almost linear speedup can be achieved; however, the analysis is ultimately limited by the memory and processors available. Symbolic methods are a heuristic that can efficiently encode many, but not all, functions over a structured and exponentially large domain; here the pitfalls are subtler: their performance varies widely depending on the class of decision diagram chosen, the state variable order, and obscure algorithmic parameters. As symbolic approaches are often much more efficient than explicit ones for many practical models, we argue for the need to parallelize symbolic state-space generation algorithms, so that we can realize the advantage of both approaches. This is a challenging endeavor, as the most efficient symbolic algorithm, Saturation, is inherently sequential. We conclude by discussing challenges, efforts, and promising directions toward this goal

Coulomb Correlations and Pseudo-gap Effects in a Pre-formed Pair Model for the Cuprates

We extend previous work on pre-formed pair models of superconductivity to incorporate Coulomb correlation effects. For neutral systems, these models have provided a useful scheme which interpolates between BCS and Bose Einstein condensation with increasing coupling and thereby describes some aspects of pseudo-gap phenomena. However, charge fluctuations (via the plasmon, $\omega_p$) significantly modify the collective modes and therefore the interpolation behavior. We discuss the resulting behavior of the pseudo-gap and thermodynamic quantities such as $T_c$, $\chi$ and $C_v$ as a function of $\omega_p$.Comment: 4 pages RevTeX, 3 ps figures included (Submitted to Physical Review B August 27, 1996

THE IMPROVED SWEEP METAHEURISTIC FOR SIMULATION OPTIMIZATION AND APPLICATION TO JOB SHOP SCHEDULING

We present an improved sweep metaheuristic for discrete event simulation optimization. The sweep algorithm is a tree search similar to beam search. The basic idea is to run a limited number of partial solutions in parallel and to search for solutions by searching the partial solutions. Traditionally, simulation optimization is carried out by multiple simulation runs executed sequentially. In contrast, the sweep algorithm executes multiple simulation runs simultaneously. It uses branching and pruning simulation models to carry out optimization. We describe new components of the algorithm, such as backtracking and local search. Then, we compare our approach with 13 metaheuristics in solving job shop scheduling benchmarks. Our approach ranks in the middle of the comparison which we regard as a success. The general nature of tree search offers a large array of sequential decision applications for the sweep algorithm, such as resource-constrained project scheduling, traveling salesman, or (real-time) production scheduling.