Water use efficiency and maximizing profitability of grain sorghum production in the Texas Panhandle

The reduction in the availability of irrigation water and the increase in pumping costs resulting from the decline in the Ogallala Aquifer make good management decisions more critical for the survival of the farm firm and the success of the agricultural sector in the Texas Panhandle. Response functions for irrigation and percentage potential evapotranspiration (PET) in the production of grain sorghum are estimated. The response functions are transferred into value product functions and combined with an irrigation energy cost function to determine the profit maximizing irrigation strategy. Three management decision variables; total water available, the level of irrigation and the water to meet crop ET requirements are evaluated. Grain sorghum yield, natural precipitation, irrigation, soil moisture content, potential evapotranspiration, and percent potential evapotranspiration (PET) data, collected over the period from 1998 through 2007 by commercial producers participating in the AgriPartners program are used to estimate the response functions. Results indicate that the optimum level of irrigation increases as the price of sorghum increases and decreases as the price of natural gas increases.Grain sorghum, ET, maximizing profit, irrigation efficiency, input use optimization, water conservation, Ogallala Aquifer, Texas Panhandle., Farm Management, Production Economics, Productivity Analysis, Resource /Energy Economics and Policy, Q12, Q15, Q25, Q32, and Q34,

THE REFORM OF RICE MILLING AND MARKETING IN THE OFFICE DU NIGER: CATALYST FOR AN AGRICULTURAL SUCCESS STORY IN MALI

This chapter focuses on how changes in the rules regarding who could compete in rice milling in the ON combined with technological change in rice production and new macro-economic policies (particularly the CFA franc devaluation) to lead to a transformation of rice production and marketing in the ON. The chapter also pays particular attention to the synergies between technological changes in rice production, the introduction of new marketing and macroeconomic policies, and the evolution of institutions governing rice production in the ON on the transformation of agriculture in this region of Mali.Crop Production/Industries, Marketing,

Performance of Three Sorghum Cultivars under Excessive Rainfall and Waterlogged Conditions in the Sudano-Sahelian Zone of West Africa: A Case Study at the Climate-Smart Village of Cinzana in Mali

Recent climate analyses show trends for increasing precipitation variability with increasing precipitation sums in Mali. The increasing occurrence of temporary intra-seasonal droughts and waterlogging longer than a week demands climate-smart solutions. Research has focused on water deficits since the 1980s. However, besides droughts, waterlogging can restrict productivity of sensitive cash and staple crops as cotton and corn. The year 2019 offered the historically unique opportunity to monitor waterlogging effects with 1088 mm precipitation in the rural commune Cinzanawith an isohyet of 681 mm. Impacts of two extreme downpours on three sorghum cultivars were monitored in a farmers-field experiment with three replications. All sorghum cultivars performed well in 2019 with significantly higher grain and above ground biomass yields than in the reference year 2007, with well distributed rainfall in Cinzana. “Jakumbè” (CSM63E) produced significantly higher grain yields than the hybrid cultivar “PR3009B” bred for high harvest index. The local cultivar “Gnofing” selected by local farmers produced significantly higher above ground biomass. All cultivars tolerated without severe stress symptoms 20 days waterlogging and 72 h inundation. Further waterlogging resilience research of other crops and other sorghum cultivars is needed to strengthen food security in Mali with expected increasing precipitation variation in the future

SMART: Unique splitting-while-merging framework for gene clustering

Copyright @ 2014 Fa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Successful clustering algorithms are highly dependent on parameter settings. The clustering performance degrades significantly unless parameters are properly set, and yet, it is difficult to set these parameters a priori. To address this issue, in this paper, we propose a unique splitting-while-merging clustering framework, named “splitting merging awareness tactics” (SMART), which does not require any a priori knowledge of either the number of clusters or even the possible range of this number. Unlike existing self-splitting algorithms, which over-cluster the dataset to a large number of clusters and then merge some similar clusters, our framework has the ability to split and merge clusters automatically during the process and produces the the most reliable clustering results, by intrinsically integrating many clustering techniques and tasks. The SMART framework is implemented with two distinct clustering paradigms in two algorithms: competitive learning and finite mixture model. Nevertheless, within the proposed SMART framework, many other algorithms can be derived for different clustering paradigms. The minimum message length algorithm is integrated into the framework as the clustering selection criterion. The usefulness of the SMART framework and its algorithms is tested in demonstration datasets and simulated gene expression datasets. Moreover, two real microarray gene expression datasets are studied using this approach. Based on the performance of many metrics, all numerical results show that SMART is superior to compared existing self-splitting algorithms and traditional algorithms. Three main properties of the proposed SMART framework are summarized as: (1) needing no parameters dependent on the respective dataset or a priori knowledge about the datasets, (2) extendible to many different applications, (3) offering superior performance compared with counterpart algorithms.National Institute for Health Researc

Towards gender-informed adaptation planning in the Sudanian zone of Mali

Understanding the linkages between gender and vulnerability is crucial for proposing sustainable gender-responsive climate-smart solutions. This study compared the vulnerabilities of male (MHHH) and female household heads (FHHH) in the Sudanian zone of Mali using Cinzana in the Segou region as a case study. We used semi-structured questionnaire interviews and focus group discussions for data collection. The questionnaires were randomly administered to 233 household heads (23% women). The Livelihood Vulnerability Index (LVI) method was used to assess vulnerability to climate change. The results showed that livelihoods in the Sudanian zone of Mali are vulnerable to climate change. Female household heads (FHHH) were found to be more vulnerable. FHHH recorded higher values for six out of the eight LVI major components used in the vulnerability assessment: socio-demographic index, livelihood strategies index, social network index, food index, natural disasters and climate variability index and agricultural production system index. The study proposes a number of interventions for improving the adaptive capacity of FHHH to climate change and variability: improving access to financial resources, improving access to radio for receiving weather information, encouraging FHHHs involvement in farmer-based groups for peer-learning; and promoting the development of policy initiatives that ensure the mainstreaming of gender into agricultural development programs

A repurposing strategy for Hsp90 inhibitors demonstrates their potency against filarial nematodes

Novel drugs are required for the elimination of infections caused by filarial worms, as most commonly used drugs largely target the microfilariae or first stage larvae of these infections. Previous studies, conducted in vitro, have shown that inhibition of Hsp90 kills adult Brugia pahangi. As numerous small molecule inhibitors of Hsp90 have been developed for use in cancer chemotherapy, we tested the activity of several novel Hsp90 inhibitors in a fluorescence polarization assay and against microfilariae and adult worms of Brugia in vitro. The results from all three assays correlated reasonably well and one particular compound, NVP-AUY922, was shown to be particularly active, inhibiting Mf output from female worms at concentrations as low as 5.0 nanomolar after 6 days exposure to drug. NVP-AUY922 was also active on adult worms after a short 24 h exposure to drug. Based on these in vitro data, NVP-AUY922 was tested in vivo in a mouse model and was shown to significantly reduce the recovery of both adult worms and microfilariae. These studies provide proof of principle that the repurposing of currently available Hsp90 inhibitors may have potential for the development of novel agents with macrofilaricidal properties

The Schistosomiasis Control Initiative (SCI): rationale, development and implementation from 2002-2008

Schistosomiasis remains one of the most prevalent parasitic diseases in developing countries. After malaria, schistosomiasis is the most important tropical disease in terms of human morbidity with significant economic and public health consequences. Although schistosomiasis has recently attracted increased focus and funding for control, it has been estimated that less than 20% of the funding needed to control the disease in Africa is currently available. In this article the following issues are discussed: the rationale, development and objectives of the Schistosomiasis Control Initiative (SCI)-supported programmes; the management approaches followed to achieve implementation by each country; mapping, monitoring and evaluation activities with quantifiable impact of control programmes; monitoring for any potential drug resistance; and finally exit strategies within each country. The results have demonstrated that morbidity due to schistosomiasis has been reduced by the control programmes. While challenges remain, the case for the control of schistosomiasis has been strengthened by research by SCI teams and the principle that a national programme using ‘preventive chemotherapy' can be successfully implemented in sub-Saharan Africa, whenever the resources are available. SCI and partners are now actively striving to raise further funds to expand the coverage of integrated control of neglected tropical diseases (NTDs) in sub-Saharan Afric

Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method

BACKGROUND: Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments. However, there are still gaps toward whole-genome functional annotation of genes using the gene expression data. RESULTS: In this paper, we propose a novel technique called Fuzzy Nearest Clusters for genome-wide functional annotation of unclassified genes. The technique consists of two steps: an initial hierarchical clustering step to detect homogeneous co-expressed gene subgroups or clusters in each possibly heterogeneous functional class; followed by a classification step to predict the functional roles of the unclassified genes based on their corresponding similarities to the detected functional clusters. CONCLUSION: Our experimental results with yeast gene expression data showed that the proposed method can accurately predict the genes' functions, even those with multiple functional roles, and the prediction performance is most independent of the underlying heterogeneity of the complex functional classes, as compared to the other conventional gene function prediction approaches

Prioritizing investments for climate-smart agriculture: Lessons learned from Mali

Agricultural productivity and growth in Mali are under threat from erratic rainfall, resulting in more frequent dry years. The national economy is vulnerable to climate change due to 50% of the gross domestic product coming from the agricultural sector and 75% of the population living in rural areas. The Climate-Smart Agriculture (CSA) concept arises from a need to provide innovative solutions towards the complex and integrated goals of increasing yields, improving resilience, and promoting a low emissions agricultural sector. A major challenge for policymakers to operationalize CSA is the identification, valuation (cost-benefit), and subsequent prioritization of climate-smart options and portfolios (groups of CSA options) for investment. This paper presents the process, results, and lessons learned from a yearlong pilot of the Climate-Smart Agriculture Prioritization Framework (CSA-PF) in Mali. Key national and international stakeholders participated in the co-development and prioritization of two CSA portfolios and related action plans for the Malian Sudanese zone. Initial steps towards outcomes of the process include inclusion of prioritized CSA practices in ongoing development projects and prompting discussion of modifications of future calls for agricultural development proposals by regional donors