Organic farming practices increase weed density and diversity over conventional practices: A meta-analysis.

Population growth and climate change challenge our food and farming systems and provide arguments for an increased intensification of agriculture. Organic farming has been seen as a promising option due to its eco-friendly approaches during production. However, weeds are regarded as the major hindrance to effective crop production which varies depending on the type of crop and spacing. Their presence leads to reduced yield, increase in harvest cost and lower the qualities of some produce. Thus, weed management is a key priority for successful crop production. Therefore, we conducted a meta-analysis from published studies to quantify possible differences on weed density, diversity and evenness in organic and conventional farming systems and best intervention for weed management in organic farming system. Data included were obtained from 32 studies where 31 studies with 410 observations were obtained for weed density, 15 studies with 168 observations for diversity, and 5 studies with 104 observations for evenness. Standard deviation of mean was obtained from the studies, log transformed using natural logarithms and the effect size pooled using standardized mean difference (SMD). Publication bias was determined through funnel plot. Results showed that organic farming has significant higher weed density (P < 0.01), diversity (P = 0.01), and evenness (P < 0.05) compared to conventional farming. Despite so, diversified crop rotation has been proved to reduce weed density in organic farming by up to 49 % while maize-bean intercropping decrease densities of Amaranthus ssp, Cyperus ssp and Cammelina ssp compared with monocropping. Use of mulch after one hand weeding was found to control up to 98 % of weeds and use of cover crop between 24 % and 85 % depending on the type of the cover crop. The study results show that organic farming encourages high weed density, diversity and evenness but use of the integrated approaches can help to maintain weed density at a manageable level.

The impact of participatory action research and endogenous integrated soil fertility management on farm-gate dietary outputs in northern Tanzania.

In most developing countries, although agricultural extension and research devolved since 1980s to promote relevance, cost-effectiveness, ownership, and sustainability, participatory action research (PAR) have been run, albeit with limited empirical evidence on their impacts on farmers livelihoods. The study use a three-stage extended regression model (ERM) to estimate the effect PAR and the promoted agronomic practices on crop produce dietary outputs considering potential endogenous engagement, omitted variable bias, reverse causality, endogenous covariates, and factor simultaneity. Using a sample of 607 small family farms with varying levels of research engagement in the Northern Highlands of Tanzania, the study found that PAR was associated with increased farm-gate dietary outcomes: per-capita calories, proteins, and minerals produced by 139, 216, and 143 %, respectively, and consumption of farm-produced minerals by 74-200 %. The organic manure application was associated with increased the dietary outputs by 62-113 % while the application of inorganic fertilizer with increased protein and mineral outputs by 68 and 105 %, respectively. The crop diversification was associated with increased dietary outputs by 11-25 % while pest and diseases control with increased dietary outputs by 12-17 % but with reduced consumption by 13-14 %. Soil and water conservation measures including terracing were associated with decreased dietary outputs. These findings indicate that PAR contributes to nutritional outcomes of smallholder farmers contingent on the promotion of low-cost input sources and crop diversification which can be leveraged to inform upscaling of participatory policies, strategies, and technologies.

Estimating nutrient concentrations and uptake in rice grain in sub-Saharan Africa using linear mixed-effects regression.

Context or problem: Quantification of nutrient concentrations in rice grain is essential for evaluating nutrient uptake, use efficiency, and balance to develop fertilizer recommendation guidelines. Accurate estimation of nutrient concentrations without relying on plant laboratory analysis is needed in sub-Saharan Africa (SSA), where farmers do not generally have access to laboratories. Objective or research question: The objectives are to 1) examine if the concentrations of macro- (N, P, K, Ca, Mg, S) and micronutrients (Fe, Mn, B, Cu) in rice grain can be estimated using agro-ecological zones (AEZ), production systems, soil properties, and mineral fertilizer application (N, P, and K) rates as predictor variables, and 2) to identify if nutrient uptakes estimated by best-fitted models with above variables provide improved prediction of actual nutrient uptakes (predicted nutrient concentrations x grain yield) compared to average-based uptakes (average nutrient concentrations in SSA x grain yield). Methods: Cross-sectional data from 998 farmers' fields across 20 countries across 4 AEZs (arid/semi-arid, humid, sub-humid, and highlands) in SSA and 3 different production systems: irrigated lowland, rainfed lowland, and rainfed upland were used to test hypotheses of nutrient concentration being estimable with a set of predictor variables among above-cited factors using linear mixed-effects regression models. Results: All 10 nutrients were reasonably predicted [Nakagawa's R2 ranging from 0.27 (Ca) to 0.79 (B), and modeling efficiency ranging from 0.178 (Ca) to 0.584 (B)]. However, only the estimation of K and B concentrations was satisfactory with a modeling efficiency superior to 0.5. The country variable contributed more to the variation of concentrations of these nutrients than AEZ and production systems in our best predictive models. There were greater positive relationships (up to 0.18 of difference in correlation coefficient R) between actual nutrient uptakes and model estimation-based uptakes than those between actual nutrient uptakes and average-based uptakes. Nevertheless, only the estimation of B uptake had significant improvement among all nutrients investigated. Conclusions: Our findings suggest that with the exception of B associated with high model EF and an improved uptake over the average-based uptake, estimates of the macronutrient and micronutrient uptakes in rice grain can be obtained simply by using average concentrations of each nutrient at the regional scale for SSA. Implications: Further investigation of other factors such as the timing of fertilizer applications, rice variety, occurrence of drought periods, and atmospheric CO2 concentration is warranted for improved prediction accuracy of nutrient concentrations.

Maize grain yield and grain zinc concentration response to zinc fertilization: A meta-analysis.

Zinc deficiency in agricultural soils is a current global agroecosystems challenge. Maize exhibits elevated susceptibility to Zn deficiency and low response to zinc fertilization. As a result, there are contradicting literature reports on the crop response to zinc fertilization. This meta-analysis synthesized the current evidence on maize response to zinc fertilization from different studies and highlighted the potential innovations to improve the crop response to zinc application. Systematic literature searches were conducted on the Web of Science and Google Scholar for peer-reviewed publications. From the selected publications, data extracted were maize grain yield and maize grain zinc concentration. The meta-analysis was conducted in R statistical environment using the metafor package. The ratio of means was the chosen effect size measure used. The assessment of effect size heterogeneity showed that the study effect sizes were significantly heterogeneous and also publication bias was evident. The analysis showed 17% and 25% maize grain yield and grain zinc concentration response to zinc fertilization. As a result, zinc fertilization was associated with yield increments of up to 1 t ha-1 and 7.19 mg kg-1 grain zinc concentration over the control (no zinc application). Despite the observed maize grain response to zinc application, the median concentration of grain Zn was below the 38 mg kg-1 recommended maize grain zinc concentration to combat human zinc deficiency (hidden hunger). As a result, potential innovations likely to achieve sufficient maize grain zinc content were highlighted including the use of nano-particulate zinc oxide, foliar zinc application, timing of zinc application, precision fertilization and zinc micro-dosing. Due to scanty literature on the progress of these innovations in maize, follow-up studies are recommended to evaluate their potential success in the agronomic bio-fortification of maize with zinc.

Understanding variability in crop response to fertilizer and amendments in sub-Saharan Africa.

Improved understanding of soil fertility factors limiting crop productivity is important to develop appropriate soil and nutrient management recommendations in sub-Saharan Africa. Diagnostic trials were implemented in Kenya, Malawi, Mali, Nigeria and Tanzania, as part of the African Soils Information Service (AfSIS) project, to identify soil fertility constraints to crop production across various cropping systems and soil fertility conditions. In each country, one to three sites of 10 km × 10 km were included with each site having 12-31 field trials. The treatments tested included a control, an NPK treatment, three treatments in which the N, P and K nutrients were omitted one at a time from the NPK treatment, and three treatments in which secondary and micronutrients (Ca, Mg, S, Zn and B) simply referred here as multi-nutrients, manure and lime were added to the NPK. The field trials were conducted for 1-2 seasons; the test crop was maize except in Mali where sorghum was used. Nitrogen was limiting in all sites and generally the most limiting nutrient except in Sidindi (Kenya) and Kontela (Mali) where P was the most limiting. The general pattern in Kiberashi (Tanzania) shows none of the nutrients were limiting. K is mainly limiting in only one site (Mbinga) although incidences of K limitation were seen in almost all sites. Addition of multi-nutrients and manure further improved the yields of NPK in most sites. Cluster analyses revealed that maize crop in 11% of fields were highly responsive to nitrogen application, 25% (i.e., 21% poor and 4% fertile) 'non-responsive' to any nutrient or soil amendment, 28% being 'low responsive' and 36% of 'intermediate response'. This study indicates that constraints to crop production vary considerably even within a site, and that addressing limitations in secondary and micronutrients, and increasing soil carbon can improve response to fertilizers. For sustainable crop production intensification in smallholder farming systems in SSA, there is need to develop management strategies to improve efficiency of fertilizer use and of other inputs, recognizing the site-specific nutrient response patterns at various spatial scales.

Soil climate and decomposer activity in Sub-Saharan Africa estimated from standard weather station data: a simple climate index for soil carbon balance calculations.

Soil biological activity was calculated on a daily basis, using standard meteorological data from African weather stations, a simple soil water model, and commonly used assumptions regarding the relations between temperature, soil water content, and biological activity. The activity factor r(e_clim) is calculated from daily soil moisture and temperature, thereby taking the daily interaction between temperature and moisture into account. Annual mean r(e_clim) was normalized to 1 in Central Sweden (clay loam soil, no crop), where the original calibration took place. Since soils vary in water storage capacity and plant cover will affect transpiration, we used this soil under no crop for all sites, thereby only including climate differences. The Swedish r(e_clim) value, 1, corresponds to ca. 50% annual mass loss of, e.g., cereal straw incorporated into the topsoil. African mean annual r(e_clim) values varied between 1.1 at a hot and dry site (Faya, Chad) and 4.7 at a warm and moist site (Brazzaville, Congo). Sites in Kenya ranged between r(e_clim) = 2.1 at high altitude (Matanya) and 4.1 in western Kenya (Ahero). This means that 4.1 times the Swedish C input to soil is necessary to maintain Swedish soil carbon levels in Ahero, if soil type and management are equal. Diagrams showing daily r(e_clim) dynamics are presented for all sites, and differences in within-year dynamics are discussed. A model experiment indicated that a Swedish soil in balance with respect to soil carbon would lose 41% of its soil carbon during 30 y, if moved to Ahero, Kenya. If the soil was in balance in Ahero with respect to soil carbon, and then moved to Sweden, soil carbon mass would increase by 64% in 30 y. The validity of the methodology and results is discussed, and r(e_clim) is compared with other climate indices. A simple method to produce a rough estimate of r(e_clim) is suggested.