Intercropping agriculture with legume trees is a promising strategy to improve soils with low soil organic matter (SOM) and nitrogen (N) contents, which is a common problem in many Southern African regions. Objective of this research was to explore long-term effects of legume-intercropping on SOM pools and soil fertility. We examined a maize-based cropping system with gliricidia (Gliricidia sepium) as intercropping legume tree on a Ferric Lixisol in Southern Malawi. The experimental trial at Makoka Research Station was in its 29th year of management with leaf biomass incorporated into the soil regularly. We determined concentrations of organic carbon (C) and N, exchangeable cations, and available phosphorus (P) of topsoil samples (0–20 cm). We used density fractionation of SOM to gain fractions that roughly approximate SOM pools with fast turnover (not associated to soil minerals), intermediate turnover (occluded within soil aggregates) and slow turnover (mineral associated SOM). We further determined water dispersible clay (WDC) and pedogenic oxides, as these are often involved in the C-stabilization process in tropical soils. Maize-gliricidia intercropping plots showed higher soil pH-values, and higher concentrations of exchangeable Mg and Ca than plots with maize monoculture. In addition, significantly higher contents of C (17.3 vs. 7.03 g kg−1) and N (1.51 vs. 0.7 g kg−1) were found at intercropping plots indicating a C-sequestration rate of 0.3 g C kg−1 a−1, while monoculture induced the loss of SOM with a rate of −0.1 g C kg−1 a−1. C and N contents doubled in pools with fast and with slow turnover and increased by >300% in SOM pool where C and N is bound in soil aggregates. Concomitantly, WDC was significantly lower in intercropping plots than in monoculture plots. Our data emphasize the fast turnover of SOM in subtropical soils and indicate that SOM in arable soils decreases continuously without suitable C-input strategy. Maize-gliricidia intercropping had positive effects on biomass production and C-input at Makoka Research Station and improved soil fertility. In addition, aggregate formation was enhanced and storage of SOM within aggregates and at mineral surfaces increased. Our results indicate a great potential of maize-gliricidia intercropping for improved C management in subtropical Lixisols. Intensive monitoring seems to be promising to validate and quantify the impacts of this measure.
Tag: Maize
Combined application of the EM-DEA and EX-ACT approaches for integrated assessment of resource use efficiency, sustainability and carbon footprint of smallholder maize production practices in sub-Saharan Africa
The goal to improve food security in sub-Saharan Africa (SSA) through domestic, resource efficient and low carbon agriculture is importance. Interventions to produce more food could impact the resource-base and lead to increase in greenhouse gas (GHG) emissions from agroecosystems. Unfortunately, existing methods are limited in analyzing small-scale agricultural systems, and this situation is an obstacle to decision making which aims at sustainable agriculture. In this paper, we showcase the recently developed Emergy-Data Envelopment Analysis (EM-DEA) approach to assess the resource use efficiency (RUE) and sustainability in maize production systems in Ghana, SSA. Using the Agricultural Production Systems sIMulator (APSIM), five land use and resource management scenarios were modeled to represent practices as decision making units (DMUs) in small-scale maize systems. The carbon footprint of the systems was assessed using an approach, which we adapted from the FAO Ex-Ante Carbon balance Tool (EX-ACT). The overall trend of the results showed that the yield, total emergy, GHG emissions and carbon footprint all increased with increase in urea application intensity. However, the relationship between the yield and urea intensity was not always linear. A system that used more renewable or fewer resources to produce a yield equal to that of its peer was considered more efficient and sustainable in relative terms. In particular, the business-as-usual scenario (12 kg/ha/yr NPK input to rainfed maize system, i.e. Extensive12) was inefficient when compared to the four contrasting scenarios. The ecological intensive scenario (20 kg/ha/yr urea input to rainfed maize-legume intercropping system, i.e. Intercrop20) achieved the greatest marginal yield, better RUE and sustainability. The high input scenario (100 kg/ha/yr urea input plus supplemental irrigation to maize monoculture, i.e. Intensive100) produced the greatest yield, but the demand for purchased inputs as well as GHG emissions and carbon footprint were greatest. The no external input scenario (0 kg/ha/yr urea input to rainfed maize system, i.e. Extensive0), and the moderate input scenario (50 kg/ha/yr urea input plus supplemental irrigation to maize monoculture, i.e. Intensive50) showed the greatest and least yield gaps relative to Intensive100, respectively. Based on these results and trade-off analysis, it was evident that Intercrop20 and Intensive50 were the two best case scenarios. As such, land use policy that aims at sustainable agriculture could recommend Intercrop20 and Intensive50 for implementation in low and high input maize production systems, respectively. Comparison between our results and other existing empirical studies revealed similarities that confirm our results. We conclude that the information derived using the EM-DEA and EX-ACT approaches could be useful when making informed decisions that aim at sustainable agriculture. Despite the limitation caused by scarcity of data, the use of the EM-DEA approach led to inclusive information on RUE and sustainability of the DMUs. Hence, the EM-DEA approach represents a way forward to better assess energy footprint in agricultural land use as a whole.
The effects of agroecological farming systems on smallholder livelihoods: a case study on push–pull system from Western Kenya
There is a need for scaling-up agroecology to promote sustainable agriculture at global level. Although, recent studies show that agroecological approaches can achieve both high yields and profits compared with conventional systems, the performance of other socioeconomic indicators remains unknown. This study has two objectives (i) identify the main characteristics of small-scale producers who represent the target-groups of the SDG 2; (ii) provide a comparison between push–pull and conventional farming systems of maize production to explore and possibly implement sustainable systems. In collaboration with Biovision Africa Trust, a participatory assessment framework was implemented in Western Kenya. Twenty-three farmers were selected and data were analysed showing that the push–pull contributes to social/cultural and natural/ecological capitals. In particular, push–pull farmers are more focused on socially oriented groups (75%); moreover, they cultivate smaller plots (1.9 ha) compared to conventional farmers (3.1 ha) without showing a reduction in profitability. The benefits of adopting push–pull system indicated by farmers (e.g. diminished Striga weed) are consistent with the advantages reported in relevant scientific literature. Considering the explorative nature of this study, the article makes a key contribution by pointing towards important questions for future research on agroecology in Sub-Saharan African countries.
Plot-Scale Agroforestry Modeling Explores Tree Pruning and Fertilizer Interactions for Maize Production in a Faidherbia Parkland
Poor agricultural productivity has led to food shortages for smallholder farmers in Ethiopia. Agroforestry may improve food security by increasing soil fertility, crop production, and livelihoods. Agroforestry simulation models can be useful for predicting the effects of tree management on crop growth when designing modifications to these systems. The Agricultural Production Systems sIMulator (APSIM) agroforestry tree-proxy model was used to simulate the response of maize yield to N fertilizer applications and tree pruning practices in the parkland agroforestry system in the Central Rift Valley, Ethiopia. The model was parameterized and tested using data collected from an experiment conducted under trees and in crop-only plots during the 2015 and 2016 growing seasons. The treatments contained three levels of tree pruning (100% pruned, 50% pruned, and unpruned) as the main plots, and N fertilizers were applied to maize at two rates (9 or 78 kg N ha−1) as sub-plots. Maize yield predictions across two years in response to tree pruning and N applications under tree canopies were satisfactorily simulated (NSE = 0.72, RSR = 0.51, R2 = 0.8). Virtual experiments for different rates of N, pruning levels, sowing dates, and cultivars suggest that maize yield could be improved by applying fertilizers (particularly on crop-only plots) and by at least 50% pruning of trees. Optimal maize yield can be obtained at a higher rate of fertilization under trees than away from them due to better water relations, and there is scope for improving the sowing date and cultivar. Across a 34-year range of recent climate, small increases in yields due to optimum N-fertilizing and pruning were probably limited by nutrient limitations other than N, but the highest yields were consistently in the 2–4 m zone under trees. These virtual experiments helped to form hypotheses regarding fertilizers, pruning, and the effects of trees on soil that warrant further field evaluation.
Critical slope length for soil loss mitigation in maize-bean cropping systems in SW Kenya
Soil erosion and land fragmentation threaten agricultural production of sub-Saharan African highlands. At our study site in Western Kenya, farm size is mostly < 2 ha, laid out in narrow strips in slope direction and ploughed downhill. Soil conservation measures like hedgerows and green manures can reduce effective slope length for erosion, but compete with crops for space and labour. Knowledge of critical slope length can minimise interventions and trade–offs. Hence, a maize–bean intercrop (MzBn) slope length trial on 20, 60 and 84 m long plots, replicated twice on three farms was carried out in Rongo, Migori County, during one rainy season. Soil loss from 84 m slope length (SL) plots was 250 % higher than from 60 m and 710% higher than from 20 m plots, while soil loss from 20 and 60 m plots did not differ (p < 0.05). Conversely, runoff was lower on the 84 m than on the 60 m (p < 0.05) or the 20 m SL (p < 0.05). Across all three farms slope gradient and length had highest explanatory power to predict soil loss. At individual farm level, under similar slope and soil texture, slope length and profile curvature were most influential. Regarding results of the slope length experiments, food crop plot lengths < 50 m appear essential considering soil loss, sediment load, and soil loss to yield ratio under the given rainfall, soil and slope (10–14%) conditions. Our results call for designing integrating slope length options and cropping systems for effective soil conservation. We recommend planting Mucuna and Calliandra–hedgerows as buffer strips below the critical slope length, and legume cash crops and maize uphill. Such approaches are critical against the backdrop of land fragmentation and labour limitation to sustainably maximise food production from the available land area in the region.
Maize production and environmental costs: Resource evaluation and strategic land use planning for food security in northern Ghana by means of coupled emergy and data envelopment analysis
This paper applies an integrated methodology which is constituted of the following: (i) the Emergy-Data Envelopment Analysis (EM-DEA), (ii) environmental Cost-Benefit Analysis (CBA), (iii) Value Chain Analysis (VCA), and (iv) Sustainability Balanced Scorecard (SBSC) approaches, -to support multicriteria decision analysis (MCDA) for strategic agricultural land use planning, which could contribute to improve food security in northern Ghana. Five scenarios of land use and resource management practices for maize production were modelled. The business-as-usual scenario was based on primary data, which were collected using semi-structured questionnaires administered to 56 small-scale maize farmers through personal interviews. The dominant land use was characterised by an external input =12 kg/ha/yr inorganic fertilizer with/without the addition of manure in rainfed maize systems. The project scenarios were based on APSIM simulations of maize yield response to 0, 20, 50 and 100 kg/ha/yr urea dosages, with/without supplemental irrigation. The scenarios were dubbed as follows: (1) no/low input systems were denoted by Extensive0, Extensive12, and Intercrop20, and (2) moderate/high input systems were denoted by Intensive50, and Intensive100. The EM-DEA approach was used to assess the resource use efficiency (RUE) and sustainability in maize production systems, Ghana. The measured RUE and sustainability were used as a proxy for further analyses by applying the environmental CBA and VCA approaches to calculate: (a) the environmental costs of producing maize, i.e. resource use measured as total emergy (U), and (b) benefits from the yielded maize, i.e. (b i) food provision from grain measured in kcal/yr, and (b ii) potential electricity (bioenergy) which could be generated from residue measured in MWh/yr. The information which was derived from the applications of the EM-DEA, CBA and VCA approaches was aggregated by applying the SBSC approach to do a sustainability appraisal of the scenarios. The results show that, when labour and services are included in the assessment of RUE and sustainability, Intercrop20 and Intensive50 achieved greater marginal yield, better RUE, sustainability and appraisal score. The same scenarios caused lesser impacts in terms of expansion of area cultivated compared to Extensive0 and Extensive12. Meanwhile the impacts of Intercrop20 and Intensive50 in terms of ecotoxicity, emissions, and demand for resources (energy, materials, labour and services) were lesser compared to Intensive100. The implications of the various scenarios are discussed. The environmental performance of the scenarios are compared to maize production systems in other developing regions in order to put this study within a broader context. We conclude that, the EM-DEA approach is useful for assessing RUE and sustainability of agricultural production systems at farm and regional scales, as well as in connecting the management planning level and regional development considerations.
Soil and management-related factors contributing to maize yield gaps in western Kenya
The solution to reducing existing yield gaps on smallholder farms lies in understanding factors limiting yield in areas with agricultural intensification potential. This study applied an integrated analysis approach comprising Classification and Regression Tree (CART), generalized linear mixed model (GLMM), and factor analysis (FA), to explain soil and management-related factors influencing maize yield gaps, in order to enhance yields. The study was conducted in Mukuyu and Shikomoli in western Kenya, sites with, respectively, high and low agroecological potential regarding soil fertility. Maize yield gaps were quantified by comparing yields on the 90th percentile of farms to yields determined in 189 fields on 70 randomly sampled smallholdings. Soil and management-related factors were determined at early and late maize development stages. Maize yield on the 90th percentile of farms in Mukuyu and Shikomoli was 5.1 and 4.8 t/ha, respectively, and the average yield gap was 1.8 and 2.6 t/ha, representing 35% and 54% unachieved yield for Mukuyu and Shikomoli, respectively. In FA, soil was revealed to be the main factor influencing maize yield gaps at both sites, rather than management-related variables. The CART method identified maize density, chlorophyll values, maize height, and depth to compact layer as consistent factors affecting yield at both sites, while GLMM identified soil texture (silt content) as important. According to CART, weed cover at early stages and maize density at late stages were the most limiting factor in maize production in Mukuyu and Shikomoli, respectively. Generalized linear mixed model analysis identified agroecology-specific factors influencing maize yield gaps as soil-available phosphorus and zinc, plus weed pressure at early maize stages in Mukuyu, and plus soil cation exchange capacity and exchangeable magnesium in Shikomoli. Through an integrated approach, it was possible to identify both consistent and agroecology-specific factors limiting crop yields. This can increase the applicability of the findings to smallholder farms.
Determinants of maize farmers market participation in Southern Ethiopia: Emphasis on demographic, socioeconomic and institutional factors
Maize is the main cereal crop that supports the livelihoods of millions of smallholder farmers in Africa. However, one of the main bottlenecks for maize production is low market penetration. This study examined the factors influencing the likelihood of smallholder farmers taking part in maize trading in southern Ethiopia using cross-sectional data collected from 360 smallholder maize growers. The data were examined with inferential statistics and the Heckman two-stage sample selection econometric model. Household head age and sex, maize price, household size, farm experience, market distance, access to transportation, frequency of extension contact, land size, amount of credit received, market information, and off-farm income were all found to be significant factors that determine maize farmers’ market participation. Investment in road infrastructure in maize production potential areas and access to market information is mainly needed to increase maize trading.