Leguminous cover crops differentially affect maize yields in three contrasting soil types of Kakamega, Western Kenya

Maize production in smallholder farming systems in Kenya is largely limited by low soil fertility. As mineral fertilizer is expensive, green manuring using leguminous cover crops could be an alternative strategy for farmers to enhance farm productivity. However due to variability in soil type and crop management, the effects of green manure are likely to differ with farms. The objectives of this study were to evaluate Mucuna pruriens and Arachis pintoi on (i) biomass and nitrogen fixation (^15N natural abundance), (ii) soil carbon and nitrogen stocks and (iii) their effects on maize yields over two cropping seasons in Kakamega, Western Kenya. Mucuna at 6 weeks accumulated 1–1.3 Mg ha^{-1} of dry matter and 33–56 kg ha^{-1} nitrogen of which 70% was nitrogen derived from the atmosphere (Ndfa). Arachis after 12 months accumulated 2–2.7 Mg ha^{-1} of dry matter and 51–74 kg N ha^{-1} of which 52-63 % was from Ndfa. Soil carbon and nitrogen stocks at 0–15 cm depth were enhanced by 2-4 Mg C ha^{-1} and 0.3–1.0 Mg N ha^{-1} under Mucuna and Arachis fallow, irrespective of soil type. Maize yield increased by 0.5-2 Mg ha^{-1} in Mucuna and 0.5–3 Mg ha^{-1} in Arachis and the response was stronger on Nitisol than on Acrisol or Ferralsol. We concluded that leguminous cover crops seem promising in enhancing soil fertility and maize yields in Kenya, provided soil conditions and rainfall are suitable.

Effects of Tithonia diversifolia, farmyard manure and urea, and phosphate fertiliser application methods on maize yields in western Kenya

Maize production in western Kenya is often limited by deficiencies of nitrogen and phosphorus. We assessed the effectiveness of Tithonia diversifolia green manure (tithonia), farmyard manure (FYM) and urea as sources of nitrogen (N) for maize when inorganic phosphorus (P) fertiliser was either broadcast (BR) or spot-placed in the planting hole (SP) for two consecutive seasons; October to December of 1998 and April to August of 1999 at two sites; Nyabeda and Khwisero in western Kenya. A randomised complete block design with four replications was used. Maize yields were higher at Nyabeda and responded to P application better than at Khwisero. At the same N rate, tithonia and FYM were as effective as urea in increasing maize yields at both sites. There were no significant differences in maize yields when phosphate fertiliser was either BR or SP regardless of the N source used in the first season. However, in the second season, the residual yields for the BR treatments were consistently higher than those of the SP. Our results suggest that tithonia and FYM can substitute for urea as N sources and that fertiliser P should be broadcast and incorporated together with the organic materials at the time of planting to save on labour costs.

Predicting the effects of nitrogen and planting density on maize water use in semi-arid Kenya

Models are important tools to assess the scope of management effects on crop productivity under different climatic and soil regimes. Accordingly, this study developed and used a simple model to assess the effects of nitrogen fertiliser and planting density on the water use efficiency (q) of maize in semi-arid Kenya. Field experiments were undertaken at Sonning, Berkshire, UK, in 1996 (one sowing) and 1997 (two sowings). The results from the field experiments plus soil and weather data for Machakos, Kenya (1 degree 33'S, 37 degree 14'E and 1560 m above sea level), were then used to predict the effects that N application and planting density may have on water use by a maize crop grown in semi-arid Kenya. The increase in q due to N application was greater under irrigated (15%-19%) than rainfed (7%-8%) conditions. Also, high planting density increased q (by 13%) under irrigation but decreased q (by 17%) under rainfed conditions. The current study has shown the significance of crop modelling techniques in assessing the influence of N and planting density on maize production in one region of semi-arid Kenya where there is high variability of rainfall.

The socioeconomics of food crop production and climate change vulnerability: a global scale quantitative analysis of how grain crops are sensitive to drought

Many studies warn that climate change may undermine global food security. Much work on this topic focuses on modelling crop-weather interactions but these models do not generally account for the ways in which socio-economic factors influence how harvests are affected by weather. To address this gap, this paper uses a quantitative harvest vulnerability index based on annual soil moisture and grain production data as the dependent variables in a Linear Mixed Effects model with national scale socio-economic data as independent variables for the period 1990-2005. Results show that rice, wheat and maize production in middle income countries were especially vulnerable to droughts. By contrast, harvests in countries with higher investments in agriculture (e.g higher amounts of fertilizer use) were less vulnerable to drought. In terms of differences between the world's major grain crops, factors that made rice and wheat crops vulnerable to drought were quite consistent, whilst those of maize crops varied considerably depending on the type of region. This is likely due to the fact that maize is produced under very different conditions worldwide. One recommendation for reducing drought vulnerability risks is coordinated development and adaptation policies, including institutional support that enables farmers to take proactive action.

Simulating maize yield in sub-tropical conditions of southern Brazil using Glam model

The objective of this work was to evaluate the feasibility of simulating maize yield in a sub‑tropical region of southern Brazil using the general large area model (Glam). A 16‑year time series of daily weather data were used. The model was adjusted and tested as an alternative for simulating maize yield at small and large spatial scales. Simulated and observed grain yields were highly correlated (r above 0.8; p<0.01) at large scales (greater than 100,000 km2), with variable and mostly lower correlations (r from 0.65 to 0.87; p<0.1) at small spatial scales (lower than 10,000 km2). Large area models can contribute to monitoring or forecasting regional patterns of variability in maize production in the region, providing a basis for agricultural decision making, and Glam‑Maize is one of the alternatives.

Weed interference on maize (Zea mays) under no tillage system

A field trial was carried out in Brazil in March 2002 with the aim to evaluate the effects of different timing and extension of weedy period on maize productivity. The hybrid Pioneer 30K75 was sowed under 7 t ha(-1) mulching promoted by glyphosate spraying. The treatments were divided in two groups: In the first group, weeds were maintained since the maize sowing until different periods in the crop cycle: 0, 14, 28, 42, 56, 70, and 150 days (harvesting time). In the second group, the maize crop was kept weed free for the same periods of the first group. Weed control was done through hand hoeing. A complete randomized blocks experimental design with five replications was used for plots distribution in the field. Nonlinear regression model was used to study the effects of weedy or weedfree periods on maize productivity. Weed community included 13 families and 31 species. Asteraceae, Poaceae, and Euphorbiaceae were the most abundant families. Results showed that under no tillage condition with 7 t ha-1 mulching at sowing time, the maize crop could cohabit with weed community for 54 days without any yield lost. on the other hand, if the crop was kept weed free for 27 days, the weed interference was not enable to reduce maize production. According to these results one weed control measure between 27 and 54 days after crop emergence could be enough to avoid any reduction in maize productivity.

Productivity, Leaf Nutrient Content and Soil Carbon Stocked in Agroforestry and Traditional Management of Maize (Zea mays L.)

The aim of the work was to evaluate the productivity, leaf nutrient content and soil nutrient concentration in maize (Zea mays L.) grown in sequence with black oats (Avena strigosa Schreb.) under Leucaena diversifolia alley cropping agroforestry system (AFS) and traditional management system/sole crop (without trees-TS), after two years of cultivation following a randomized block design. The experiment was carried out in the Brazilian Association of Biodynamic Agriculture, in Botucatu—S?o Paulo, Brazil. Treatments were: control (C), chemical fertilizer application (F), biomass of L. diversifolia alley cropping application (B), biomass of L. diversifolia alley cropping + chemical fertilizer application (B + F). In the second year of management it was observed that black oat yield was higher in treatments B + F and F with significant difference in relation to the others treatments in both systems, followed by treatment B. Between systems, only treatment B showed significant difference, with higher yield value corresponding to AFS, reflecting the efficiency of AFS to promote soil fertility. Maize production presented the second year of cultivation an increasing trend in all treatments in both production systems. This result may be due to the cumulative effect of mineralization and maize straw and oats, along the experiment. How productivity was higher in the AFS system, could also be occurring effect of biological nitrogen fixation, water retention and reduction of extreme microclimate through the rows of L. diversifolia. Comparing the AFS and TS, it was observed that the concentration of N in leaf tissue was higher in the AFS treatments, probably due to nitrogen fixation performed through the rows of L. diversifolia, that is a nitrogen fixing tree species. After two years, carbon stocked in soil show higher values in the treatments biomass + fertilizer and biomass application, in both systems, AFS and TS.

Yield potential and resource-use efficiency of maize systems in the western U.S. Corn Belt

Maize demand for food, livestock feed, and biofuel is expected to increase substantially. The Western U.S. Corn Belt accounts for 23% of U.S. maize production, and irrigated maize accounts for 43 and 58% of maize land area and total production, respectively, in this region. The most sensitive parameters (yield potential [YP], water-limited yield potential [YP-W], yield gap between actual yield and YP, and resource-use efficiency) governing performance of maize systems in the region are lacking. A simulation model was used to quantify YP under irrigated and rainfed conditions based on weather data, soil properties, and crop management at 18 locations. In a separate study, 5-year soil water data measured in central Nebraska were used to analyze soil water recharge during the non-growing season because soil water content at sowing is a critical component of water supply available for summer crops. On-farm data, including yield, irrigation, and nitrogen (N) rate for 777 field-years, was used to quantify size of yield gaps and evaluate resource-use efficiency. Simulated average YP and YP-W were 14.4 and 8.3 Mg ha-1, respectively. Geospatial variation of YP was associated with solar radiation and temperature during post-anthesis phase while variation in water-limited yield was linked to the longitudinal variation in seasonal rainfall and evaporative demand. Analysis of soil water recharge indicates that 80% of variation in soil water content at sowing can be explained by precipitation during non-growing season and residual soil water at end of previous growing season. A linear relationship between YP-W and water supply (slope: 19.3 kg ha-1 mm-1; x-intercept: 100 mm) can be used as a benchmark to diagnose and improve farmer’s water productivity (WP; kg grain per unit of water supply). Evaluation of data from farmer’s fields provides proof-of-concept and helps identify management constraints to high levels of productivity and resource-use efficiency. On average, actual yields of irrigated maize systems were 11% below YP. WP and N-fertilizer use efficiency (NUE) were high despite application of large amounts of irrigation water and N fertilizer (14 kg grain mm-1 water supply and 71 kg grain kg-1 N fertilizer). While there is limited scope for substantial increases in actual average yields, WP and NUE can be further increased by: (1) switching surface to pivot systems, (2) using conservation instead of conventional tillage systems in soybean-maize rotations, (3) implementation of irrigation schedules based on crop water requirements, and (4) better N fertilizer management.

How do various maize crop models vary in their responses to climate change factors?

Comments This article is a U.S. government work, and is not subject to copyright in the United States. Abstract Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha 1 per °C. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

Characterization of the effect of nitrogen deficiency on above-ground plant phenotypes in relation to root complexity in maize

Nitrogen (N) is an essential plant nutrient in maize production, and if considering only natural sources, is often the limiting factor world-wide in terms of a plant’s grain yield. For this reason, many farmers around the world supplement available soil N with synthetic man-made forms. Years of over-application of N fertilizer have led to increased N in groundwater and streams due to leaching and run-off from agricultural sites. In the Midwest Corn Belt much of this excess N eventually makes its way to the Gulf of Mexico leading to eutrophication (increase of phytoplankton) and a hypoxic (reduced oxygen) dead zone. Growing concerns about these types of problems and desire for greater input use efficiency have led to demand for crops with improved N use efficiency (NUE) to allow reduced N fertilizer application rates and subsequently lower N pollution. It is well known that roots are responsible for N uptake by plants, but it is relatively unknown how root architecture affects this ability. This research was conducted to better understand the influence of root complexity (RC) in maize on a plant’s response to N stress as well as the influence of RC on other above-ground plant traits. Thirty-one above-ground plant traits were measured for 64 recombinant inbred lines (RILs) from the intermated B73 & Mo17 (IBM) population and their backcrosses (BCs) to either parent, B73 and Mo17, under normal (182 kg N ha-1) and N deficient (0 kg N ha-1) conditions. The RILs were selected based on results from an earlier experiment by Novais et al. (2011) which screened 232 RILs from the IBM to obtain their root complexity measurements. The 64 selected RILs were comprised of 31 of the lowest complexity RILs (RC1) and 33 of the highest complexity RILs (RC2) in terms of root architecture (characterized as fractal dimensions). The use of the parental BCs classifies the experiment as Design III, an experimental design developed by Comstock and Robinson (1952) which allows for estimation of dominance significance and level. Of the 31 traits measured, 12 were whole plant traits chosen due to their documented response to N stress. The other 19 traits were ear traits commonly measured for their influence on yield. Results showed that genotypes from RC1 and RC2 significantly differ for several above-ground phenotypes. We also observed a difference in the number and magnitude of N treatment responses between the two RC classes. Differences in phenotypic trait correlations and their change in response to N were also observed between the RC classes. RC did not seem to have a strong correlation with calculated NUE (ΔYield/ΔN). Quantitative genetic analysis utilizing the Design III experimental design revealed significant dominance effects acting on several traits as well as changes in significance and dominance level between N treatments. Several QTL were mapped for 26 of the 31 traits and significant N effects were observed across the majority of the genome for some N stress indicative traits (e.g. stay-green). This research and related projects are essential to a better understanding of plant N uptake and metabolism. Understanding these processes is a necessary step in the progress towards the goal of breeding for better NUE crops.

Assessing the impact of agricultural drought on maize prices in Kenya with the approach of the SPOT-VEGETATION NDVI remote sensing

The high cost of maize in Kenya is basically driven by East African regional commodity demand forces and agricultural drought. The production of maize, which is a common staple food in Kenya, is greatly affected by agricultural drought. However, calculations of drought risk and impact on maize production in Kenya is limited by the scarcity of reliable rainfall data. The objective of this study was to apply a novel hyperspectral remote sensing method to modelling temporal fluctuations of maize production and prices in five markets in Kenya. SPOT-VEGETATION NDVI time series were corrected for seasonal effects by computing the standardized NDVI anomalies. The maize residual price time series was further related to the NDVI seasonal anomalies using a multiple linear regression modelling approach. The result shows a moderately strong positive relationship (0.67) between residual price series and global maize prices. Maize prices were high during drought periods (i.e. negative NDVI anomalies) and low during wet seasons (i.e. positive NDVI anomalies). This study concludes that NDVI is a good index for monitoring the evolution of maize prices and food security emergency planning in Kenya. To obtain a very strong correlation for the relationship between the wholesale maize price and the global maize price, future research could consider adding other price-driving factors into the regression models.

Consórcio de milho e Brachiaria decumbens em diferentes preparos de solo

Preparos conservacionistas e sistemas de produção que visam à maximização sustentável do uso do solo e da água têm surgido como alternativas para regiões caracterizadas por períodos chuvosos relativamente curtos e temperaturas elevadas. O objetivo deste trabalho foi avaliar o sistema de consorciação entre milho e Brachiaria decumbens que melhor se adapte às condições edafoclimáticas da região da Zona da Mata do Estado de Alagoas. Os tratamentos consistiram de um híbrido de milho BRS3150, cultivado nos sistemas: Preparo Convencional, Cultivo Mínimo e Semeadura Direta (BRS3150 consorciado com Brachiaria decumbens). O delineamento utilizado foi o de blocos casualisados com parcelas subdivididas. Amostras de solo foram coletadas para análise química. Também foram avaliados os componentes da produção e produtividade de grãos de milho. Os diferentes preparos do solo e a presença de Brachiaria decumbens, no sistema de consócio com milho, não exerceram influência sobre os componentes da produção. Os resultados analisados permitem concluir que a presença da Brachiaria decumbens interferiu negativamente na produtividade dos grãos de milho, quando cultivado em sistema de consórcio, e as maiores produtividades foram obtidas nos sistemas conservacionistas.

Seleção de progênies de meios-irmãos do composto Isanão VF-1 de milho na safra e safrinha

O aumento significativo da produção de milho na segunda safra no Brasil, principalmente no centro-sul do país, têm estimulado os programas de melhoramento da cultura a selecionar genótipos que sejam adaptáveis às condições climáticas das diferentes épocas de semeadura. Nesse sentido, o objetivo do presente trabalho foi quantificar a interação progênies x épocas de semeadura e verificar seus reflexos no progresso genético com o uso de índice de seleção multivariado para seleção de progênies do Composto Isanão VF-1 de milho. As semeaduras foram realizadas na segunda safra em 2004 e na primeira safra do ano agrícola 2004/05. Foram utilizadas 71 progênies de meios irmãos avaliadas em blocos ao acaso, com três repetições. Os caracteres avaliados foram: altura de plantas, altura de espigas, tombamento, prolificidade e rendimento de grãos. Realizaram-se a decomposição da interação progênies x épocas e foram estimados os ganhos pelo índice de seleção descrito por Mulamba e Mock. Houve predomínio da interação do tipo simples para maioria dos caracteres, exceto para prolificidade, que revelou 86% de interação do tipo complexa. Pelo índice de Mulamba e Mock, os ganhos proporcionais mais adequados para o conjunto de caracteres avaliados foi obtido pelos pesos econômicos atribuídos por tentativas. Os ganhos preditos foram de 1,41, 0,86, -13,03, 9,54 e 16,12% para altura de planta, altura de espiga, tombamento, prolificidade e rendimento de grãos, respectivamente.

Milho e Brachiaria decumbens em sistemas de integração lavoura-pecuária

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