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Maize Regional On-Farm Variety Trials in Eastern and Southern Africa 2011 and 2012
... Under controlled experimental research, DT maize varieties not only exhibit drought tolerance but are also high yielding, more than most current commercial hybrids (CIMMYT, 2013). For example, on average, DT maize hybrids yield 40% more than commercial checks under drought conditions (Setimela et al., 2014). Therefore, DT maize offers some insurance over mid-season droughts and dry spells and the potential to ensure a substantial maize harvest under mild drought conditions. ...
... This is higher than what has been reported in regional on-farm maize variety trials studies. Setimela et al. ( , 2014 found that DT maize yielded 35-50% and 40% more than the best commercial hybrids, respectively. Our results compare not with the best commercial hybrids but with all other maize varieties that farmers grow, including some old varieties such as R201 and local varieties such as Hickory King. ...
Drought is a huge limiting factor in maize production, mainly in the rain-fed agriculture of sub-Saharan Africa. In response to this threat, drought-tolerant (DT) maize varieties have been developed with an aim to ensure maize production under mild drought conditions. We conducted a study to assess the impact of smallholder farmers' adoption of DT maize varieties on total maize production. Data for the study came from a survey of 200 randomly sampled households in two districts of Chiredzi and Chipinge in southeastern Zimbabwe. The study found that 93% of the households were growing improved maize varieties and that 30% of the sampled households were growing DT maize varieties. Total maize yield was 436.5 kg/ha for a household that did not grow DT maize varieties and 680.5 kg/ha for households that grew DT maize varieties. We control for the endogeneity of the DT adoption variable, by using the control function approach to estimate total maize production in a Cobb–Douglas model. The results show that households that grew DT maize varieties had 617 kg/ha more maize than households that did not grow the DT maize varieties. Given that almost all farmers buy their seeds in the market, a change in varieties to DT maize seeds gives an extra income of US$240/ha or more than nine months of food at no additional cost. This has huge implications in curbing food insecurity and simultaneously saving huge amounts of resources at the household and national levels, which are used to buy extra food during the lean season.
... Drought-tolerant maize varieties exhibit the ability to withstand drought and to produce higher yields compared to other commercial hybrids (Simtowe et al. 2019). According to Setimela et al. (2014), drought-tolerant maize germplasm produces about 40% more output under drought conditions than other commercial varieties. ...
Variability in climate and debility in soil fertility affect agrarian production, especially in subSaharan Africa, and thus threaten food security. This has prompted the seed sector to introduce various varieties of climate-smart maize in Kenya and release them in the market. In contrast, there is little experiential insight into how the adoption of these varieties by small-scale farmers affects their household income. This paper used cross-sectional data to evaluate the implications of climatesmart maize varieties on small-scale farmers’ household income in Embu County in Kenya. The endogenous switching regression model was used to estimate the influence of climate-smart maize adoption on household income. Based on survey data obtained from 550 maize farmers in Embu County, the results show that age, education, land under climate-smart maize varieties, and distance to the market positively influenced the income level of the adopters. The findings further reveal that the decision to adopt the climate-smart maize varieties had a significant positive effect of about 60% on farmers’ household income. It therefore can be concluded from the results that the adopters would gain more from technology adoption. These results recommend policies that stimulate the adoption of current climate-smart varieties, with an emphasis on adoption by youths, to create more jobs and increase household income to reduce poverty among smallholder farmers in Kenya
... New stress tolerant maize varieties can out-yield commercial checks by 50% under on-farm testing conditions (Setimela et al., , 2014. D this, DTMV adoption in Kenya is far from universal (CIMMYT, 2017). ...
Droughts have devastating effects on agricultural productivity and livelihoods, which triggers a quest for adaptation strategies such as the development and deployment of drought tolerant maize varieties (DTMVs). This study examines the scalability of DTMVs in Kenya using household survey data from eight counties. Results show that the 2018 DTMV adoption rate of 26% could be doubled to52% as farmer knowledge constraints are alleviated, could potentially be further increased to 56% if seed access constraints are addressed, and even rise to 60% if seed affordability constraints are lifted. There is heterogeneity in scalability across counties attributable to differences in levels of scaling efforts. The use of electronic media appears to be a key success factor to create awareness about DTMVs but could exclude more marginalized households and communities, which highlights the need for multipronged awareness strategies. Scalability calls for public-private partnerships to foster a sustained supply of seed to the farming communities at competitive prices.
Vulnerable households, often the target for efforts to increase resilience, likely hold beliefs about their ability to control outcomes that make them less likely to invest in new technologies. Locus of control provides one way to elicit these beliefs and can help identify populations requiring additional support prior to widespread adoption of new technologies. This paper presents evidence from a large sample of maize‐producing households in Mozambique and Tanzania. A more external locus of control is strongly associated with lower expected returns to improved maize varieties and a reduced probability of their adoption.
This paper assesses the relative advantage of drought-tolerant (DT) maize, conditional on drought severity, using an unbalanced panel of 4 years of on-farm yield trials and high-resolution precipitation data (10-day measurements at a 0.05° resolution) in Malawi, Zambia, Mozambique and Zimbabwe. Under rain-fed conditions, DT maize yield exceeds that of other varieties: 7 per cent higher yields on average and 15 per cent higher yields under moderate drought stress. While this contrasts with higher estimates measured in controlled trials, it nonetheless represents an economically significant advantage. This study further measures heterogeneity in the relative advantage conditional using conditional quantile analysis.
W.E.Easterling, P.K. Aggarwal, P. Batima, K.M. Brander, L. Erda, S.M. Howden, A. Kirilenko, J. Morton, J.-F. Soussana, J. Schmidhuber and F.N. Tubiello, 2007: Food, fibre and forest products. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, M.L. Parry, O.F. Canziani,
J.P. Palutikof, P.J. van der Linden,C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK, 273-313.
Agronomic experiments are often replicated over time and space to evaluate how treatments perform across a range of environments. of eanalysis of experiments conducted for more than one growing season (years) and/or places (locations) is commonly referred to as analysis of combined experiments. Common analyses of these studies treat some effects as fixed, treat others as random, and usually include interactions between fixed and random effects, which we call mixed interactions. Recommendations for how to treat mixed interactions has changed. In the traditional practice, the effects of interactions between fixed and random effects were assumed to sum to zero within each level of a fixed factor. Contemporary practice considers these effects to be mutually independent.This latter assumption is used to construct F tests by many of the statistical analysis programs that are widely used to analyze data from agronomic experiments but is inconsistent with that used in many previously published studies. The assumptions made about mixed interactions in the analysis of variance can result in very different interpretations and can potentially lead to different conclusions. We address the discrepancy between the analyses that were formerly recommended and those that are currently implemented by popular software programs and provide recommendations for analyzing data from combined experiments. © 2015 by the American Society of Agronomy, 5585 Guilford Road, Madison, WI 53711. All rights reserved.
To develop stable and high-yielding maize (Zea mays L.) hybrids for a diverse target population of environments (TPE), breeders have to decide whether greater gains result from selection across the undivided TPE or within more homogeneous subregions. Currently, CIMMYT subdivides the TPE in eastern and southern Africa into climatic and geographic subregions. To study the extent of specific adaptation to these subregions and to determine whether selection within subregions results in greater gains than selection across the undivided TPE, yield data of 448 maize hybrids evaluated in 513 trials across 17 countries from 2001 to 2009 were used. The trials were grouped according to five subdivision systems into climate, altitude, geographic, country, and yield-level subregions. For the first four subdivision systems, genotype x subregion interaction was low, suggesting broad adaptation of maize hybrids across eastern and southern Africa. In contrast, genotype x yield-level interactions and moderate genotypic correlations between low-and high-yielding subregions were observed. Therefore, hybrid means should be estimated by stratifying the TPE considering the yield-level effect as fixed and appropriately weighting information from both subregions. This strategy was at least 10% better in terms of predicted gains than direct selection using only data from the low- or high-yielding subregion and should facilitate the identification of hybrids that perform well in both subregions.
SA genotype main effect plus genotype × environment interaction (GGE) biplot graphically displays the genotypic main effect (G) and the genotype × environment interaction (GE) of the multienvironment trial (MET) data and facilitates visual evaluation of both the genotypes and the environments. This paper compares the merits of two types of GGE biplots in MET data analysis. The first type is constructed by the least squares solution of the sites regression model (SREG2), with the first two principal components as the primary and secondary effects, respectively. The second type is constructed by Man‐del's solution for sites regression as the primary effect and the first principal component extracted from the regression residual as the secondary effect (SREGM+1). Results indicate that both the SREG2 biplot and the SREGM+1 biplot are equally effective in displaying the “which‐won‐where” pattern of the MET data, although the SREG2 biplot explains slightly more GGE variation. The SREGM+1 biplot is more desirable, however, in that it always explicitly indicates the average yield and stability of the genotypes and the discriminating ability and representativeness of the test environments.
The magnitude and type of genetic variability are of prime importance to breeders in determining whether or not to improve a breeding population and the method to use. The early maturing population, TZE-W Pop DT STR, has gone through three cycles of S 1 recurrent se- lection for improvement for grain yield and Striga resis- tance. Three hundred full-sib families within half-sib groups from cycle 3 of TZE-W Pop DT STR were evaluated under artificial Striga infestation in Ferkéssedougou, Côte d'Ivoire, 2002, and in Mokwa, Nigeria, 2003. Estimates of additive genetic variances were positive and moderate-to-large for all traits except lodging percentage. The additive genetic variance was much larger than the dominance variance for all traits except Striga emergence count. The dominance variance for Striga emergence was about twice as large as additive genetic variance at 8 WAP and about four times as large at 10 WAP. Narrow sense heritability (h2) estimate was 25% for grain yield and 0-90% for 13 other traits. The wide ranges, moderate-to-large additive genetic variance and ex- pected gain/cycle of selection, and moderately low-to-high narrow sense heritability estimates observed in TZEE-W Pop DT STR C 3 indicate that sufficient residual genetic vari- ability still exists in the population to allow further im- provement for grain yield, Striga resistance, and most other traits in the population. A wide range of genetic variation was observed among the full-sib families from TZE-W Pop DT STR C 3 in Striga emergence count and Striga damage rating and several progenies were identified that combined reduced Striga emergence and Striga damage implying that it should be possible to extract from the population experi- mental varieties that combine both low Striga emergence and Striga damage. Grain yield had a large positive additive genetic correlation with EPP, a large negative genetic corre- lation with Striga damage ratings, and moderately large negative genetic correlations with flowering traits and Stri- ga emergence count at 10 WAP.
This book examines future technological and policy prospects for the sustainable intensification of rainfed upland maize production in Asia, and derives R&D priorities for specific maize production environments and markets. Village-level and farmer-group surveys were conducted to characterize upland maize production environments and systems in China, India, Indonesia, Nepal, the Philippines, Thailand, and Vietnam. Survey findings, particularly farmer-identified constraints to maize production, complemented with other relevant data, were used in country-level, R&D priority-setting workshops. High on the list of farmer constraints was drought, estimated to affect three production environments that are home to about 48 million rural poor and produce an estimated 16 million tons of maize, and others such as downy mildew, stem borers, soil erosion/landslides, waterlogging, poor agricultural extension/ technology transfer services, and poor access to low-interest credit and markets. Farmers felt that socioeconomic and policy-related constraints impact maize productivity more than technical constraints do. It is important to recognize that technology is not the only key to increasing productivity and bettering the conditions of marginal maize farmers in Asia. There is a growing trend towards commercializing and intensifying maize production that is different from the staple food self-sufficiency paradigm that has been the cornerstone of agricultural policy in most developing countries. Appropriate government policies could help alleviate the adverse consequences of commercialization and promote sustainable intensification of maize production, especially in marginal environments inhabited by resource-poor subsistence farmers
Multienvironment trials (MET) generate two types of two-way data: genotype X environment data for a target trait and genotype X trait data in individual or across environments. These data can be visually analyzed by a GGE biplot and a genotype X trait biplot, respectively. This paper describes a third type of biplot, the covariate-effect biplot, and illustrates its tandem use with the other biplots to achieve a fuller understanding of MET data. The covariate-effect biplot is generated on the basis of an explanatory trait X environment two-way table consisting of correlation coefficients between the target trait (e.g., yield) and each of the other traits in each of the environments. This biplot displays the yield-trait relations in individual environments and addresses whether and how the genotype X environment interactions (GE) for yield can be explored by indirect selection for the other traits. These other traits are treated as genetic covariables and can be replaced by other genetic covariables such as genetic markers, QTL, or genes. The biplot methodology was demonstrated by MET data of barley (Hordeum vulgare L.) conducted across North America. Both the GGE biplot and the covariate-effect biplot showed that the environments fell into two (eastern vs. western) megaenvironments. The covariate-effect pattern explained 81% of the GGE pattern, suggesting that the GE pattern for yield can be effectively explored by indirect selection for these traits. Specifically, barley yield can be improved by selecting for larger kernel weight, earlier heading, and better lodging resistance in the eastern megaenvironment. In contrast, the yield-trait relationship in the western megaenvironment was highly variable, and yield improvement can be achieved only by selecting for yield per se across environments. We suggest that the GGE biplot, the genotype X trait biplot, and the covariate-effect biplot be used jointly to better understand and more fully explore MET data.
An understanding of the causes of genotype × environment (GE) interaction can help identify traits that contribute to better cultivar performance and environments that facilitate cultivar evaluation. Through subjecting environment‐centered yield of a multi‐environment trial data to singular value decomposition, the portion of yield variation that is relevant to cultivar evaluation is partitioned into noncrossover and crossover GE interaction, quantified by the first two principal components (PC), respectively. Each PC is a set of genotypic scores multiplied by a set of environmental scores. By relating the PC scores to genotypic and environmental covariates, GE interaction represented by each PC can be interpreted in terms of trait × factor interactions. This strategy was employed in analysis of the 1992 to 1998 Ontario winter wheat (Triticum aestivum L.) performance trial data. Results indicated that plant height and maturity were the major genotypic causes of GE interaction, whereas cold temperature in the winter and hot temperature in the summer were the major environmental causes of GE interaction. Positive interactions were found between earlier maturity vs. warmer winters or hotter summers, and between shorter plant height vs. warmer winters or cooler summers. In addition, better resistance to septoria leaf blotch (caused by Septoria secalis Prill. & Delacr.) was frequently associated with overall performance. The results of this study should help in determining breeding objectives and for selecting test sites or environments for winter wheat breeding in Ontario.
The difficulty of choosing appropriate selection environments has restricted breeding progress for drought tolerance in highly-variable target environments. Genotype-by-environment interactions in southern African maize-growing environments result from factors related to maximum temperature, seasonal rainfall, season length, within season drought, subsoil pH and socio-economic factors that result in sub- optimal input application. In 1997 CIMMYT initiated a product-oriented breeding program targeted at improving maize for the drought-prone mid-altitudes of southern Africa. Maize varieties were selected in Zimbabwe using simultaneous selection in three types of environments, (i) recommended agronomic management/high rainfall conditions, (ii) low N stress, and (iii) managed drought. Between 2000 and 2002, 41 hybrids from this approach were compared with 42 released and prereleased hybrids produced by private seed companies in 36-65 trials across eastern and southern Africa. Average trial yields ranged from less than 1 t/ha to above 10 t/ha. Hybrids from CIMMYT's stress breeding program showed a consistent advantage over private company check hybrids at all yield levels. Selection differentials were largest between 2 to 5 t/ha and they became less significant at higher yield levels. An Eberhart-Russell stability analysis estimated a 40% yield advantage at the 1-ton yield level which decreased to 2.5% at the 10-ton yield level. We conclude that including selection under carefully managed high priority abiotic stresses, including drought, in a breeding program and with adequate weighing can significantly increase maize yields in a highly variable drought-prone environment and particularly at lower yield levels.
Maize remains crucial for food security in Sub-Saharan Africa. In some regions, the predominance of the crop in farming systems and diets implies that yield gains have the potential to jump-start a Green Revolution like those experienced in Asia for rice and wheat. However, despite episodes of success, the evidence compiled here suggests that very little progress has been made toward achieving this potential in recent years. Reversing this condition remains crucial to agricultural growth and food security in Africa.
Over the long term, large investments and sustained political commitment are needed to ensure strong plant breeding and seed systems to serve smallholders, predicated on improved crop management practices to protect soils and cope with unreliable rainfall, and access to appropriate labor-saving technologies. More innovative extension and advisory systems are also needed to facilitate farmer learning and adapt techniques and technologies to local environmental and social conditions. Better financial services, perhaps including new forms of insurance, are needed for smallholders.
Maize is one of the most important food crops in the world and, together with rice and wheat, provides at least 30% of the
food calories to more than 4.5 billion people in 94 developing countries. In parts of Africa and Mesoamerica, maize alone
contributes over 20% of food calories. Maize is also a key ingredient in animal feed and is used extensively in industrial
products, including the production of biofuels. Increasing demand and production shortfalls in global maize supplies have
worsened market volatility and contributed to surging global maize prices. Climatic variability and change, and the consequent
rise in abiotic and biotic stresses, further confound the problem. Unless concerted and vigorous measures are taken to address
these challenges and accelerate yield growth, the outcome will be hunger and food insecurity for millions of poor consumers.
We review the research challenges of ensuring global food security in maize, particularly in the context of climate change.
The paper summarizes the importance of maize for food, nutrition and livelihood security and details the historical productivity
of maize, consumption patterns and future trends. We show how crop breeding to overcome biotic and abiotic stresses will play
a key role in meeting future maize demand. Attention needs to be directed at the generation of high yielding, stress-tolerant
and widely-adapted maize varieties through judicious combination of conventional and molecular breeding approaches. The use
of improved germplasm per se will not, however, be enough to raise yields and enhance adaptation to climate change, and will need to be complemented by
improved crop and agronomic practices. Faced with emasculated state extension provision and imperfect markets, new extension
approaches and institutional innovations are required that enhance farmers’ access to information, seeds, other inputs, finance
and output markets. Over the long-term, large public and private sector investment and sustained political commitment and
policy support for technology generation and delivery are needed to overcome hunger, raise the incomes of smallholder farmers
and meet the challenges of growing demand for maize at the global level.
KeywordsMaize–Productivity growth–Demand–Food security–Crop breeding–Climate change–Policy
Drought is an important cause of instability of national maize grain yields and of the food supply and economy of small-scale maize-based farming systems in the tropics. Water shortages affect maize yields throughout the crop cycle, but most severely at flowering and to a lesser degree at establishment. Maize is often grown in environments thought to be better suited to sorghum and millet, yet because farmers in these areas persist with maize, researchers have an obligation to help stabilize maize production. Recurrent selection, which focused mainly on increasing tolerance to drought during flowering and grainfilling, has successfully increased grain yield over a wide range of moisture regimes. Gains ranged from 80-108 (mean 94) kg ha−1 yr−1 when selecting among full-sib (FS) families to 73–144 (mean 111) kg ha−1 yr−1 when selecting among S, families, and were observed when selections were evaluated at a drought-induced yield level of 1.5–2.4 ton ha−1. This represents annual gains in severely droughted environments of >5%. Under well-watered conditions where yields ranged from 5.6-8.0tonha−1, gains from the same two selection schemes ranged from 38–108 (mean 73)kgha−1 yr−1 and from 27–89 (mean 59)kgha−1 yr−1, respectively. Gains in yield were mainly due to increased numbers of grains per plant, and were associated with a reduced anthesis-silking interval (ASI) and an increased harvest index. These changes are consistent with increased assimilate partitioning to the ear at flowering, a phenomenon that will need to be addressed by maize models that focus on genotypic responses to stress. Little change was observed in plant water status or foliar senescence rates. Drought-tolerant varieties have shown similar gains when evaluated under low N conditions, suggesting that partitioning of N to the ear has also been improved. The challenge now is to develop drought-tolerant hybrids. Conventionally improved populations have provided a lower frequency of drought-tolerant hybrids than their counterparts with a history of improvement for drought tolerance. Molecular marker-based linkage maps of ASI, an easily observed indicator of drought tolerance at flowering, suggest that this trait could be efficiently transferred to elite inbred lines using marker-assisted backcrossing techniques. Yields of drought-tolerant varieties, lines and hybrids, when grown under well-watered conditions, have shown clearly that drought tolerance does not come at the cost of yield potential. The key to efficient improvement for drought-tolerance lies in the choice of elite adapted germplasm, use of carefully managed drought stress, and selection based on a minimum data set comprising anthesis date, ASI, ears per plant and shelled grain yields. This results in stabilized and improved yield for the maize component of maize-based cropping systems exposed to mid-season and terminal drought in highly variable rainfall environments.
Maize and wheat are two of the most important food crops worldwide. Together with rice, they provide
30% of the food calories to 4.5 billion people in almost 100 developing countries. Predictions suggest
that climate change will reduce maize production globally by 3 to 10% by 2050 and wheat production in
developing countries by 29 to 34%. This will coincide with a substantial increase in demand for maize
and wheat due to rising populations. Maize and wheat research has a crucial role to play in enhancing
adaptation to and mitigation of climate change while also enhancing food security. Crop varieties with
increased tolerance to heat and drought stress and resistance to pests and diseases are critical for
managing current climatic variability and for adaptation to progressive climate change. Furthermore,
sustainable agronomic and resource management practices, such as conservation agriculture and
improved nitrogen management can contribute to climate change mitigation. There is also a need for
better policies and investments in infrastructure to facilitate technology adoption and adaptation. These
include investments in irrigation, roads, storage facilities and improved access to markets. There is
also a need for policy innovations for stabilizing prices, diversifying incomes, increasing farmer access
to improved seeds and finance, and providing safety nets to enhance farmers’ livelihood security. This
review paper details the potential impacts of climate change on food security, and the key role of
improved technologies and policy and institutional innovations for climate change adaptation and
mitigation. The focus is on maize and wheat in sub-Saharan Africa and South Asia.
This study evaluates the potential impacts of investing in Drought Tolerant Maize (DTM) in 13 countries of East, South and West Africa. The analysis utilizes geo-referenced production data at the regional and household levels and employs a model that estimates both the conventional mean yield gains and the additional benefits from yield stability gains of DTM varieties as well as impacts on poverty. The results indicate that by 2016, adoption of DTM can generate between US 590 million in cumulative benefits to both producers and consumers. Yield variance reductions stand to generate considerable benefits, especially in high drought risk areas. These benefits translate into poverty reductions in the range of 0.01–4.29% by 2016. Significant benefits are also found among different types of households living in drought risk areas of Kenya, Ethiopia and Nigeria.
GENOTYPE-BY-ENVIRONMENT INTERACTION AND STABILITY ANALYSIS Genotype-by-Environment Interaction Heredity and Environment Genotype-by-Environment Interaction Implications of GEI in Crop Breeding Causes of Genotype-by-Environment Interaction Stability Analyses in Plant Breeding and Performance Trials Stability Analysis in Plant Breeding and Performance Trials Stability Concepts and Statistics Dealing with Genotype-by-Environment Interaction GGE Biplot: Genotype + GE Interaction GGE BIPLOT AND MULTI-ENVIRONMENTAL TRIAL ANALYSIS Theory of Biplot The Concept of Biplot The Inner-Product Property of a Biplot Visualizing the Biplot Relationships among Columns and among Rows Biplot Analysis of Two-Way Data Introduction to GGE Biplot The Concept of GGE and GGE Biplot The Basic Model for a GGE Biplot Methods of Singular Value Partitioning An Alternative Model for GGE Biplot Three Types of Data Transformation Generating a GGE Biplot Using Conventional Methods Biplot Analysis of Multi-Environment Trial Data Objectives of Multi-Environment Trial Data Analysis Simple Comparisons Using GGE Biplot Mega-Environment Investigation Cultivar Evaluation for a Given Mega-Environment Evaluation of Test Environments Comparison with the AMMI Biplot Interpreting Genotype-by-Environment Interaction GGE BIPLOT SOFTWARE AND APPLICATIONS TO OTHER TYPES OF TWO-WAY DATA GGE Biplot Software-The Solution for GGE Biplot Analyses The Need for GGE Biplot Software The Terminology of Entries and Testers Preparing Data File for GGE Biplot Organization of GGE Biplot Software Functions for a Genotype-by-Environment Dataset Function for a Genotype-by-Strain Dataset Application of GGE Biplot to Other Types of Two-way Data GGE Biplot Continues to Evolve Cultivar Evaluation Based on Multiple Traits Why Multiple Traits? Cultivar Evaluation Based on Multiple Traits Identifying Traits for Indirect Selection for Loaf Volume Identification of Redundant Traits Comparing Cultivars as Packages of Traits Investigation of Different Selection Strategies Systems Understanding of Crop Improvement Three-Mode Principal Component Analysis and Visualization QTL Identification Using GGE Biplot Why Biplot? Data Source and Model Grouping of Linked Markers Gene Mapping Using Biplot QTL Identification via GGE Biplot Interconnectedness among Traits and Pleiotropic Effects of a Given Locus Understanding DH Lines through the Biplot Pattern QTL and GE Interaction Biplot Analysis of Diallel Data Model for Biplot Analysis of Diallel Data General Combining Ability of Parents Specific Combining Ability of Parents Heterotic Groups The Best Testers for Assessing General Combining Ability of Parents The Best Crosses Hypothesis on the Genetic Constitution of Parents Targeting a Large Dataset Advantages and Disadvantages of the Biplot Approach Biplot Analysis of Host Genotype-by-Pathogen Strain Interactions Vertical vs. Horizontal Resistance Genotype-By-Strain Interaction for a Barley Net Blotch Genotype-by-Strain Interaction for Wheat Fusarium Head Blight Biplot Analysis to Detect Synergism between Genotypes of Different Species Genotype-by-Strain Interaction for Nitrogen-Fixation Wheat-Maize Interaction for Wheat Haploid Embryo Formation References Index
Multienvironment trials (MET) are conducted every year for all major crops throughout the world, and best use of the information contained in MET data for cultivar evaluation and recommendation has been an important issue in plant breeding and agricultural research. A genotype main effect plus genotype x environment interaction (GGE) biplot based on MET data allows visualizing (i) the which-won-where pattern of the MET, (ii) the interrelationship among test environments, and (iii) the ranking of genotypes based on both mean performance and stability. Correct visualization of these aspects, however, requires appropriate singular-value (SV) partitioning between the genotype and environment eigenvectors. This paper compares four SV scaling methods. Genotype-focused scaling partitions the entire SV to the genotype eigenvectors; environment-focused scaling partitions the entire SV to the environment eigenvectors; symmetrical scaling splits the SV symmetrically between the genotype and the environment eigenvectors; and equal-space scaling splits the SV such that genotype markers and environment markers take equal biplot space. It is recommended that the genotype-focused scaling be used in visualizing the interrelationship and comparison among genotypes and the environment-focused scaling be used in visualizing the interrelationship and comparison among environments. All scaling methods are equally valid in visualizing the which-won-where pattern of the MET data, but the symmetric scaling is preferred because it has all properties intermediate between the genotype- and the environment-focused scaling methods.
tion in an elite lowland tropical maize population 'Tux- peno Crema I' (Johnson et al., 1986) in 1975, under Drought is common in tropical environments, and selection for conditions of managed drought stress. This population, drought tolerance is one way of reducing the impacts of water deficit on crop yield. The primary objective of this study was to evaluate later renamed 'Tuxpeno Sequia', underwent eight cycles biomass, grain yield, and harvest index of maize (Zea mays L.) popula- of recurrent full-sib selection in the dry winter season tions selected for drought tolerance. Three late-maturing tropical at Tlaltizapan, Mexico. Here the timing and intensity maize populations were subjected to three cycles of S1 recurrent selec- of drought stress could be managed by irrigation, one tion ('La Posta Sequia' and 'Pool 26 Sequia') or eight cycles of full-sib strategy sometimes used by plant breeders to develop recurrent selection ('Tuxpeno Sequia') for yield and traits indicative of drought tolerance. Methods of selection and water man- drought tolerance during flowering and grain filling. Selection gains agement have been described by Fischer et al. (1989) were assessed in five trials conducted under mid-late season drought and Bolanos and Edmeades (1993a). and in five trials conducted under well-watered conditions. In water- A second strategy for developing drought tolerance stressed environments, with average yields of 1.0 to 4.5 Mg ha 21 , yield is the conventional breeding approach which relies on
Water-deficits during flowering and pollination can cause considerable reductions in yields of determinate crops due to influences on reproductive components. This study was conducted to determine how different levels of soil water-deficit during emergence of tassels influence silking and yield components of maize. A rain shelter provided timely water-deficits in a field environment during 1987 on a sandy soil in Michigan. Yield reductions in excess of 90% occurred when water-deficits spanned the interval from just prior to tassel emergence to beginning of grain-fill. Emergence of tassels and silks was delayed more than two weeks. Final internode lengths reflected reductions in plant extension growth, and evaluation of lengths of individual internodes depicted the windows of development in which plants were most affected by water-deficits. Grain number was reduced in proportion to the duration of the water-deficit period. Assessment of grain and non-grain above-ground biomass 100 days after sowing demonstrated that both were reduced by severe water-deficits, but not to the same degree. There was delayed development in response to the severe water-deficits, as was apparent from 75% silking dates and biomass assessments.
The difficulty of choosing appropriate selection environments has restricted breeding progress for abiotic stress tolerance in highly variable target environments. Genotype-by-environment interactions in southern African maize growing environments result from factors related to maximum temperature, season rainfall, season length, within-season drought, subsoil pH and socio-economic factors that result in sub-optimal input application. In 1997, CIMMYT initiated a product-oriented breeding program targeted at improving maize for the drought-prone mid-altitudes of southern Africa. Maize varieties were selected in Zimbabwe using simultaneous selection in three types of environments, (i) recommended agronomic management/high rainfall conditions, (ii) low N stress, and (iii) managed drought. Between 2000 and 2002, 41 hybrids from this approach were compared with 42 released and pre-released hybrids produced by private seed companies in 36–65 trials across eastern and southern Africa. Average trial yields ranged from less than 1 t/ha to above 10 t/ha. Hybrids from CIMMYT's stress breeding program showed a consistent advantage over private company check hybrids at all yield levels. Selection differentials were largest between 2 and 5 t/ha and they became less significant at higher yield levels. An Eberhart–Russell stability analysis estimated a 40% yield advantage at the 1-t yield level which decreased to 2.5% at the 10-t yield level. We conclude that including selection under carefully managed high-priority abiotic stresses, including drought, in a breeding program and with adequate weighing can significantly increase maize yields in a highly variable drought-prone environment and particularly at lower yield levels.
Following the liberalization and restructuring of the seed sector, the maize seed industry in eastern and southern Africa has witnessed a proliferation of private seed companies. Whereas the total number of registered maize seed companies in major maize producing countries increased four-fold between 1997 and 2007, the quantity of seed marketed barely doubled suggesting that the seed production and deployment environment is less than perfect. A study involving over 92% of all seed providers in east and southern Africa in 2007 showed that a number bottlenecks affect the entire maize seed value chain. The lack of access to credit constitutes a significant barrier to entry. Until governments and development partners make credit available to seed entrepreneurs directly or through risk sharing arrangements with commercial banks, national seed companies will not grow leaving the seed sector monopolized by the regional and multinational seed companies. In addition, the transfer of genetic materials between public and private sectors should be improved to allow easy access by seed companies to suitable and adapted varieties. To allow for rapid regional spillovers of varieties released in one country to similar agro-ecologies in different countries, the implementation of the harmonized regional seed laws and regulations should be expedited. Finally, the best strategies that increase the adoption of improved maize varieties should be explored and implemented to enhance seed demand.
The publication describes outcomes of a study conducted in 2007/08 to analyze the bottlenecks affecting the production and deployment of maize seed in eastern and southern Africa. The objectives of the study were to provide a better understanding of the factors limiting the production and deployment of improved maize seed in Africa, and to contribute to increasing the efficiency of variety release, seed production and seed dissemination for new drought tolerant maize varieties. The study identified a number of institutional bottlenecks affecting the maize seed value chain, in particular in the area of policy, credit availability, seed production, germplasm and marketing. To address these bottlenecks and improve the efficiency of seed production and deployment to African farmers, the authors recommended a coordinated effort from policy makers, private and public organizations and farmers. The study was supported by the Bill & Melinda Gates Foundation and the Howard G. Buffett Foundation
Performance of Elite Maize Varieties Tested On farm Trials in Eastern and Southern Africa
- S Chipoka
- Ndalika Malawi
- Epa Chipoka
- M Salima
- Mhango Malawi
- Epa Chipoka
- Seed Salima
- Co
- Sophie Seedco Lilongwe Malawi
- P Setimela
- J Macrobert
- G N Atlin
- C Magorokosho
- A Tarekegne
- D Makumbi
- G Taye
Chipoka
S. Ndalika
Malawi
Chipoka EPA Salima
M. Mhango
Malawi
Chipoka EPA Salima
Seed Co.Sophie
SeedCo Lilongwe Malawi
Setimela, P., MacRobert, J., Atlin, G. N., Magorokosho,
C., Tarekegne, A., Makumbi, D., & Taye, G. (2012).
Performance of Elite Maize Varieties Tested On farm
Trials in Eastern and Southern Africa. Presented at the
ASA, CSSA, and SSSA International Annual Meetings,
21–24 October, 2012. Cincinnati, Ohio, USA.
Estimates of genetic variances in Striga resistant extra-early-maturing maize populations
- B Badu-Apraku
Badu-Apraku, B. 2007a. Estimates of genetic variances in Striga resistant
extra-early-maturing maize populations. J. New Seeds 8(2):23-43.
doi:10.1300/J153v08n02_02
Recent advances in breeding maize for drought and salinity stress tolerance
- M Bänziger
- J L Araus
Bänziger, M., and J.L. Araus. 2007. Recent advances in breeding maize
for drought and salinity stress tolerance. In: M.A. Jenks, P.M.
Hasegawa, and S. Mohan, editors, Advances in molecular breeding
towards drought and salt tolerant crops. Springer, the Netherlands.
p. 587-601. doi:10.1007/978-1-4020-5578-2_23
Efficiency of high-N selection environments for improving maize for low-N target environments
- M Bänziger
- F Betran
- H Lafitte
Bänziger, M., F. Betran, and H. Lafitte. 1997. Efficiency of high-N
selection environments for improving maize for low-N target
environments. Crop Sci. 37:1103-1109. doi:10.2135/cropsci1997.
0011183X003700040012x
Breeding for low-input conditions and consequences for participatory plant breedingExamples from tropical maize and wheat
- M Bänziger
- M E Cooper
Bänziger, M., and M.E. Cooper. 2001. Breeding for low-input
conditions and consequences for participatory plant breedingExamples from tropical maize and wheat. Euphytica 122:503-519.
doi:10.1023/A:1017510928038
Adapting maize production to climate change in sub-Saharan
- J E Cairns
- J Hellin
- K Sonder
- J L Araus
- J F Macrobert
- C Thierfelder
- B M Prasanna
Cairns, J.E., J. Hellin, K. Sonder, J.L. Araus, J.F. MacRobert, C.
Thierfelder, and B.M. Prasanna. 2013. Adapting maize production
to climate change in sub-Saharan Africa. Food Secur. 5:345-360.
doi:10.1007/s12571-013-0256-x
Preference index from voting by men and women on the different varieties in the trials
Fig. 7. Preference index from voting by men and women on the different varieties in the trials.
Agronomy Journal • Volume 109, Issue 2 • 2017
VSN International. GenState for Windows 15th ed. VSN International
- Genstat
GenStat. 2014. VSN International. GenState for Windows 15th ed.
VSN International, Hemel Hempstead, UK. GenStat.co.uk
(accessed 16 Jan. 2016).
Could farmer interest in a diversity of seed attributes to explain adoption plateaus for modern maize varieties in Malawi?
- R Lunduka
- M Fisher
- S Snapp
Lunduka, R., M. Fisher, and S. Snapp. 2012. Could farmer interest in a
diversity of seed attributes to explain adoption plateaus for modern
maize varieties in Malawi? Food Policy 37, no. 5. (2012):504-510.
doi:10.1016/j.foodpol.2012.05.001
Characterization of maize germplasm grown in eastern and southern Africa: Results of the 2010 regional trials coordinated by CIMMYT
- C Magorokosho
- A Tarekegne
- J Macrobert
Magorokosho, C., A. Tarekegne, and J. MacRobert. 2011.
Characterization of maize germplasm grown in eastern and
southern Africa: Results of the 2010 regional trials coordinated by
CIMMYT. CIMMYT, Harare, Zimbabwe.
Character ization of maize germplasm grown in eastern and southern Africa: Results of the 2008 regional trials coordinated by CIMMYT
- C Magorokosho
- B Vivek
- J Macrobert
Magorokosho, C., B. Vivek, and J. MacRobert. 2009. Character ization
of maize germplasm grown in eastern and southern Africa: Results
of the 2008 regional trials coordinated by CIMMYT. CIMMYT,
Harare, Zimbabwe.
Gains in maize genetic improvement in Eastern and Southern Africa: II. CIMMYT open pollinated varieties breeding pipeline
- B Masuka
- C Magorokosho
- M Olsen
- G N Atlin
- M Bänziger
- K Pixley
Masuka, B., C. Magorokosho, M. Olsen, G.N. Atlin, M. Bänziger, K.
Pixley et al. 2017b. Gains in maize genetic improvement in Eastern
and Southern Africa: II. CIMMYT open pollinated varieties
breeding pipeline. Crop Sci. doi:10.2135/cropsci2016.05.0408
Analysis of combined experiments
- M S Mcintosh
McIntosh, M.S. 1983. Analysis of combined experiments. Agron. J.
75:153-155. doi:10.2134/agronj1983.00021962007500010041x
Farmers' highland maize (Zea mays L.) selection criteria: Implication for maize breeding for the Hararghe highlands of eastern Ethiopia
- E Mulatu
- H Zelleke
Mulatu, E., and H. Zelleke. 2002. Farmers' highland maize (Zea mays
L.) selection criteria: Implication for maize breeding for the
Hararghe highlands of eastern Ethiopia. Euphytica 127(1):11-30.
doi:10.1023/A:1019939721444
Estimation of heritability and prediction of selection response in plant populations
- W E Nyquist
- R J Baker
Nyquist, W.E., and R.J. Baker. 1991. Estimation of heritability and
prediction of selection response in plant populations. Crit. Rev.
Plant Sci. 10(3):235-322. doi:10.1080/07352689109382313
Yield trends are insufficient to double global crop production by 2050
- D K Ray
- M D Mueller
- P C West
- J A Foley
Ray, D.K., M.D. Mueller, P.C. West, and J.A. Foley. 2013. Yield trends
are insufficient to double global crop production by 2050. PLoS
One 8(6):e66428. doi:10.1371/journal.pone.0066428
Use of molecular markers in plant breeding: Drought tolerance improvement in tropical maize
- J M Ribaut
- M Bänziger
- F J Betrán
- C Jiang
- G O Edmeades
- K Dreher
- D Hoisington
Ribaut, J.M., M. Bänziger, F.J. Betrán, C. Jiang, G.O. Edmeades, K.
Dreher, and D. Hoisington. 2002. Use of molecular markers in
plant breeding: Drought tolerance improvement in tropical maize.
In: M.S. Kang, editor, Quantitative genetics, genomics and plant
breeding. CAB Int., Wallingford, UK. p. 85-99.
Managing vulnerability to drought and enhancing livelihood resilience in sub-Saharan Africa: Technological, institutional and policy options
- B Shiferaw
- K Tesfaye
- M Kassie
- T Abate
- B M Prasanna
- A Menkir
Shiferaw, B., K. Tesfaye, M. Kassie, T. Abate, B.M. Prasanna, and A.
Menkir. 2014. Managing vulnerability to drought and enhancing
livelihood resilience in sub-Saharan Africa: Technological,
institutional and policy options. Weather and Climate Extremes
3:67-79. doi:10.1016/j.wace.2014.04.004
Maize revolutions in subSaharan Africa. In an African green revolution. Sprinter, Dordrect, the Netherlands
- M Smale
- D Byerlee
- T Jayne
Smale, M., D. Byerlee, and T. Jayne. 2011. Maize revolutions in subSaharan Africa. In an African green revolution. Sprinter, Dordrect,
the Netherlands. p. 165-195.
The bioeconomic impact of climate change on maize production in sub-Saharan Africa and its implications for food security
- K Tesfaye
- S Gbegbelegbe
- J E Cairns
- B Shiferaw
- B M Prasanna
- K J Boote
Tesfaye, K., S. Gbegbelegbe, J.E. Cairns, B. Shiferaw, B.M. Prasanna,
K.J. Boote et al. 2015. The bioeconomic impact of climate change
on maize production in sub-Saharan Africa and its implications
for food security. Int. J. Clim. Chang. Strateg. Manag. 7:247-271.
doi:10.1108/IJCCSM-01-2014-0005
Rapid gains in yield and adoption of new maize varieties for complex hillside environments through farmer participation: I. Improving options through participatory varietal selection (PVS)
- T P Tiwari
- D S Virk
- Fl Sinclair
Tiwari, T.P., D.S. Virk, and Fl. Sinclair. 2009. Rapid gains in yield and
adoption of new maize varieties for complex hillside environments
through farmer participation: I. Improving options through
participatory varietal selection (PVS). Field Crops Res. 111:137143. doi:10.1016/j.fcr.2008.11.008
N uptake and utilization in contrasting N efficient tropical maize hybrids
- M Worku
- M Bänziger
- D Friesen
- W J Horst
Worku, M., M. Bänziger, D. Friesen, and W.J. Horst. 2007. N uptake
and utilization in contrasting N efficient tropical maize hybrids.
Crop Sci. 47:519-528. doi:10.2135/cropsci2005.05.0070
Biplot analysis of multi-environment trial data: Principles and applications
- W Yan
- N A Tinker
Yan, W., and N.A. Tinker. 2006. Biplot analysis of multi-environment
trial data: Principles and applications. Can. J. Plant Sci. 86:623645. doi:10.4141/P05-169