Response For Grain Yield Research Articles

Selection response for grain yield and its components in one segregating population of bread wheat (Triticum aestivum. L).

Selection response for grain yield and its components in one segregating population of bread wheat (Triticum aestivum. L).

Genomic prediction and selection response for grain yield in safflower.

In plant breeding programs, multiple traits are recorded in each trial, and the traits are often correlated. Correlated traits can be incorporated into genomic selection models, especially for traits with low heritability, to improve prediction accuracy. In this study, we investigated the genetic correlation between important agronomic traits in safflower. We observed the moderate genetic correlations between grain yield (GY) and plant height (PH, 0.272-0.531), and low correlations between grain yield and days to flowering (DF, -0.157-0.201). A 4%-20% prediction accuracy improvement for grain yield was achieved when plant height was included in both training and validation sets with multivariate models. We further explored the selection responses for grain yield by selecting the top 20% of lines based on different selection indices. Selection responses for grain yield varied across sites. Simultaneous selection for grain yield and seed oil content (OL) showed positive gains across all sites with equal weights for both grain yield and oil content. Combining g×E interaction into genomic selection (GS) led to more balanced selection responses across sites. In conclusion, genomic selection is a valuable breeding tool for breeding high grain yield, oil content, and highly adaptable safflower varieties.

Selection response for grain yield in a segregation population of bread wheat under heat stress

Selection response for grain yield in a segregation population of bread wheat under heat stress

Genotype X Environment Interaction and Yield Stability of Bread Wheat Genotypes in central Ethiopia

The present study was conducted to interpret Genotype main effect and GEI obtained by AMMI analysis and group the genotype having similar response pattern over all environments. Fifteen bread wheat genotypes were evaluated by RCBD using four replications at six locations in Ethiopia. The main effect differences among genotypes, environments, and the interaction effects were highly significant (P ≤ 0.001) for the total variance of grain yield. Results of AMMI analysis of mean grain yield for the six locations showed significant differences (P0.001) among the genotypes, environments and GEI. The environment had the greatest effect with the environmental sum of squares (35.28%) than the genotypes (33.46%) and GEI (31.45%) effect. The AMMI analysis for the IPCA1 captured 46.1% and the IPCA2 explained 28.6%. The two IPC cumulatively captured 74.7% of the sum of square the GEI of bread wheat genotypes, when the IPCA1 was plotted against IPCA2. The genotype ETBW8075, ETBW8070 and ETBW9470 were unstable as they are located far apart from the other genotypes in the biplot when plotted on the IPCA1 and IPCA2 scores. The ETBW8078, ETBW8459, Hidase and ETBW8311 were genotype located near to the origin of the biplot which implying that it was stable bread wheat genotypes across environments. There is closer association between Lemu and ETBW8065 which indicate similar response of the genotypes to the environment. The best genotype with respect to location Kulumsa was ETBW9470, ETBW8075 was the best genotype for Dhera, ETBW8070 was the best genotype for Holeta while ETBW9466 was the best genotype for Arsi Robe. Arsi Robe and Kulumsa is the most favorable environment for all genotypes with nearly similar yield response for grain yield.

Additive Main effect and Multiplicative Interaction Analysis of Grain Yield of advanced Bread Wheat (Triticum aestivum L) Genotype in Ethiopia

The present study was conducted to interpret Genotype main effect and GEI obtained by AMMI analysis and group the genotype having similar response pattern over all environments. Fifteen bread wheat genotypes were evaluated by RCBD using four replications at six locations in Ethiopia. The main effect differences among genotypes, environments, and the interaction effects were highly significant (P ≤ 0.001) of the total variance of grain yield. Results of AMMI analysis of mean grain yield for the six locations showed significant differences (P<0.001) among the genotypes, the environments and GEI. The environment had the greatest effect of the environmental sum of squares (35.28%) than the genotypes (33.46%) and GEI(31.45%) effect. The AMMI analysis for the IPCA1 captured 46.1% and the IPCA2 explained 28.6% the two IPC cumulatively captured 74.7% of the sum of square the GEI of bread wheat genotypes, when the IPCA1 was plotted against IPCA2. The genotype ETBW8075, ETBW8070 and ETBW9470 were unstable as they are located far apart from the other genotypes in the biplot when plotted on the IPCA1 and IPCA2 scores. The ETBW8078, ETBW8459, Hidase and ETBW8311 were genotype located near to the origin of the biplot which implying that it was stable bread wheat genotypes across environments. There is closer association between Lemu and ETBW8065 which indicate similar response of the genotypes to the environment. The best genotype with respect to location Kulumsa was ETBW9470, ETBW8075 was the best genotype for Dhera, ETBW8070 was the best genotype for Holeta while ETBW9466 was the best genotype for Arsi Robe. Arsi Robe and Kulumsa is the most favorable environment for all genotypes with nearly similar yield response for grain yield.

Synergistic Effect of Sulfur and Nitrogen in the Organic and Mineral Fertilization of Durum Wheat: Grain Yield and Quality Traits in the Mediterranean Environment

In recent years, awareness on sustainable land use has increased. Optimizing the practice of nitrogen fertilization has become crucially imperative in cropping management as a result of this current trend. The effort to improve the availability of organic nitrogen has incurred a bottleneck while seeking to achieve a high yield and quality performance for organic winter cereals. Field experiments were conducted, under rainfed Mediterranean conditions, over a period of two subsequent growing seasons. The objective was to investigate the effect of soil and foliar S application on the performance of three durum wheat cultivars fertilized with either organic or inorganic N. The hypothesis to be verified was if different S fertilization strategies could improve grain yield and quality when coupled with mineral or organic N fertilizer. There were three levels of treatment with mineral N fertilizer (120, 160 and 200 kg ha−1), two levels of organic N fertilizer (160 and 200 kg ha−1), two levels of S fertilizer applied to the soil (0 and 70 kg ha−1), and two levels of foliar S application at flag leaf stage (0 and 5 kg ha−1). Cultivars were Dylan, Iride and Saragolla. Analyzed traits were grain yield, yield components and quality features of grain. Overall, at the same N rate, grain yield and quality were markedly higher for mineral than organic N source. Cultivar × Year × N treatment interactions significantly affected grain yield and quality indices. Iride showed a high yield stability throughout the mineral N rates in the most favorable year (2011) and, in the same year, was the top performing cultivar in organic N treatments. Dylan was the top performing cultivar for protein content, while Saragolla for the SDS sedimentation test. Soil S fertilization had no effect on grain quality, whereas it significantly increased grain yield (+ 300 kg ha−1) when coupled with organic rather than a mineral N source. However, foliar S application at flag leaf stage did not affect grain yield, but it significantly enhanced quality indices such as test weight (81 vs. 79.9 kg hL−1), protein content (13.7% vs. 12.9 %) and SDS value (72.5 vs. 70.5 mm). A rate of 160 kg ha−1 of N (both mineral and organic) determined the optimal response for both grain yield and quality. Finally, soil and foliar application of S may help to contain the large yield and quality gap that still exists between mineral and organic fertilization of durum wheat.

Stability Analysis of Durum Wheat (Triticum Durum Desf) Genotypes by Regression Measurement In Ethiopia

In this study, 13 advanced lines with 4 standard and a local check of Durum wheat (Triticum turgidum var. durum Desf.) were evaluated for two consecutive cropping seasons (2014-2015) at six research stations for grain yield in Ethiopia. The combined analysis of variance indicated that the main effects of location and genotype and interaction effects of genotype × year, genotype × location and genotype × year × location were highly significant for grain yield. GE interaction was analyzed using linear regression techniques. There was a considerable variation in grain yield among genotypes and environments. Stability was estimated using the Eberhart and Russell method. Stability analysis of grain yield in deferent environments showed that the variance of genotypes and genotypes × environment interactions were significant. Due to the stability analysis, Genotypes 2, 3, 4 and 15 have b value close to one, i.e. genotypes are responsive to good environments, and it may be considered stable for grain yield in all of the environments. The deviation from regression for G7, G9, G10 and G11 are also low and because of the low value of the genotypic mean, these genotypes are intermediate stable and poorly adapted to all environments. None of the genotypes evaluated was perfectly stable in all of the environments due to lack of b- the value equal to unity. The broad sense heritability was 69.2%, indicating selection should give a good response for grain yield.

Heritability and Selection Response for Grain Yield and Associated Traits in F3 Wheat Populations

Heritability and Selection Response for Grain Yield and Associated Traits in F3 Wheat Populations

SELECTION RESPONSE FOR INCREASED GRAIN YIELD IN TWO HIGH OIL MAIZE SYNTHETICS

Selection for increased oil level in maize showed the increase was associated with decrease in starch concentration, kernel weight, and grain yield. The study was conducted with the objectives: (1) to evaluate response to six cycles for increased grain yield in the high oil maize Alexho Elite (AE: 60-90 g kg-1 oil concentration) and Ultra High Oil (UHO: 100-140 g kg-1 oil concentration) using inbred tester B73; (2) to measure responses to selection for increased grain yield with changes in yield components; and (3) to determine a suitable tester. Previously the two synthetics had been selected for oil concentration. After six cycles, the six genotypes i.e. AE C0, AE C3, AE C6, UHO C0, UHO C3, and UHO C6 were testcrossed to B73, LH185, and LH202 inbreds (40 g kg-1 oil concentration) to a total of 18 testcrosses. Two field experiments were used to evaluate selection in AE and UHO testcrosses. The study showed selection using inbred tester B73 in AE and UHO was effective in increasing grain yield of AE testcrosses without changing (i.e. decreasing) oil and protein concentrations. AE testcrosses produced higher grain yield and greater selection response for grain yield than UHO testcrosses. LH185 was best for grain yield in AE and UHO testcrosses. Increase in grain yield in most of the testcrosses was associated with increases in starch concentration, kernel weight, kernel number, and grain weight.

SELECTION RESPONSE FOR INCREASED GRAIN YIELD IN TWO HIGH OIL MAIZE SYNTHETICS

Selection for increased oil level in maize showed the increase was associated with decrease in starch concentration, kernel weight, and grain yield. The study was conducted with the objectives: (1) to evaluate response to six cycles for increased grain yield in the high oil maize Alexho Elite (AE: 60-90 g kg-1 oil concentration) and Ultra High Oil (UHO: 100-140 g kg-1 oil concentration) using inbred tester B73; (2) to measure responses to selection for increased grain yield with changes in yield components; and (3) to determine a suitable tester. Previously the two synthetics had been selected for oil concentration. After six cycles, the six genotypes i.e. AE C0, AE C3, AE C6, UHO C0, UHO C3, and UHO C6 were testcrossed to B73, LH185, and LH202 inbreds (40 g kg-1 oil concentration) to a total of 18 testcrosses. Two field experiments were used to evaluate selection in AE and UHO testcrosses. The study showed selection using inbred tester B73 in AE and UHO was effective in increasing grain yield of AE testcrosses without changing (i.e. decreasing) oil and protein concentrations. AE testcrosses produced higher grain yield and greater selection response for grain yield than UHO testcrosses. LH185 was best for grain yield in AE and UHO testcrosses. Increase in grain yield in most of the testcrosses was associated with increases in starch concentration, kernel weight, kernel number, and grain weight.

Genotype × Environment Interaction for Plant Density Response in Maize (Zea mays L.)

Increased adaptation to high plant density has been an important factor in improvements in grain yield in maize (Zea mays L.). Despite extensive public literature on variation and improvement in plant density response among maize varieties, much less public information is available on effects of environment and genotype × environment interactions (G × E) on plant density response for grain yield in maize. The present study was conducted to quantify environment effects and G × E effects on plant density response for maize grain yield. A set of 57 synthetic populations, synthetic × inbred line crosses, and synthetic × synthetic population crosses were evaluated across a five year period including 17 individual location–years. The data in this study were an unbalanced combination of multiple experiments that included 370 pedigree‐environment combinations with each containing at least four planting densities and two replications per environment in most cases. G × E accounted for 26% of total genetic variance (genetic variance plus G × E variance) in linear regression coefficients and 39% of variance in quadratic regression coefficients in the regression of grain yield on observed plant density. Variance in G × E for linear and quadratic regression coefficients resulted in variation in optimal densities among varieties being highly specific to individual environments. Average plant density responses varied widely among environments with average optimal plant densities ranging from 5.6 to 9.1 plants m–2.

Stability Analysis of Durum Wheat Genotypes by Regression Parameteres in Dryland Conditions

The objectives of this study were to estimate genotype × environment (GE) interaction effects and to determine the stable durum wheat (Triticum turgidum var. durum Desf.) genotypes for grain yield in warm winter areas of Iran. Twenty durum wheat genotypes, including 18 experimental lines and two local checks were evaluated during three cropping seasons (2004–2006) at five research sites. The combined analysis of variance indicated that the main effects of location and genotype and interaction effects of genotype × year, genotype × location and genotype × year × location were highly significant for grain yield. GE interaction was analyzed using linear regression techniques. There was considerable variation for grain yield among both genotypes and environments. Stability was estimated using the Eberhart and Russell method. Stability analysis of grain yield in different environments showed that the variance of genotypes and genotypes × environment (linear) interactions were significant. Due to the stability analysis, genotype 12 (D68-1-93A-1A//Ruff/Fg/3/Mtl-5/4/Lahn) indicated relatively minimum value for S2d and a b-value close to unity and hence, it may be considered stable for grain yield in all of the environments. The results showed that G10 (Bcr//Memo/goo) also favor for its stability in high yielding environments. The broad sense heritability was 77%, indicating selection should give a good response for grain yield.

Evaluation of Drought Tolerance among Elite Indian Bread Wheat Cultivars

Thirty diverse elite Indian wheat genotypes varying in their yield performance and drought tolerance were evaluated to examine differences for some drought tolerance characters and to determine relationship between these characters. Genotypes differed in their response for grain yield, days to heading, excised-leaf water loss and relative water content under both conditions over years. Under irrigated conditions differences in the genotypes for water retention traits were not clear. The varieties HPW251, Hindi 62, HPW184, VL 892 and VL 907 showed a good combination of drought resistance, water retention and high grain yield, whereas C 306, VL 421 and NI 5439 had high grain yield only under drought stress conditions and showed better water retention in the leaves. These genotypes may be used for exploitation of drought tolerance in wheat breeding programmes. Drought response index (DRI) appeared to be an important trait as the genotypes having high DRI values also had high grain yield, high water retention and low score of drought susceptibility index (DSI) under drought stress.

Change in heritability estimates due to half-sib family selection in the maize variety Pahari

This research was carried out at the Agriculture Research Farm, Khyber Pakhtunkhwa Agricultural University, Peshawar, and the Cereal Crops Research Institute, Pirsabak, Nowshera, during 2009 and 2010. Half-sib families (HS) derived from the maize variety Pahari in spring crop seasons 2009 and 2010 were developed at the Cereal Crops Research Institute. All HS families were detasseled well before pollen shedding. At maturity, each family was harvested and shelled separately. During the summer crop of seasons 2009 and 2010, these HS families were evaluated in 12 x 12 and 11 x 11 partially balanced lattice square arrangements at the Khyber Pakhtunkhwa Agricultural University, Peshawar, for various flowering and yield traits, respectively. The data on days to mid-silking, anthesis, anthesis-silking interval, 100-grain weight, and grain yield were recorded. The results revealed significant differences among families for all traits in both cycles. High heritability (0.88) was observed for days to mid-silking in cycle 0 (C₀), while moderate heritability (0.42) was recorded for 100-grain weight in C₁. The selection differential was quite reasonable and varied according to the traits of interest. The observed response for grain yield in C₀ (815.74 kg/ha) was greater than the expected response (681.76 kg/ha).

Selection and Adaptation to High Plant Density in the Iowa Stiff Stalk Synthetic Maize (Zea mays L.) Population

The plant density at which maize (Zea mays L.) hybrids achieve maximum grain yield has increased throughout the hybrid era, whereas grain yield on a per plant basis has increased little. Changes in grain yield, grain moisture, test weight, and stalk and root lodging have been well characterized in comparisons of commercial hybrids representing different eras of hybrid maize production but have yet to be examined in a recurrent selection program. The objective of this experiment was to determine if direct selection for grain yield and agronomic performance in the Iowa Stiff Stalk Synthetic (BSSS) population has indirectly improved adaptation to high plant density. Material from an unselected base population, BSSS, was compared to the most advanced cycles of selection from three different recurrent selection programs at seven Iowa locations in 2008 and 2009. Populations were compared at densities of 38,300, 57,400, 77,500, and 95,700 plants ha−1. Treatments were replicated twice at each location and arranged in a split plot design. Selection produced notable improvement in adaptation to high plant density for grain yield and stalk lodging. Selection did not have large impacts on density response for root lodging, test weight, or grain moisture. Because of the improvement in density response for grain yield and stalk lodging without major negative changes in other traits, our data suggest that selection has improved adaptation to high plant density in these populations.

Heterotic Response for Grain Yield and Ecophysiological Related Traits to Nitrogen Availability in Maize

ABSTRACTMaize (Zea mays L.) hybrid vigor for plant grain yield (PGY) is associated with heterosis for plant biomass at maturity (aboveground biomass at physiological maturity [BiomassPM]), kernel number per plant (KNP), and harvest index (HI); however, no evidence of the effects of nitrogen (N) availability or combination of abiotic stresses on heterosis for physiological components of PGY has been reported. The objective of this study was to determine the response of heterosis for ecophysiological traits related to PGY at contrasting N supply levels in a set of six inbred lines and 12 derived hybrids. Field experiments were conducted in five growing seasons at low nitrogen (LN; no N added) and high nitrogen (HN) supply (200 or 400 kg N ha−1) under irrigation and dryland farming. Increased PGY (65% for hybrids and 30% for inbreds) was ascribed to similar increase in BiomassPM as no increase in HI was found. Heterosis for PGY was higher under HN (137%) than LN (87%). A similar response was observed for traits related to light capture and biomass accumulation. Heterosis for HI did not differ between HN (31%) and LN (28%). Heterosis for PGY was associated (p < 0.01) with heterosis for KNP, BiomassPM, radiation use efficiency (RUE) during grain filling, HI, and traits related to maximum light capture. Heterosis for PGY at LN was also correlated with heterosis for RUE at critical period (i.e., 30 d bracketing silking) and kernel weight. Under the combined effect of N and drought, PGY heterosis was reduced and more affected at HN (59%) than at LN (70%).

Genetic Analysis of Indirect Selection for Winter Wheat Grain Yield Using Spectral Reflectance Indices

Selection criteria that can facilitate grain yield improvement would be considered important plant breeding tools. We assessed the value of spectral reflectance indices (SRI) as indirect selection tools for grain yield improvement in winter wheat (Triticum aestivum L.). The objectives of this study were to estimate genetic correlation between SRI and grain yield, heritability, response to selection, correlated response of grain yield, and relative selection efficiency of SRI for grain yield improvement. Three field experiments consisting of 25 winter wheat cultivars and 2 sets of 25 recombinant inbred lines were conducted in the Oklahoma State University Agronomy Farm for 2 yr. Eight SRI were calculated at three growth stages (booting, heading, and grain‐filling). The water‐based indices (water index and normalized water indices) showed moderate to high heritability and higher genetic correlations with grain yield compared to the commonly used vegetation‐based indices (normalized difference vegetation index and simple ratio). The water‐based indices also showed higher correlated response than direct response for grain yield. Up to 83% of the top 25% highest‐yielding genotypes were selected by the two newly developed water‐based indices (normalized water index 3 [NWI‐3] and normalized water index 4 [NWI‐4]). These results suggest the strong genetic basis of NWI‐3 and NWI‐4 as potential selection tools for winter wheat grain yield improvement under Great Plains conditions.

Heritability, correlated response, and indirect selection involving spectral reflectance indices and grain yield in wheat

The objectives of this study were to assess the potential of using spectral reflectance indices (SRIs) as an indirect selection tool for grain yield in wheat under irrigated conditions. This paper demonstrates the genetic correlation between grain yield and SRIs, heritability and expected response to selection for grain yield and SRIs, correlated response to selection for grain yield estimated from SRIs, and efficiency of indirect selection for grain yield using SRIs in different spring wheat populations. Four field experiments, GHIST (15 CIMMYT globally adapted genotypes), RLs1 (25 random F3-derived families), RLs2 (36 random F3-derived families), and RLs3 (64 random F5-derived families) were conducted under irrigated conditions at the CIMMYT research station in north-west Mexico in 3 different years. Spectral reflectance was measured at 3 growth stages (booting, heading, and grain filling) and 7 SRIs were calculated using average values of spectral reflectance at heading and grain filling. Five previously developed SRIs (PRI, WI, RNDVI, GNDVI, SR), and 2 newly calculated SRIs (NWI-1 and NWI-2) were evaluated in the experiments. In general, the within- and between-year genetic correlations between grain yield and SRIs were significant. Three NIR-based indices (WI, NWI-1, and NWI-2) showed higher genetic correlations (0.73–0.92) with grain yield than the other indices (0.35–0.67), and these observations were consistent in all populations. Broad-sense heritability estimates for all indices were in general moderate to high (0.60–0.80), and higher than grain yield (0.45–0.70). The realised heritability for the 3 NIR-based indices was higher than for the other indices and for grain yield itself. Expected response to selection for all indices was moderate to high (0.54–0.85). The correlated response for grain yield estimated from the 3 NIR-based indices (0.59–0.64) was much higher than the correlated response for grain yield estimated from the other indices (0.31–0.46), and the efficiency of indirect selection for these 3 NIR-based indices was 90–96% of the efficiency of direct selection for grain yield. These results demonstrate the potential for using the 3 NIR-based SRI tools in breeding programs for selecting for increased genetic gains for yield.

Response to Selection and Genetic Drift in Three Populations Derived from the Golden Glow Maize Population

Reciprocal recurrent selection (RRS) in maize (Zea mays L.) is used to develop populations with superior combining ability, and it is usually assumed that these populations must be genetically distinct for RRS to be effective. Starting from two randomly derived subpopulations, GG(A) and GG(B), of the open‐pollinated maize population ‘Golden Glow’ (GGC0), we conducted six cycles of full‐sib RRS for grain yield and moisture. Our objectives were to (i) document selection response; (ii) evaluate inter and intrapopulation genetic diversity; and (iii) review selection response relative to gene action, heterosis, inbreeding, and genetic drift. We performed a generation means analysis (GMA) using GG(A), GG(B), and a third population of Golden Glow developed by 21 cycles of mass selection for prolificacy, GG(MP). Field performance was evaluated at four environments in Wisconsin. We analyzed allele frequency changes using simple sequence repeats (SSRs) and amplified fragment length polymorphisms (AFLPs). Selection response for grain yield of GG(A) × GG(B) population crosses was 5.3 g plant−1 cycle−1 Grain moisture and root lodging decreased by −0.5% cycle−1 and −5.2% cycle−1, while prolificacy increased by 0.03 ears cycle−1 After six cycles of RRS, GG(A) and GG(B) diverged genetically from each other, as well as from GG(MP)C21 and Golden Glow. Gene diversity within GG(A) and GG(B) decreased. However, total gene diversity over both GG(A) and GG(B) did not change over cycles of RRS. Genetic drift did not appear to seriously impede selection response. Most of the selection response, regardless of trait, selection method, or subpopulation, was attributed to additive genetic effects.

Farmers' seed management practices open up new base populations for pearl millet breeding in a semi‐arid zone of India

AbstractFarmers in western Rajasthan (north‐west India) produce and maintain their landrace populations of pearl millet through their own distinct seed management practices. The objective of this study was to characterize morphological and agronomic variability of different traits between and within three farmers' populations using quantitative‐genetic parameters. Populations examined were a typical landrace and two modified landraces, which were generated through farmer introgression of modern varieties with different levels of subsequent selection. From these three populations, 100 random full‐sib progenies were evaluated in field trials at two locations in western Rajasthan over two years. Significant genetic variation existed within the three populations. Estimates of heritability were moderate to high for all observed traits. Predicted selection response for grain yield across environments was 1.6% for the typical landrace and 2.2% for both the modified landraces. Results suggest that the introgression of modern varieties into landraces had increased the genetic diversity. Therefore, farmers' current breeding activities could open up new resources for plant breeding programmes aiming at plant improvement for the semiarid zones of India.