Effects of N and K fertilizers on durum wheat quality in different environments

Eight genotypes from two different genetic pools (high yielding varieties and landraces) were assessed for grain yield (GY) and for five quality traits: protein content (P), thousand kernel weight (TKW), yellow berry (YB), gluten content (G_c) and gluten index (G_i) in sub-humid and semi-arid areas using four combinations of nitrogen and potassium fertilizers during two cropping seasons. Genotype × Environment × Fertilizers (G × E × F) was significant only for protein content (p < 0.05); and E × F was found significant (p < 0.05) for all parameters. Greater quality related traits expression was noted in the semi-arid areas for both genetic pools. Excessive rainfall in semi-arid areas resulted in gluten elasticity reduction. N-fertilizers seemed to enhance protein content and to reduce thousand kernel weight. K-fertilizer, might enhance the increase in both proteins and thousand kernel weight in favorable growing conditions of water availability. Semolina yielding ability was higher in landraces as compared to high yielding varieties particularly using recommended fertilizer management. This group of cultivars showed superiority over high yielding cultivars for quantitative quality parameters.     

Genotype-by-environment interactions for grain yield associated with water availability at flowering in rainfed lowland rice

While a large genotype-by-environment (G × E) interaction component of variance for grain yield (GY) has been widely reported for rainfed lowland rice, the reasons for such large interactions are not well known. A random reference population of 34 genotypes taken from the Cambodian rice improvement program was used to examine the magnitude and nature of G × E interactions for GY in Cambodia. These genotypes were evaluated in a multi-environment trial (MET) conducted across 3 years (2000–2002) and eight locations in the rainfed lowlands. The G × E interaction was partitioned into components attributed to genotype-by-location (G × L), genotype-by-year (G × Y) and genotype-by-location-by-year (G × L × Y) interactions. The G × L × Y interaction was the largest component of variance for GY. The G × L interaction was also significant and comparable in size to the genotypic component (G). The significant G component was partly explained by a group of four genotypes that were broadly adapted to different environmental conditions represented by three environmental groups. The three environmental groups were identified from a pattern analysis, and the grouping was partly related to the time of sowing, and hence water availability at flowering. A major factor contributing to the large G × L × Y interactions for GY was late maturing genotypes being affected greatly when soil water availability at flowering was reduced greatly, compared to earlier maturing genotype groups. While the differential genotypic responses to the water availability environment explained part of a large G × E interaction for GY, other non-water related environmental conditions also appeared to have contributed to the interaction. Three target environments were identified for focusing efforts of the breeding programs in Cambodia, and four putative genotypes were selected for their high yield and wide adaptation in the rainfed lowlands.     

Estimation of lucerne yield stability for enabling effective cultivar selection under rainfed conditions

Evaluation of crop and forage yield stability is of increasing relevance in the context of current and recent environmental changes but, in contrast to other field crops, there are no published systematic analyses among forage crops in Europe. A study of stability performance was conducted with 13 Czech cultivars of lucerne at four locations over a 2‐year period with the following aims: (a) to evaluate yield stability of varieties across different environments and (b) to calculate measurable benefits of variety selection in relation to the specific environment. The cultivar Vlasta was identified as the highest yielding cultivar (annual yield 16.0 t DM/ha), whereas the lowest yielding cv. Magda, Tereza and Oslava averaged around 14.9 t DM/ha. Effect of genotype × environment interaction (G × E) was two times higher than for genotype alone. Additive main effects and the multiplicative interaction (AMMI) model showed that the highest yielding cultivars may not be stable across environments. This study demonstrated further that significant yield improvement could be detected, even among a relatively homogenous group of domestic cultivars, and this was driven mainly by site productivity: the improvement was +10% in low‐yielding sites, compared with +3% in high‐yielding sites. Results highlight that advanced agronomy should also consider stability parameters such as AMMI stability value or superiority measures for forage crops in response to the challenges associated with climate change.     

Kernel morphometric traits in hexaploid wheat (Triticum aestivum L.) are modulated by intricate QTL × QTL and genotype × environment interactions

Wheat kernel size and shape influence its flour yield and market price. A hexaploid wheat population of 185 recombinant inbred lines was evaluated for five kernel morphometric traits namely, 1000-kernel weight, kernel length, width, length–width ratio and factor form density in two diverse agro-climatic regions in India in five to eight year–location combinations. Additive main effects and multiplicative interaction analysis revealed significant contributions from genotype (G) and genotype × environment (G × E) effects for these traits. Quantitative trait locus (QTL) analysis by composite interval mapping (CIM) was performed using a linkage map of 251 SSR markers and 59 QTLs distributed on 16 chromosomes were identified. The majority of the QTLs were located on the D genome (44.07%) and the homeologous chromosomes of Group 2 (38.98%). Stable QTLs detected in three or more year–location combinations were identified for four traits. Multi-trait CIM showed 10 chromosomal regions harboring putative pleiotropic loci. Complexity in the genetic effects was further revealed by QTL analysis based on mixed-linear model that indicated 19 QTLs with significant individual effects (main-effect QTLs) and 14 QTL × QTL interactions. Five of these nineteen main-effect QTLs and one of the fourteen QTL × QTL interactions showed environmental influence.     

Genotype × environment interactions for shoot fly resistance in sorghum (Sorghum bicolor (L.) Moench): Response of recombinant inbred lines

Sorghum shoot fly (Atherigona soccata) is a serious pest that destabilizes the performance of sorghum cultivars and ultimately reduces sorghum production in many parts of the world. Identifying sorghum genotypes with stable resistance to shoot fly is important as it helps to reduce the cost of cultivation and stabilizes yields. In the present study, our objective was to identify stable shoot fly resistant genotypes among 385 recombinant inbred lines (RILs) of a cross between a susceptible parent and a resistant parent. We evaluated this set of RILs in eight environments over three years (2006-2008) for shoot fly resistance and component traits. Non-significant genotype-environment (G × E) linear component and significant pooled deviation for deadheart percentage indicated that the performance of genotypes was unpredictable over the environments. However, five lines had deadheart percentages much less than the population mean with regression coefficient (bi) values close to unity, and non-significant deviation from regression, indicating that they have stable shoot fly resistance and are well adapted to all the environments. Additive main effect and multiplicative interaction (AMMI) analysis partitioned main effects into genotype, environment and G × E interacts with all the components showing highly significant effects (p < 0.001). Environment had the greatest effect (69.2%) followed by G × E interactions (24.6%) and genotype (6.2%). Low heritability and high environmental influence for deadheart percentage suggested that shoot fly resistance is a highly complex character, emphasizing the need for marker assisted selection. We observed transgressive variation in the RIL population for all the traits indicating the contribution of alleles for resistance from both resistant and susceptible parents. Since the alleles for shoot fly resistance are contributed by both resistant and susceptible parents, efforts should be made to capture favourable alleles from resistant and susceptible genotypes.     

Influence of genotype and environment on the content of 5-n alkylresorcinols,total phenols and on the antiradical activity of whole durum wheat grains

The 5-n-alkylresorcinol (AR) contents of thirty different cultivars of durum wheat grown in two years (2009 and 2010) in two Italian locations were determined and related to the total soluble phenolic content (TPC) and antiradical activity (AA). On average, AR and TPC ranged from 161.3 to 405.8 μg/g (dry matter, DM) and from 19.0 to 192.4 μg/g (DM), respectively. AA (EC₅₀ values) ranged from 70.9 to 289.2 mg of dry whole milled wheat grain (DM). The results showed that the environment (E) and the genotype (G), as well as their interactions (G × E), significantly influenced the phytochemical profiles of the samples. The contribution of G × E to the total variance was much lower than that due to the separate effects (G and E). Principal component analysis identified genotypes that were richer in ARs and more stable across environments. There were significant negative correlations between ARs and TPC (p < 0.05) and between TPC and AA (p < 0.01), but not between ARs and AA. Graphical representation was efficient in summarizing the overall antiradical profiles of the durum wheat grain in each environment.     

Multi-environment field testing for identification and validation of genetic resistance to Botrytis cinerea causing Botrytis grey mold in chickpea (Cicer arietinum L.)

Botrytis grey mould (BGM), caused by Botrytis cinerea Pers. Ex. Fr., is a destructive foliar disease of chickpea (Cicer arietinum L.) worldwide. Disease management through host-plant resistance is the most effective and economic option to manage this disease. The objective of this study was to identify new sources of resistance to BGM, validate their stability across environments and determine the magnitude of G × E interaction. One hundred and nine chickpea genotypes with moderate levels of resistance (BGM severity ≤5.0 on a 1–9 scale) were selected from the preliminary evaluation of 412 genotypes including germplasm and breeding lines under controlled environmental conditions in 2004–2005 at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India. In order to validate resistance stability, an ‘International Botrytis Grey Mould Nursery’ (IBGMN) was constituted with 25 genotypes and tested in multi-environments for BGM resistance at two locations (Gurdaspur and Pantnagar) in India for 4 years and two locations (Tarahara and Rampur) in Nepal for 3 years. Additive main effects and multiplicative interaction (AMMI) analysis showed significant genotype (G), environment (E) and G × E interaction (p < 0.0001) with largest contribution by environment (47.36%). The first two principal component axes were significant, and contributed 48.21% to the total G × E interaction. The AMMI biplot analysis allowed the selection of five genotypes ICCV 96859, ICCV 96853, ICCV 05604, ICCV 96852 and ICCV 05605 with low BGM severity (between 3.7 and 4.7 on 1–9 scale) and moderate stability. Genotype ICCV 96859 having least disease severity and moderate stability could be highlighted and exploited in chickpea resistance breeding programmes.     

Effect of genotype and environment on flavonoid concentration and profile of black sorghum grains

In recent years, colored sorghum genotypes high in flavonoids have been developed. Flavonoid levels of eight black sorghum genotypes grown in four locations in Texas were evaluated to assess the relative genotype, environment and genotype × environment effects. Levels of total 3-deoxyanthocyanidins ranged from 292 μg/g to 499 μg/g and 251 μg/g to 804 μg/g across environments and genotypes, respectively. Total 3-deoxyanthocyanidins in sorghums from Halfway were low (178–694 μg/g) due to the reduction of their non-methoxylated forms. This reduction is likely due to significant grain weathering which was observed only at Halfway. In addition, flavanone and flavone levels were the lowest at Halfway with levels of 12 μg/g and 78 μg/g, respectively. For all flavonoids there was a genotype by environment interaction (p < 0.01) which suggests that environment had a different effect on flavonoid levels depending on the genotype. Color values L*, a* and b* did not correlate with flavonoid content. Due to genotype, environment and their interactions, sorghum breeders must evaluate these traits in multiple environments to identify genotypes with high and stable production of flavonoid compounds.     

Large deformation stress relaxation and compression-recovery of gluten representing different wheat classes

Despite the great variety of physicochemical and rheological tests available for measuring wheat flour, dough and gluten quality, the US wheat marketing system still relies primarily on wheat kernel hardness and growing season to categorize cultivars. To better understand and differentiate wheat cultivars of the same class, the tensile strength, and stress relaxation behavior of gluten from 15 wheat cultivars was measured and compared to other available physicochemical parameters, including but not limited to protein content, glutenin macropolymer content (GMP) and bread loaf volume. In addition, a novel gluten compression–relaxation (Gluten CORE) instrument was used to measure the degree of elastic recovery of gluten for 15 common US wheat cultivars. Gluten strength ranged from 0.04 to 0.43 N at 500% extension, while the degree of recovery ranged from 5 to 78%. Measuring gluten strength clearly differentiated cultivars within a wheat class; nonetheless it was not a good predictor of baking quality on its own in terms of bread volume. Gluten strength was highly correlated with mixograph mixing times (r = 0.879) and degree of recovery (r = 0.855), suggesting that dough development time was influenced by gluten strength and that the CORE instrument was a suitable alternative to tensile testing, since it is less time intensive and less laborious to use.     

The influence of drought and heat stress on the expression of end-use quality parameters of common wheat

The effects of drought and heat stress on quality parameters of wheat (Triticum aestivum) cultivars were studied under field conditions in a 2-year trial (2009–2010) in northwest Mexico. Under no stress conditions, rapid small-scale parameters [protein (GP; FP) content, SDS sedimentation (SDSS), mixograph peak time (MPT), swelling index of glutenin (SIG), and lactic acid retention capacity (LARC)] showed significant relationship with gluten strength (alveograph energy, W) and bread loaf volume (LV). SIG and LARC were better than SDSS and MPT for predicting W, while SDSS was better than W and SIG for predicting bread LV. Most quality traits were primarily controlled by genotype (G), although environment (E) and G × E also had significant effects. Heat and drought stress showed contrasting effects on LARC, MPT, alveograph parameters [tenacity (P), extensibility (L), P/L ratio, W] and LV. Increase in P and decrease in L resulted in higher tenacity (larger P/L), which may explain the smaller loaf volume under drought stress. In contrast, decrease in P and increase in L, may explain the improved bread volume observed under heat stress. It is advisable to select for wheat quality under both favorable and abiotic stress conditions to identify genotypes with quality stability across environments.     

Effect of Genotype,Environment and Their Interaction on Quality Parameters of Wheat Breeding Lines of Diverse Grain Hardness

Abstract

Understanding the contribution of genotype, environment and genotype-by-environment interaction to wheat grain quality facilitates the selection for quality in breeding programs. Stability of grain quality characteristics is an important requirement in the baking industry. We assessed 24 winter wheat genotypes with different grain hardness in multienvironment trials at four locations and two levels of fertilization in each location. Grain samples were analyzed for hardness, protein and starch content, and wet gluten content, Zeleny sedimentation value, alveograph parameter (W) and hectoliter weight. All parameters were evaluated on whole grains using the near infrared transmittance technique. Differences between hard and soft genotypes appeared to be significant, apart from grain hardness, for protein content, Zeleny test and alveograph parameter. Genotype was found to have a major influence only on grain hardness; for protein content, wet gluten and Zeleny sedimentation value environment prevailed the influence of genotype, and for starch content, alveograph W parameter and hectoliter weight both sources of variation had similar importance. Genotype-by-environment interaction was of smaller size relative to genotype and environment in terms of all the studied quality parameters. Stable genotypes predominate the breeding lines studied. Response of unstable genotypes to environmental conditions was nonlinear in most cases.     

Interpretation of genotype × environment interactions of sugarcane: Identifying significant environmental factors

An understanding of the causes of genotype × environment (G × E) interactions is essential for the implementation of efficient selection and evaluation networks. Currently, studies involving the interpretation of sugarcane (Saccharum spp.) G × E interactions are limited. The objective of this study was to investigate the relative influence of environmental factors on the G × E interactions of sugarcane under rainfed conditions in South Africa through a comprehensive analysis of a multi-environment trial (MET) dataset. Fifteen commercial cultivars were evaluated over 147 environments (trial × ratoon combinations) across the coastal (C), hinterland (H) and midlands (M) regions of the sugar industry. Environments were characterized according to five site covariates (soil depth, clay percentage, organic matter percentage, nitrogen mineralization category, and total available moisture) and nine seasonal covariates (time of harvest, age at harvest, average daily heat units, solar radiation, rainfall, evaporation, and three derived water stress indices).Additive main effects and multiplicative interaction (AMMI) biplots for cane yield (TCANE), estimated recoverable crystal percent (ERC) and tons ERC (TERC) revealed overlapping of C and H environments, while M environments formed unique clusters characterized by specific cultivar adaptabilities. Principal components analysis (PCA) allowed visualization of the covariates determining the regional separation patterns. AMMI interaction principal components axes (IPCA) 1 and 2 scores were correlated to the covariates and showed that harvest age, temperature, and water stress were mainly responsible for separation of M environments from C and H environments on the TCANE and TERC biplots. Time of harvest was identified as an important covariate influencing ERC G × E patterns in the C and H regions. The third water stress index (based on a ratio of observed yields to simulated irrigated yields) was a dominant factor influencing G × E patterns within the C and H regions and was identified as a superior indicator of water deficient environments for future studies. The M trials were characterized by shallower soils with lower total available moisture and greater variability in this regard compared with the C and H trials. Nitrogen mineralization category, organic matter percent, and clay percent were not significantly correlated to IPCA scores, while soil depth was identified as a major site selection criterion in the M region. The M region should be treated as a single mega-environment, while the C and H regions could be combined for future interpretive studies, where covariates should be summarized within growth phases. The results of this study will assist in restructuring the MET network through exploitation and targeting of the relevant environmental factors within the different regions.     

Genetic improvement of sorghum for grain mould resistance: I. Performance of sorghum recombinant inbred lines for grain mould reactions across environments

Grain mould on sorghum is an important disease worldwide, which causes considerable qualitative and quantitative damage. Success in breeding for grain mould resistance has been limited because of many mechanisms governing resistance, complex genetics and environmental influence. Objectives of this study were to characterize 200 recombinant inbred lines (RILs) from a cross between ‘296 B’ (susceptible elite parent) and ‘B 58586’ (resistant parent) for grain mould reaction (GMR) at physiological maturity (PM) and at harvest maturity (HM), and to identify sources of resistance. The RILs were characterized in six environments (3 years × 2 locations) for GMR. Five RILs were identified with GMR on par with the resistant parent across various environments. The results of stability analysis for GMR at PM and HM stages showed difference. At PM, there was a significant genotype (G) × environment (E) (linear) interaction plus significant environmental effects for GMR. However, at HM, there was not a significant G × E (linear) interaction but environment effects were significant for GMR. These indicated that part of variation was predictable at PM while the variation was not predictable at HM as it was entirely influenced by environment. It is concluded that grain mould occurring before PM is influenced by genetics and to some extent by environment while that occurring after PM is influenced by environment. Therefore, host plant resistance would be better assessed at PM than at HM, and identification of quantitative trait loci (QTL) which show consistency in expression across environments, even in diverse environments, would be desirable for marker-assisted selection programs.     

Improving the baking quality of bread wheat using rapid tests and genomics: The prediction of dough rheological parameters by gluten peak indices and genomic selection models

The measurement of baking quality by dough mixing and viscoelastic tests is often labor-intensive and time-consuming, thus the possibility to predict these rheological parameters either by rapid tests or genomic selection models based on molecular markers was investigated in this study. A winter wheat breeding population of 128 genotypes was measured for its rheological parameters, gluten peak indices and other rapid test variables in multiple environments. The prediction accuracy of the rheological parameters was assessed in different cross-validation schemes, reflecting scenarios encountered either in food-processing or by plant breeders. Predictions based on gluten peak indices (r = 0.41–0.82) outperformed the other investigated rapid tests in the food-processing scenario. The combination of gluten peak indices with sedimentation value and protein content gave furthermore the overall highest prediction accuracy (r = 0.70). Cross-validation results from the plant breeding scenario revealed that the prediction accuracy of genomic selection models was merely slightly lower (r = 0.42) than using a combination of sedimentation value and protein content (r = 0.44). Merging gluten peak indices with genomic estimated breeding values resulted in a higher accuracy than either method alone (r = 0.52), and was a promising strategy to select for baking quality in wheat breeding.     

Heat and drought stress on durum wheat: Responses of genotypes,yield, and quality parameters

Heat and/or drought stress during cultivation are likely to affect the processing quality of durum wheat (Triticum turgidum L. ssp. durum). This work examined the effects of drought and heat stress conditions on grain yield and quality parameters of nine durum wheat varieties, grown during two years (2008–09 and 2009–10). Generally, G and E showed main effects on all the parameters whereas the effects of G × E were relatively small. More precipitation in Y09–10 may account for the large differences in parameters observed between crop cycles (Y08–09 and Y09–10). Combined results of the two crop cycles showed that flour protein content (FP) and SDS sedimentation volume (SDSS) increased under both stress conditions, but not significantly. In contrast the gluten strength-related parameters lactic acid retention capacity (LARC) and mixograph peak time (MPT) increased and decreased significantly under drought and heat stress, respectively. Drought and heat stress drastically reduced grain yield (Y) but significantly enhanced flour yellowness (FY). LARC and the swelling index of glutenin (SIG) could be alternative tests to screen for gluten strength. Genotypes and qualtiy parameters performed differently to drought and heat stress, which justifies screening durum wheat for both yield and quality traits under these two abiotic stress conditions.     

Influencing factors of sodium dodecyl sulfate sedimentation in bread wheat

Bread wheat elite lines and F4 populations were evaluated to determine the influence of genotype and environment on variation in sodium dodecyl sulphate (SDS) sedimentation, and the relation between SDS sedimentation and other quality characteristics. Nine intermediate hard red wheat elite lines and two checks were evaluated for three years over eight locations, and six F4 populations and two hard red wheat checks were evaluated at three locations. In both sets of material, the genotype and location main effect, and genotype × location interaction were highly significant. The genotype component contributed 85.96% of the total variation in SDS sedimentation in the F4 material, and the genotype × location component only 12.87%. In the elite material the contribution of genotype was high enough to make effective selection for SDS sedimentation possible. The genotype × year effect was large, indicating that testing genotypes across years may be more important than across locations. SDS sedimentation was significantly positively correlated with protein content and mixograph development time, and negatively with yield. Selection of higher SDS sedimentation may lead to overly strong dough and lower yields. Therefore a careful approach should be taken in the selection process, balancing the different objectives in a breeding program.     

Multiple-disease resistance in Vicia faba: Multi-environment field testing for identification of combined resistance to rust and chocolate spot

The aim of this work was to identify Vicia faba germplasm resistant both to rust and chocolate spot. A collection of 43 accessions of V. faba previously identified as chocolate-spot resistant was evaluated for rust and chocolate spot resistance in Egypt and in Spain. The genotype and genotype × environment (GGE) biplot analyses allowed the selection of 11 accessions resistant to both diseases in those locations. These 11 accessions were evaluated for rust in an additional field trial in Spain, all performing better than the susceptible check. The joint analysis of the 11 accessions in the four field trials where they had been evaluated revealed no significant effects either for genotype, environment or the genotype × environment interaction. They are hence promising sources of resistance, both for their low severities and their stable responses across the studied environments. This collection was also tested under controlled conditions against the Egyptian and the Spanish isolates of rust present in the field trials further underlining the stable performance of these genotypes. Finally, the effect of previous infection with chocolate spot on rust resistance was assessed under controlled conditions and no influence of it was found.     

Grain concentrations of protein and mineral nutrients in a large collection of spelt wheat grown under different environments

A large number of spelt wheat genotypes (ranging from 373 to 772) were evaluated for grain concentrations of protein and mineral nutrients under 6 different environments. There was a substantial genotypic variation for the concentration of mineral nutrients in grain and also for the total amount of nutrients per grain (e.g., content). Zinc (Zn) showed the largest genotypic variation both in concentration (ranging from 19 to 145 mg kg⁻¹) and content (ranging from 0.4 to 4.1 μg per grain). The environment effect was the most important source of variation for grain protein concentration (GPC) and for many mineral nutrients, explaining between 37 and 69% of the total sums of squares. Genotype by environment (G × E) interaction accounted for between 17 and 58% of the total variation across the minerals. GPC and sulfur correlated very significantly with iron (Fe) and Zn. Various spelt genotypes have been identified containing very high grain concentrations of Zn (up to 70 mg kg⁻¹), Fe (up to 60 mg kg⁻¹) and protein (up to 30%) and showing high stability across various environments. The results indicated that spelt is a highly promising source of genetic diversity for grain protein and mineral nutrients, particularly for Zn and Fe.     

Genetic variation and environmental effects on agronomical and commercial quality traits in the main European market classes of dry bean

Repeated testing of diverse commercial classes of beans over time and space and selection for a minimal degree of genotype × environment interaction (GEI) is a common feature of all plant breeding programs. The GEI effect limits the accuracy of yield estimates and complicates the identification of specific genotypes suited for specific environments. The purpose of this work was to study GEI on yield of the main European dry bean market classes by the site regression (SREG) and multiple trait data by genotype–trait (GT) methods, which graphically displayed the interrelationships among traits and facilitated visual comparison of genotypes. Sixty-seven genotypes of common bean, grown in three different sites in northwestern Spain during the 2001 and 2002 growing seasons, were evaluated for yield, two phenological and four commercial seed traits. Interactions between GEI and yield were established using a SREG analysis model to generate a genotype–GEI (GGEI) biplot. The GGEI biplot revealed GEI as a major source of bean yield variation and the different growing sites served to discriminate among the genotypes. This method provided information on the three growing sites: Lugo was identified as the location that best represents the target environment for seed yield; Pontevedra was the location showing the greatest yield stability and León separated the genotypes clearly although as this was not consistent over other sites, León was not representative of an average environment. Each site was represented by a group of genotypes, which showed a superior performance. Large-seed genotypes of the favada market class were best suited to the Lugo site. Commercial seed traits (seed coat fraction, water absorption, crude protein content and seed weight) and days to maturity showed wide variation, as indicated by the relative length of their vectors in the GT plot. Genotypes with the highest yield showed the highest protein content and the poorest seed coat quality and were the latest to flower, while the genotypes that exhibited a high seed coat fraction had the poorest water absorption capacity. The results presented in this work permitted the identification of optimal adapted dry bean genotypes for each bean producing area. These high-yielding genotypes with a good commercial seed quality merit special attention as they could have potential applications for the development of breeding strategies.     

Effect of the grain protein content locus Gpc-B1 on bread and pasta quality

Grain protein concentration (GPC) affects wheat nutritional value and several critical parameters for bread and pasta quality. A gene designated Gpc-B1, which is not functional in common and durum wheat cultivars, was recently identified in Triticum turgidum ssp. dicoccoides. The functional allele of Gpc-B1 improves nitrogen remobilization from the straw increasing GPC, but also shortens the grain filling period resulting in reduced grain weight in some genetic backgrounds. We developed isogenic lines for the Gpc-B1 introgression in six hexaploid and two tetraploid wheat genotypes to evaluate its effects on bread-making and pasta quality. In common wheat, the functional Gpc-B1 introgression was associated with significantly higher GPC, water absorption, mixing time and loaf volume, whereas in durum wheat, the introgression resulted in significant increases in GPC, wet gluten, mixing time, and spaghetti firmness, as well as a decrease in cooking loss. On the negative side, the functional Gpc-B1 introgression was associated in some varieties with a significant reduction in grain weight, test weight, and flour yield and significant increases in ash concentration. Significant gene × environment and gene × genotype interactions for most traits stress the need for evaluating the effect of this introgression in particular genotypes and environments.