Indirect Selection Tool Research Articles

Potential of Grain Physical Traits to the Study of Variability in Maize

Aims: The identification of new traits that can be used as phenotypic markers as well as potential indirect selection tools is interesting for plant breeding. The objective of the study was to investigate the potential use of physical traits of grains to study phenotypic variability in maize.
 Methodology: Ten maize varieties were evaluated, one commercial variety and nine local open-pollinated varieties. After harvesting, the following traits were evaluated: mass of 1000 grains, weight of ears, grain yield per hectare, estimated from plot production; real volume and apparent volume; real density and apparent density; sphericity and volumetric weight; obtained in samples of 50 grains of each of the studied varieties. A principal component analysis was performed on the data. First, those traits that showed a strong correlation with components capable of explaining a smaller portion of the total variation were excluded from the analysis. A new principal component analysis was performed with the remaining traits.
 Results: The result revealed the possibility of excluding five of the ten analyzed variables: mass of 1000 grains, weight of ears, apparent volume, real density, and volumetric weight. Some possibilities of trait exclusion can be explained by correlation and method of estimate among them. The genotypes G2 and G3 showed great difference, mainly due the grain yield. The porosity and real volume contributed to the majority variation among genotypes.
 Conclusion: Some physical grain traits showed potential for use in divergence studies. Apparent density can be used in indirect selection strategies for higher grain yield.

Evaluation of the U.S. Peanut Germplasm Mini-Core Collection in the Virginia-Carolina Region Using Traditional and New High-Throughput Methods

Peanut (Arachis hypogaea L.) is an important food crop for the U.S. and the world. The Virginia-Carolina (VC) region (Virginia, North Carolina, and South Carolina) is an important peanut-growing region of the U.S and is affected by numerous biotic and abiotic stresses. Identification of stress-resistant germplasm, along with improved phenotyping methods, are important steps toward developing improved cultivars. Our objective in 2017 and 2018 was to assess the U.S. mini-core collection for desirable traits, a valuable source for resistant germplasm under limited water conditions. Accessions were evaluated using traditional and high-throughput phenotyping (HTP) techniques, and the suitability of HTP methods as indirect selection tools was assessed. Traditional phenotyping methods included stand count, plant height, lateral branch growth, normalized difference vegetation index (NDVI), canopy temperature depression (CTD), leaf wilting, fungal and viral disease, thrips rating, post-digging in-shell sprouting, and pod yield. The HTP method included 48 aerial vegetation indices (VIs), which were derived using red, blue, green, and near-infrared reflectance; color space indices were collected using an octocopter drone at the same time, with traditional phenotyping. Both phenotypings were done 10 times between 4 and 16 weeks after planting. Accessions had yields comparable to high yielding checks. Correlation coefficients up to 0.8 were identified for several Vis, with yield indicating their suitability for indirect phenotyping. Broad-sense heritability (H2) was further calculated to assess the suitability of particular VIs to enable genetic gains. VIs could be used successfully as surrogates for the physiological and agronomic trait selection in peanuts. Further, this study indicates that UAV-based sensors have potential for measuring physiologic and agronomic characteristics measured for peanut breeding, variable rate input application, real time decision making, and precision agriculture applications.

Combining Genetic and Multidimensional Analyses to Identify Interpretive Traits Related to Water Shortage Tolerance as an Indirect Selection Tool for Detecting Genotypes of Drought Tolerance in Wheat Breeding.

Water shortages have direct adverse effects on wheat productivity and growth worldwide, vertically and horizontally. Productivity may be promoted using water shortage-tolerant wheat genotypes. High-throughput tools have supported plant breeders in increasing the rate of stability of the genetic gain of interpretive traits for wheat productivity through multidimensional technical methods. We used 27 agrophysiological interpretive traits for grain yield (GY) of 25 bread wheat genotypes under water shortage stress conditions for two seasons. Genetic parameters and multidimensional analyses were used to identify genetic and phenotypic variations of the wheat genotypes used, combining these strategies effectively to achieve a balance. Considerable high genotypic variations were observed for 27 traits. Eleven interpretive traits related to GY had combined high heritability (h2 > 60%) and genetic gain (>20%), compared to GY, which showed moderate values both for heritability (57.60%) and genetic gain (16.89%). It was determined that six out of eleven traits (dry leaf weight (DLW), canopy temperature (CT), relative water content (RWC), flag leaf area (FLA), green leaves area (GLA) and leaf area index (LAI)) loaded the highest onto PC1 and PC2 (with scores of >0.27), and five of them had a positive trend with GY, while the CT trait had a negative correlation determined by principal component analysis (PCA). Genetic parameters and multidimensional analyses (PCA, stepwise regression, and path coefficient) showed that CT, RWC, GLA, and LAI were the most important interpretive traits for GY. Selection based on these four interpretive traits might improve genetic gain for GY in environments that are vulnerable to water shortages. The membership index and clustering analysis based on these four traits were significantly correlated, with some deviation, and classified genotypes into five groups. Highly tolerant, tolerant, intermediate, sensitive and highly sensitive clusters represented six, eight, two, three and six genotypes, respectively. The conclusions drawn from the membership index and clustering analysis, signifying that there were clear separations between the water shortage tolerance groups, were confirmed through discriminant analysis. MANOVA indicated that there were considerable variations between the five water shortage tolerance groups. The tolerated genotypes (DHL02, DHL30, DHL26, Misr1, Pavone-76 and DHL08) can be recommended as interesting new genetic sources for water shortage-tolerant wheat breeding programs.

Combining Genetic Analysis and Multivariate Modeling to Evaluate Spectral Reflectance Indices as Indirect Selection Tools in Wheat Breeding under Water Deficit Stress Conditions

Progress in high-throughput tools has enabled plant breeders to increase the rate of genetic gain through multidimensional assessment of previously intractable traits in a fast and nondestructive manner. This study investigates the potential use of spectral reflectance indices (SRIs; 15 vegetation-SRIs; 15 water-SRIs) as alternative selection tools for destructively measured traits in wheat breeding programs. The genetic variability, heritability (h2), genetic gain (GG), and expected genetic advances (GA) of these indices were compared with those of destructively measured traits in 43 F7-8 recombinant inbred lines (RILs) grown under limited water conditions. The performance of SRIs to estimate the destructively measured traits directly was also evaluated using the partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR) models. Most vegetation-SRIs exhibited high genotypic variation, similar to the measured traits, and phenotypic correlations with these traits, compared with the water-SRIs. Most vegetation-SRIs presented comparable values for h2 (>60%) and GG (>20%) as intermediate traits, while about half of water-SRIs exhibited a high h2 (>60%), but low GG (<20%). Principle component analysis revealed that most vegetation-SRIs and seven of 15 water-SRIs were grouped together in a positive direction, had a moderate to strong relationship with measured traits, and could identify the drought-tolerant parent Sakha 93 and several RILs. The PLSR model based on all SRIs as a single index showed moderate to high R2 in calibration (0.53–0.75) and validation (0.46–0.72) datasets, with strong relationships between observed and predicted values of measured traits. The SMLR models identified four and three SRIs from vegetation-SRIs and water-SRIs, respectively, to explain 63–86% of the total variability in measured traits among genotypes. These results demonstrated that vegetation-SRIs can be used individually or combined with water-SRIs as alternative breeding tools to increase genetic gains and selection accuracy in spring wheat breeding.

Phosphorus and potassium uptake, translocation, and utilization efficiency in chickpea under Mediterranean conditions

Sowing time and cultivar choice have major effects on chickpea yield in the Mediterranean climate, but the effects on nutrient requirements are not well known. Information regarding nutrient requirements and utilization efficiency by crop species is necessary to optimize nutrient management in agricultural systems. Α two-year field study was conducted to examine the patterns of P and K uptake, translocation, utilization and removal across a wide-range of chickpea yield levels induced by sowing time (March and April) and cultivar [Zehavit-27 (Kabuli-type), Andros, Kassos, and Serifos (desi-type)], as well as to identify plant traits associated with efficient nutrient utilization. At all samplings throughout the growing period, P uptake was significantly correlated with that of K uptake with r values between 0.633 (P < 0.05) and 0.983 (P < 0.01). Both P and K uptake peaked, in terms of uptake rate and net uptake, earlier during the April sowing (early pod filling stage) compared with March sowing (late pod filling stage). Early sowing increased chickpea productivity and total nutrient uptake, but did not offer any advantage in terms of nutrient utilization efficiency. Phosphorus or K translocation to seeds were significantly correlated with P (r = 0.838, P < 0.01) or K (r = 0.861, P < 0.01) accumulation prior to the beginning of seed filling, respectively. PUtE varied from 161 to 422 kg kg−1 and was greater than KUtE (32–101 kg kg−1). Low (leaf + stem)-P or K concentration at maturity could be considered as an indirect selection tool to enhance nutrient utilization efficiency. Seed P or K removal depended on yield level of each cultivar. For a yield level of 2000 kg ha−1, 8.2 kg P ha−1 and 18.9 kg K ha−1 were removed by seed harvest.

Using aerial imagery and digital photography to monitor growth and yield in winter wheat

ABSTRACT Monitoring wheat (Triticum aestivum L.) performance throughout the growing season provides information on productivity and yield potential. Remote sensing tools have provided easy and quick measurements without destructive sampling. The objective of this study was to evaluate genetic variability in growth and performance of 20 wheat genotypes under two water regimes (rainfed and irrigated), using spectral vegetation indices (SVI) estimated from aerial imagery and percentage ground cover (%GC) estimated from digital photos. Field experiments were conducted at Bushland, Texas in two growing seasons (2014–2015 and 2015–2016). Digital photographs were taken using a digital camera in each plot, while a manned aircraft collected images of the entire field using a 12-band multiple camera array Tetracam system at three growth stages (tillering, jointing and heading). Results showed that a significant variation exists in SVI, %GC, aboveground biomass and yield among the wheat genotypes mostly at tillering and jointing. Significant relationships for %GC from digital photo at jointing was recorded with Normalized Difference Vegetation Index (NDVI) at tillering (coefficient of determination, R 2 = 0.84, p< 0.0001) and with %GC estimated from Perpendicular Vegetation Index (PVI) at tillering (R 2 = 0.83, p< 0.0001). Among the indices, Ratio Vegetation Index (RVI), Green-Red VI, Green Leaf Index (GLI), Generalized DVI (squared), DVI, Enhanced VI, Enhanced NDVI, and NDVI explained 37–99% of the variability in aboveground biomass and yield. Results indicate that these indices could be used as an indirect selection tool for screening a large number of early-generation and advanced wheat lines.

Relationship between drought and preharvest aflatoxin contamination in groundnut (Arachis hypogaea L.)

Groundnut is a commercial oilseed crop that is prone to infection byAspergillus flavus orAspergillus parasiticus. Drought impairs the defence mechanism of the plant and favours the production of aflatoxin by the fungus. Aflatoxin is a carcinogen and its presence in food and feed causes significant economic loss. The answer to the question, ‘how drought tolerance and aflatoxin resistance are related?’ is not clear. In this review paper, the relationship of drought and preharvest aflatoxin contamination (AC), the relationship of drought tolerance traits and AC, and the approaches to enhance resistance to AC are discussed using up-to-date literature. Factors leading to AC are drought, high geocarposphere temperature, kernel/pod damage, and reduced phytoalexin synthesis by the plant. If the fungus colonises a kernel with reduced water activity, the plant cannot synthesise phytoalexin and then, the fungus synthesises aflatoxin. Breeding for resistance to AC is complicated because aflatoxin concentration is costly to measure, highly variable, and influenced by the environment. Since drought tolerant cultivars have resistance to AC, traits of drought tolerance have been used as indirect selection tools for reduced AC. The genetics of aflatoxin resistance mechanisms have not been made clear as the environment influences the host-pathogen relationship. Host-pathogen interactions under the influence of environment should be studied at molecular level to identify plant resistant factors using the tools of genomics, proteomics, and metabolomics in order to develop cultivars with durable resistance. Many candidate genes involved in host-pathogen interactions have been identified due to improvements in fungal expressed sequence tags, microarrays, and genome sequencing techniques. Moreover, research projects are underway on identifying genes coding for antifungal compounds, resistance associated proteins and quantitative trait loci associated with aflatoxin resistance. This review is expected to help those who wish to work on reducing AC in groundnuts.

Evaluation of Elite Open-Pollinated Maize Lines in Two Contrasting Environments

Selection environment affects plant behavior and response to selection. The objective of the present study was the evaluation of 17 quality and quantity phenotypic characteristics of six open-pollinated maize lines of fifth cycle of selection (C4), which was performed by the implementation of honeycomb breeding, in two contrasting environments (A and B). A: Florina, W. Macedonia (40o46' N, 21o22' E, altitude 705 m) and B: Trikala, Thessaly (39o55' N, 21o64' E, altitude 120 m), with about 4-10 oC higher temperatures than environment A. The soil chemical analysis revealed that the two environments were very diverse (A: SL, pH = 6.25, organic matter: 1.29%, B: SCL, pH = 8, organic matter: 2.4%). Our data suggest that moisture content, seed oil content, ear length, ear diameter, number of grain rows, spindle diameter and seed thickness exhibit inter-location high broad-sense heritability (over 0.9). Heritability estimations were highly depended on the environment, since GEI interaction was high indicating environmental interaction with genotype, especially environment B, which seems to favor heritability. Location affects strongly variation and genotype by environment interaction is significant in many cases. Seed width was the only characteristic to be depended on genetic variability. Descriptive statistics revealed a broad range of mean fluctuations, indicating satisfactory variability in many characteristics to be exploited by breeders. Some characteristics showed low CV (Coefficient of Variation) values (1.6 to 5.3), indicating stability of performance and low environmental effects. Significant correlations between the 17 quantity and quality traits found in our study may be a useful tool for indirect selection of certain characteristics, otherwise difficult to be selected due to non-additive effects. Cluster analysis and PCA showed contrasting results in classification of open-pollinated lines and this was attributed to strong environmental effects that distorted phenotypic expression of the characteristics studied.

&lt;b&gt;Molecular markers associated with the agronomic traits in the medicinal plant lemon balm

Finding association between molecular markers and agronomic traits provide an excellent tool for indirect selection of a trait of interest in the population. In this study, stepwise regression analysis was used to estimate associations between ISSR and RAPD markers with some agronomic traits in lemon balm ecotypes. The analysis of results revealed significant associations between the traits and some of the studied loci. For all the traits, more than one informative marker was detected. Totally,90informative markers, including 48 ISSR loci and 42 RAPD loci, were identified. The SA-R-10, UBC826-1, UBC812-9, UBC813-10, UBC825-4, OPA-01-15, OPC-04-7 and CS-56-8 markers or fragment showed a significant correlation with Essential oil percentage and controlled 99.8% of the phenotypic variation. These markers are relatively more reliable. Among the RAPD primers, special attention should be drawn to primer SA-R, which had the highest associated fragments with the traits including days for 50% flowering, number of branches per plant, fresh weight and dry weight. Some of ISSR and RAPD markers were associated with more than one trait in multiple regression analysis that may be due to pleiotropic effect of the linked quantitative trait locus on different traits or its linkage to different genes. These primers have been found useful for improved lemon balm.

Identifying Morphological and Mechanical Traits Associated with Stem Lodging in Bioenergy Sorghum (Sorghum bicolor)

Stem lodging in Sorghum is a major agronomic problem that has far-reaching economic consequences. More rapid and reliable advances in stem lodging resistance could be achieved through development of selective breeding tools that are not dependent on post hoc data or dependent on abiotic or biotic environmental factors. Our objective was to use sorghum to examine how mechanical stability is achieved and lost, and to provide insights into the development of a rapid and reliable phenotyping approach. The biomechanical properties of the stems of six bioenergy sorghum genotypes were investigated using a three-point bending test protocol. Important morphometric data were also collected, and previously collected lodging scores were used to associate with morphological and mechanical traits. Nodes were two to three-folds stronger, stiffer, and more rigid than internodes. In general, internodes were numerically weakest and more rigid between internodes 3 and 6, corresponding to the area where higher stem lodging is observed. Internode strength was negatively correlated with diameter (r = −0.77, P < 0.05) and volume (r = 0.96, P < 0.01), while stem lodging was positively correlated with flexural rigidity (r = 0.85, P < 0.05) and volume (r = 0.78, P < 0.05). The analysis revealed key functional traits that influence the mode and location of stem lodging. Moreover, these results indicate the potential of these methods as a selective breeding tool for indirect selection of stem lodging resistance in bioenergy sorghum.

Mendelization and fine mapping of a bread wheat spot blotch disease resistance QTL

The wheat (Triticum aestivum L.) quantitative trait locus (QTL) QSb.bhu-5B, which determines resistance to spot blotch (causative pathogen Bipolaris sorokiniana), was mapped to an interval of 0.62 cM on chromosome arm 5BL via the analysis of a recombinant inbred line population bred from a cross between ‘YS116’ and ‘Sonalika.’ ‘YS116’ is an F12 selection from the cross ‘Yangmai 6’ (source of resistance) × ‘Sonalika,’ which contains only one spot blotch resistance QTL. Lines tested from F3 to F5 were inoculated in the field with B. sorokiniana over three consecutive seasons. Measurements of both disease severity and the area under the disease progress curve were used to assess each line’s disease response. In the present population, QSb.bhu-5B, which is flanked by the SSR loci Xgwm639 (0.28 cM) and Xgwm1043, behaved as a single Mendelian gene and was given the gene symbol Sb2. The physical location of Sb2 is within the 5BL1-0.55-0.75 deletion bin. Both Xgwm1043 and Xgwm639 were effective as indirect selection tools in various genetic backgrounds.

Exploring a Tomato Landraces Collection for Fruit-Related Traits by the Aid of a High-Throughput Genomic Platform.

During its evolution and domestication Solanum lycopersicum has undergone various genetic ‘bottlenecks’ and extreme inbreeding of limited genotypes. In Europe the tomato found a secondary centre for diversification, which resulted in a wide array of fruit shape variation given rise to a range of landraces that have been cultivated for centuries. Landraces represent a reservoir of genetic diversity especially for traits such as abiotic stress resistance and high fruit quality. Information about the variation present among tomato landrace populations is still limited. A collection of 123 genotypes from different geographical areas was established with the aim of capturing a wide diversity. Eighteen morphological traits were evaluated, mainly related to the fruit. About 45% of morphological variation was attributed to fruit shape, as estimated by the principal component analysis, and the dendrogram of relatedness divided the population in subgroups mainly on the basis of fruit weight and locule number. Genotyping was carried out using the tomato array platform SolCAP able to interrogate 7,720 SNPs. In the whole collection 87.1% markers were polymorphic but they decreased to 44–54% when considering groups of genotypes with different origin. The neighbour-joining tree analysis clustered the 123 genotypes into two main branches. The STRUCTURE analysis with K = 3 also divided the population on the basis of fruit size. A genomic-wide association strategy revealed 36 novel markers associated to the variation of 15 traits. The markers were mapped on the tomato chromosomes together with 98 candidate genes for the traits analyzed. Six regions were evidenced in which candidate genes co-localized with 19 associated SNPs. In addition, 17 associated SNPs were localized in genomic regions lacking candidate genes. The identification of these markers demonstrated that novel variability was captured in our germoplasm collection. They might also provide a viable indirect selection tool in future practical breeding programs.

Low ambient temperature elevates plasma triiodothyronine concentrations while reducing digesta mean retention time and methane yield in sheep.

Ruminant methane yield (MY) is positively correlated with mean retention time (MRT) of digesta. The hormone triiodothyronine (T3 ), which is negatively correlated with ambient temperature, is known to influence MRT. It was hypothesised that exposing sheep to low ambient temperatures would increase plasma T3 concentration and decrease MRT of digesta within the rumen of sheep, resulting in a reduction of MY. To test this hypothesis, six Merino sheep were exposed to two different ambient temperatures (cold treatment, 9 ± 1 °C; warm control 26 ± 1 °C). The effects on MY, digesta MRT, plasma T3 concentration, CO2 production, DM intake, DM digestibility, change in body weight (BW), rumen volatile fatty acid (VFA) concentrations, estimated microbial protein output, protozoa abundance, wool growth, water intake, urine output and rectal temperature were studied. Cold treatment resulted in a reduction in MY (p < 0.01); digesta MRT in rumen (p < 0.01), hindgut (p = 0.01) and total digestive tract (p < 0.01); protozoa abundance (p < 0.05); and water intake (p < 0.001). Exposure to cold temperature increased plasma T3 concentration (p < 0.05), CO2 production (p = 0.01), total VFA concentrations (p = 0.03) and estimated microbial output from the rumen (p = 0.03). The rate of wool growth increased (p < 0.01) due to cold treatment, but DM intake, DM digestibility and BW change were not affected. The results suggest that exposure of sheep to cold ambient temperatures reduces digesta retention time in the gastrointestinal tract, leading to a reduction in enteric methane yield. Further research is warranted to determine whether T3 could be used as an indirect selection tool for genetic selection of low enteric methane-producing ruminants.

Evaluation of a semi‐controlled test as a selection tool for frost tolerance in durum wheat (Triticum durum)

AbstractMost durum wheat (Triticum durum) varieties possess only low winter hardiness due to their frost susceptibility. In North America and Central Europe, durum wheat is therefore typically sown in spring to circumvent the local winter conditions. However, the yield potential of durum in these regions could be much better exploited if durum varieties with increased frost tolerance were available, which could be sown in autumn. A factor limiting breeding for increased frost tolerance is the variation in the occurrence of frost stress across years. The ‘Weihenstephaner Auswinterungsanlage’ is a semi‐controlled test that exposes the plants to all weather conditions. Snow coverage of the plants, serving as frost protection, is prevented by the movable glass lid of the semi‐controlled test. In this study, different scorings for frost tolerance based on this semi‐controlled test were evaluated and compared with frost tolerance data in the field. Our results illustrate the potential of the ‘Weihenstephaner Auswinterungsanlage’ as an indirect selection tool for frost tolerance in durum breeding programmes, especially when regular frost tolerance data from the field are not available.

Considerations When Deploying Canopy Temperature to Select High Yielding Wheat Breeding Lines under Drought and Heat Stress

Developing cultivars with improved adaptation to drought and heat stressed environments is a priority for plant breeders. Canopy temperature (CT) is a useful tool for phenotypic selection of tolerant genotypes, as it integrates many physiological responses into a single low-cost measurement. The objective of this study was to determine the ability of CT to predict grain yield within the flow of a wheat breeding program and assess its utility as a tool for indirect selection. CT was measured in both heat and drought stressed field experiments in northwest Mexico on 18 breeding trials totaling 504 spring wheat lines from the International Maize and Wheat Improvement Center (CIMMYT) Irrigated Bread Wheat program. In the heat treatment, CT was significantly correlated with yield (r = −0.26) across all trials, with a maximum coefficient of determination within the individual trials of R2 = 0.36. In the drought treatment, a significant correlation across all trials was only observed when days to heading or plant height was used as a covariate. However, the coefficient of determination within individual trials had a maximum of R2 = 0.54, indicating that genetic background may impact the ability of CT to predict yield. Overall a negative slope in the heat treatment indicated that a cooler canopy provided a yield benefit under stress, and implementing selection strategies for CT may have potential for breeding tolerant genotypes.

Multivariate Analysis as a Tool for Indirect Selection of Common Bean Genotypes (&lt;i&gt;Phaseolus vulgaris L&lt;/i&gt;) for Soil Acidity Tolerance under Field Conditions

A field experiment was conducted to evaluate soil acidity tolerance of 25 common bean (Phaseolus vulgaris L.) genotypes on lime-treated and lime-untreated acid soils. The twenty-five common bean genotypes were tested in a randomized complete block design with two replications per treatment in 2009 in western Ethiopia. Morpho-agronomic parameters were recorded to evaluate the genotypes. Multivariate methods, including principal component and cluster analysis were used to assess the patterns of morpho-agronomic variation to group the genotypes into distinct categories. The genotype bi trait (GT) bi-plot was used to identify the best traits that are important to identify tolerant genotype and to know the relationships between traits and genotypes. The principal component analysis indicated that the first three principal components contributed 64.6 and 66.1% of the total variability among the 25 common bean genotypes grown on the lime-untreated and lime-treated soils, respectively. Among the measured traits, plant height, number of pods per plant, days to pod setting, grain yield, days to flowering and maturity, biomass yield, and 100 seed weight were the parameters that most significantly caused the variations among the genotypes. Genotype by trait (GT) bi-plot led to grouping of the tested genotypes into four categories based on PC1 and PC2 values and also enabled to identify traits such as number of pods per plant, plant height, pod length, 100 seed weight, and grain yield, which were found to be the most responsive characters in evaluating the genotypes for tolerance to soil acidity. The cluster analysis led to classification of the 25 common bean genotypes in to four groups, the first group (cluster) of which contained four genotypes of BILFA material (new BILFA 38, new BILFA 58, New BILFA 61, and new BILFA 60) that outperformed genotypes in the other group (clusters) when grown on lime-untreated acid soil. In conclusion, the results of this study have revealed that multivariate analysis can be used as an indirect method of selecting high-yielding common bean genotypes having the most important desirable traits that contribute to soil acidity tolerance.

Genetic parameters for early growth and biomass traits of Pinus radiata D. Don under different water regimes

AbstractIn Chile, genetic improvement of Radiata pine has been directed towards characters such as volume, form and wood density. Estimation of genetic parameters for growth and biomass traits in young seedlings, as a tool for early indirect selection in the P. radiata breeding program, has not been explored yet. We aimed to estimate genetic parameters for growth and biomass traits. Five-month-old P. radiata seedlings grown under wellwatered (WW) and water stress (WS) regimes were evaluated. Root collar diameter, height, shoot dry weight, root dry weight, total dry weight, height/diameter ratio and root/shoot ratio were analyzed in both treatments. Trait with the highest heritability was root/shoot ratio in WW and WS regime (h2= 0.80 and 0.63 respectively). The highest genetic correlation was between height and shoot dry weight (rg= 0.90), under WW regime. In contrast, there were negative genetic correlations between root collar diameter and height/diameter ratio under WS regime. To breed for drought tolerance, traits such as height and root collar diameter would be effective targets for indirect selection since estimated heritabilities are high, there is sizable genetic variation, they are easily assessed, they can be measured non-destructively and they have a high genetic correlation with root/shoot ratio, a trait related to drought tolerance. The measurement of dry weights for early selection purposes is not recommended.

Associations between physiological traits for drought tolerance and aflatoxin contamination in peanut genotypes under terminal drought

With 1 figure and 4 tables AbstractTerminal drought induces preharvest aflatoxin contamination (PAC) in peanut. Drought resistance traits are promising as indirect selection tools for improving resistance to PAC. The objectives of this study were to determine the effects of terminal drought on PAC and to investigate the associations between surrogate traits for drought tolerance and PAC. Field tests under rainout shelters were conducted in the dry seasons 2004/2005 and 2005/2006. Eleven peanut genotypes were evaluated under irrigated and terminal drought conditions. Data were recorded for physiological traits, total biomass, pod yield, Aspergillus flavus colonization and PAC. ICGV 98305, ICGV 98330, ICGV 98348, ICGV 98353 and Tifton‐8 had low aflatoxin contamination in both years. Traits related to drought resistance were associated well with those related to PAC under drought conditions. Specific leaf area, relative water content, chlorophyll density and drought stress ratings are the best traits for use as indirect selection tools for lower PAC. Breeding for drought tolerance using these traits as selection criteria may help to accelerate progress in developing resistance to PAC.

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.