Genetic parameters for productive life traits and reproductive efficiency traits at 6 years in Nellore cattle

The objective of the present study was to estimate (co)variance components for length of productive life (LPL) and some alternative reproductive traits of 6-year-old Nellore cattle. The data set contained 57,410 records for age at first calving from Nellore females and was edited to remove animal records with uncertain paternity and cows with just one piece of calving information. Only animals with age at first calving ranging from 23 to 48 months and calving intervals between 11 and 24 months were kept for analysis. LPL and life production ( LP) were used to describe productive life. LPL was defined as the number of months a cow was kept in the herd until she was 6 years old, given that she was alive at first calving and LP was defined as total number of calves in that time. Four traits were used to describe reproductive traits: two breeding efficiencies on original scale were estimated using Wilcox and Tomar functions (BEW and BET, respectively), and two breeding efficiencies transformed (ASBEW and ASBET, respectively), using the function [arcsine (square root (BEi/100))]. Estimates of heritability for measures of LPL and LP were low and ranged from 0.04 to 0.05. Estimates of heritability for breeding efficiencies on original and transformed scales oscillated from 0.18 to 0.32. Estimates of genetic correlations ranged from -0.57 to 0.79 for LPL and other traits and from 0.28 to 0.63 for LP and other traits.

Sorghum Crop Modeling and Its Utility in Agronomy and Breeding

Crop models are simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system. Sorghum crop modeling has evolved in parallel with crop modeling capability in general, since its origins in the 1960s and 1970s. Here we briefly review the trajectory in sorghum crop modeling leading to the development of advanced models. We then (i) overview the structure and function of the sorghum model in the Agricultural Production System sIMulator (APSIM) to exemplify advanced modeling concepts that suit both agronomic and breeding applications, (ii) review an example of use of sorghum modeling in supporting agronomic management decisions, (iii) review an example of the use of sorghum modeling in plant breeding, and (iv) consider implications for future roles of sorghum crop modeling. Modeling and simulation provide an avenue to explore consequences of crop management decision options in situations confronted with risks associated with seasonal climate uncertainties. Here we consider the possibility of manipulating planting configuration and density in sorghum as a means to manipulate the productivity–risk trade-off. A simulation analysis of decision options is presented and avenues for its use with decision-makers discussed. Modeling and simulation also provide opportunities to improve breeding efficiency by either dissecting complex traits to more amenable targets for genetics and breeding, or by trait evaluation via phenotypic prediction in target production regions to help prioritize effort and assess breeding strategies. Here we consider studies on the stay-green trait in sorghum, which confers yield advantage in water-limited situations, to exemplify both aspects. The possible future roles of sorghum modeling in agronomy and breeding are discussed as are opportunities related to their synergistic interaction. The potential to add significant value to the revolution in plant breeding associated with genomic technologies is identified as the new modeling frontier.

Quantitative trait loci for agronomic and seed quality traits in an F-2 and F-4 : 6 soybean population

Molecular breeding is becoming more practical as better technology emerges. The use of molecular markers in plant breeding for indirect selection of important traits can favorably impact breeding efficiency. The purpose of this research is to identify quantitative trait loci (QTL) on molecular linkage groups (MLG) which are associated with seed protein concentration, seed oil concentration, seed size, plant height, lodging, and maturity, in a population from a cross between the soybean cultivars 'Essex' and 'Williams.' DNA was extracted from F-2 generation soybean leaves and amplified via polymerase chain reaction (PCR) using simple sequence repeat (SSR) markers. Markers that were polymorphic between the parents were analyzed against phenotypic trait data from the F-2 and F-4:6 generation. For the F-2 population, significant additive QTL were Satt540 (MLG M, maturity, r(2)=0.11; height, r(2)=0.04, seed size, r(2)=0.061, Satt373 (MLG L, seed size, r(2)=0.04; height, r(2)=0.14), Satt50 (MLG A1, maturity r(2)=0.07), Satt14 (MLG D2, oil, r(2)=0.05), and Satt251 (protein r(2)=0.03, oil, r(2)=0.04). Significant dominant QTL for the F-2 population were Satt540 (MLG M, height, r(2)=0.04; seed size, r(2)=0.06) and Satt14 (MLG D2, oil, r(2)=0.05). In the F-4:6 generation significant additive QTL were Satt239 (MLG I, height, r(2)=0.02 at Knoxville, TN and r(2)=0.03 at Springfield, TN), Satt14 (MLG D2, seed size, r(2)=0.14 at Knoxville, TN), Satt373 (MLG L, protein, r(2)=0.04 at Knoxville, TN) and Satt251 (MLG B I, lodging r(2)=0.04 at Springfield, TN). Averaged over both environments in the F-4:6 generation, significant additive QTL were identified as Satt251 (MLG B 1, protein, r(2)=0.03), and Satt239 (MLG 1, height, r(2)=0.03). The results found in this study indicate that selections based solely on these QTL would produce limited gains (based on low r(2) values). Few QTL were detected to be stable across environments. Further research to identify stable QTL over environments is needed to make marker-assisted approaches more widely adopted by soybean breeders.

Identification of research to improve the efficiency of breeding strategies for white clover in Australia - a review

A major challenge faced by today's white clover breeder is how to manage resources within a breeding program. It is essential to utilise these resources with sufficient flexibility to build on past progress from conventional breeding strategies, but also take advantage of emerging opportunities from molecular breeding tools such as molecular markers and transformation. It is timely to review white clover breeding strategies. This background can then be used as a foundation for considering how to continue conventional plant improvement activities and complement them with molecular breeding opportunities. In this review, conventional white clover breeding strategies relevant to the Australian dryland target population environments are considered. Attention is given to: (i) availability of genetic variation, (ii) characterisation of germplasm collections, (iii) quantitative models for estimation of heritability, (iv) the role of multi-environment trials to accommodate genotype-by-environment interactions, (v) interdisciplinary research to understand adaptation to dryland environments, (vi) breeding and selection strategies, and (vii) cultivar structure. Current achievements in biotechnology with specific reference to white clover breeding in Australia are considered, and computer modelling of breeding programs is discussed as a useful integrative tool for the joint evaluation of conventional and molecular breeding strategies and optimisation of resource use in breeding programs. Four areas are identified as future research priorities: (i) capturing the potential genetic diversity among introduced accessions and ecotypes that are adapted to key constraints such as summer moisture stress and the use of molecular markers to assess the genetic diversity, (ii) understanding the underlying physiological/morphological root and shoot mechanisms involved in water use efficiency of white clover, with the objective of identifying appropriate selection criteria, (iii) estimation of quantitative genetic parameters of important morphological/physiological attributes to enable prediction of response to selection in target environments, and (iv) modelling white clover breeding strategies to evaluate the opportunities for integration of molecular breeding strategies with conventional breeding programs.

Evaluation of the effect of the seed extract of Moringa oleifera Lam over the efficiency of organic filters in wastewater treatment of dairy cattle breeding

This study aimed to evaluate the effect of Moringa oleifera Lam extract on the removal of total solids (TS), total suspended solids (TSS) and chemical oxygen demand (COD), in different filter media for treating wastewater of dairy cattle breeding (DCW). The moringa seed extract was obtained by grinding 50 g of seeds in one liter of distilled water and, after passing the solution through a quantitative paper filter of 25 microns, 60 mL of the extract were added to wastewater from cattle breeding before the filtration process in organic filters made of thin coal, bamboo leaves, eucalyptus leaves, gliricidia branches and sawdust. This was followed by the completely randomized experimental design, adopting a factorial of 5 x 2. Aliquots of filtered effluent were collected and the total solids (TS) concentrations, total suspended solids (TSS) and chemical oxygen demand (COD) were determined. It was found that the increase in the efficiency of removal of COD and total solids can be attributed to the coagulating power of the moringa seed extract, wherein the filter medium with bamboo leaves presented the best performance, showing potential for use as alternative filter material in the primary treatment of DCW.

Strategies to improve the efficiency of genomic selection in animal breeding programs

Pós-graduação em Zootecnia - FCAV

Genetic analysis of average annual productivity of Nellore breeding cows (COWPROD)

With the aim of estimating the coefficient of heritability of average annual productivity of Nellore cows (COWPROD), a data set from 24,855 animals with known pedigree was analyzed. COWPROD is defined as the amount (in kilograms) of weaned calves produced yearly by one cow during her remaining time in herd ignoring a fixed period of 365 days. COWPROD was calculated regarding three standards: a) based on the post-weaning weight from the calves ignoring any kind of adjustment (COWPROD_NAJ), b) adjusted weight for the fixed effects (COWPROD_AJFIX) and c) adjusted weight for the fixed effects and for the genetic merit of the sire (COWPROD_AJFIN). The obtained heritabilities were 0.15, 0.15 and 0.16 for COWPROD_NAJ, COWPROD_AJFIX and COWPROD_AJFIN, respectively. A complete set composed of 105,158 COWPROD records on 130,740 animals in pedigree was also analyzed for predicting the genetic merit of all animals in the data set and for the calculation of the genetic, phenotypic and residual trends. Ranking correlation was high for the adjusted and non-adjusted data, yet, for some of the animals, the difference among the genetic values was large. This would be an indication that it would be better to work always with the adjusted weaning weights. The genetic trend was positive, but was of small magnitude (0.26% of the trait average) and the residual trend was negative as a consequence of the large intensification of the production system, which has been occurring in the last years in the farms studied. The phenotypic trend was also negative and intermediate between the genetic and the residual ones.

The role of physiological understanding in plant breeding; From a breeding perspective

The role of physiological understanding in improving the efficiency of breeding programs is examined largely from the perspective of conventional breeding programs. Impact of physiological research to date on breeding programs, and the nature of that research, was assessed from (i) responses to a questionnaire distributed to plant breeders and physiologists, and (ii) a survey of literature abstracts. Ways to better utilise physiological understanding for improving breeding programs are suggested, together with possible constraints to delivering beneficial outcomes. Responses from the questionnaire indicated a general view that the contribution by crop physiology to date has been modest. However, most of those surveyed expected the contribution to be larger in the next 20 years. Some constraints to progress perceived by breeders and physiologists were highlighted. The survey of literature abstracts indicated that from a plant breeding perspective, much physiological research is not progressing further than making suggestions about possible approaches to selection. There was limited evidence in the literature of objective comparison of such suggestions with existing methodology, or of development and application of these within active breeding programs. It is argued in this paper that the development of outputs from physiological research for breeding requires a good understanding of the breeding program(s) being serviced and factors affecting its performance. Simple quantitative genetic models, or at least the ideas they represent, should be considered in conducting physiological research and in envisaging and evaluating outputs. The key steps of a generalised breeding program are outlined, and the potential pathways for physiological understanding to impact on these steps are discussed. Impact on breeding programs may arise through (i) better choice of environments in which to conduct selection trials, (ii) identification of selection criteria and traits for focused introgression programs, and (iii) identifying traits for indirect selection criteria as an adjunct to criteria already used. While many breeders and physiologists apparently recognise that physiological understanding may have a major role in the first area, there appears to be relatively Little research activity targeting this issue, and a corresponding bias, arguably unjustified, toward examining traits for indirect selection. Furthermore, research on traits aimed at crop improvement is often deficient because key genetic parameters, such as genetic variation in relevant breeding populations and genetic (as opposed to phenotypic) correlations with yield or other characters of economic importance, are not properly considered in the research. Some areas requiring special attention for successfully interfacing physiology research with breeding are discussed. These include (i) the need to work with relevant genetic populations, (ii) close integration of the physiological research with an active breeding program, and (iii) the dangers of a pre-defined or narrow focus in the physiological research.

Evaluating plant breeding strategies by simulating gene action and dryland environment effects

Functional genomics is the systematic study of genome-wide effects of gene expression on organism growth and development with the ultimate aim of understanding how networks of genes influence traits. Here, we use a dynamic biophysical cropping systems model (APSIM-Sorg) to generate a state space of genotype performance based on 15 genes controlling four adaptive traits and then search this spice using a quantitative genetics model of a plant breeding program (QU-GENE) to simulate recurrent selection. Complex epistatic and gene X environment effects were generated for yield even though gene action at the trait level had been defined as simple additive effects. Given alternative breeding strategies that restricted either the cultivar maturity type or the drought environment type, the positive (+) alleles for 15 genes associated with the four adaptive traits were accumulated at different rates over cycles of selection. While early maturing genotypes were favored in the Severe-Terminal drought environment type, late genotypes were favored in the Mild-Terminal and Midseason drought environment types. In the Severe-Terminal environment, there was an interaction of the stay-green (SG) trait with other traits: Selection for + alleles of the SG genes was delayed until + alleles for genes associated with the transpiration efficiency and osmotic adjustment traits had been fixed. Given limitations in our current understanding of trait interaction and genetic control, the results are not conclusive. However, they demonstrate how the per se complexity of gene X gene X environment interactions will challenge the application of genomics and marker-assisted selection in crop improvement for dryland adaptation.

Methods to classify maize cultivars in use efficiency and response to nitrogen

n plant breeding programs that aim to obtain cultivars with nitrogen (N) use efficiency, the focus is on methods of selection and experimental procedures that present low cost, fast response, high repeatability, and can be applied to a large number of cultivars. Thus, the objectives of this study were to classify maize cultivars regarding their use efficiency and response to N in a breeding program, and to validate the methodology with contrasting doses of the nutrient. The experimental design was a randomized block with the treatments arranged in a split-plot scheme with three replicates and five N doses (0, 30, 60, 120 and 200 kg ha-1) in the plots, and six cultivars in subplots. We compared a method examining the efficiency and response (ER) with two contrasting doses of N. After that, the analysis of variance, mean comparison and regression analysis were performed. In conclusion, the method of the use efficiency and response based on two N levels classifies the cultivars in the same way as the regression analysis, and it is appropriate in plant breeding routine. Thus, it is necessary to identify the levels of N required to discriminate maize cultivars in conditions of low and high N availability in plant breeding programs that aim to obtain efficient and responsive cultivars. Moreover, the analysis of the interaction genotype x environment at experiments with contrasting doses is always required, even when the interaction is not significant.

Efficiency Measures in the Agricultural Sector: With Applications

Copyright 2013 Springer Netherlands.

Increasing the efficiency of utilization of soil and fertilizer phosphorus in the subtropical and tropical agricultural systems C

As a rule, soils of the subtropical and tropical regions, in which rainfall is not limiting, are acidic, and low in phosphorus, and, to a less extent, in other macro and micronutrients as well, such a sulfur, boron and zinc. The establishment of a permanent agricultural prac. tice therefore, demands relatively high usage of liming and phosphatic fertilization, to begin with. Several approaches, not mutually exclusive, could be used in order to increase the efficiency of utilization of soil and fertilizer phosphorus so that, goal of diminishing costs of production is reached. The use of liming materials bringing up pH to 6.0-6.5 causes the conversion of iron and aluminum phosphates to more available calcium phosphates; on the other hand, by raising calcium saturation in the exchange complex, it improves the development and operation if the root system which allows c or a higher utilization of all soil nutrients, including phosphorus, and helps of stand water deficits which may occur. The role of mycorrhizal fungi should be considered as a way of increasing soil and fertilizer P utilization, as well as the limitations thereof. Screening of and breeding for varieties with higher efficiency of uptake and utilization of soil and fertilizer phosphorus leads to a reduction in cost of inputs and to higher benefit/cost ratios. Corrective fertilization using ground rock phosphate helps to saturate the fixation power of the soil thereby reducing, as a consequence, the need for phosphorus in the maintenance fertilization. Maintenance fertilization, in which soluble phos-phatic sources are used, could be improved by several means whose performance has been proved: limimg, granula tion, placement, use of magnesium salts. Last, cost of phosphate fertilization could be further reduced, without impairing yields, through impairing yields, through changes in technology designed to obtain products better adapted to local conditions and to the availability or raw materials and energy sources.

Spatial statistical analysis and selection of genotypes in plant breeding

The objective of this study was to evaluate the efficiency of spatial statistical analysis in the selection of genotypes in a plant breeding program and, particularly, to demonstrate the benefits of the approach when experimental observations are not spatially independent. The basic material of this study was a yield trial of soybean lines, with five check varieties (of fixed effect) and 110 test lines (of random effects), in an augmented block design. The spatial analysis used a random field linear model (RFML), with a covariance function estimated from the residuals of the analysis considering independent errors. Results showed a residual autocorrelation of significant magnitude and extension (range), which allowed a better discrimination among genotypes (increase of the power of statistical tests, reduction in the standard errors of estimates and predictors, and a greater amplitude of predictor values) when the spatial analysis was applied. Furthermore, the spatial analysis led to a different ranking of the genetic materials, in comparison with the non-spatial analysis, and a selection less influenced by local variation effects was obtained.

Growth components and zinc recovery efficiency of upland rice genotypes

The objective of this work was to evaluate Zn use efficiency by upland rice genotypes. The experiment was carried out in a greenhouse, with ten upland rice genotypes grown on an Oxisol (Typic Hapludox) with no application, and with application of 10 mg kg-1 Zn, applied as zinc sulfate. Shoot dry weight, grain yield, Zn harvest index, Zn concentration in shoot and in grain were significantly influenced by soil Zn levels and genotypes. However, panicle number and grain harvest index were significantly affected only by genotype. Genotypes CNA8557, CNA8540 and IR42 produced higher grain yield than other genotypes. Genotypes showed significant variability in Zn recovery efficiency. On average, 13% of the applied Zn was recovered by upland rice genotypes. Genotypes with high Zn recovery efficiency could be used in breeding of Zn efficient upland rice cultivars. Higher level of soil Zn (10 mg kg-1) increased significantly the concentrations of plant Cu and Mn. However, Fe concentrations in plant (shoot and grain) were not influenced by soil Zn levels.