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Animal scientists and their funding organisations need to ensure investment in research is maximised by strict adherence to the scientific method and the rigorous design and analysis of experiments. Statisticians should be considered as equals in the research process, engaged from the beginning of research projects and appropriately funded. The importance of experimental design that accounts for factors affecting the primary experiment measurement is illustrated in two examples. One shows how failure to involve a statistician at the beginning of a project resulted in considerable waste of resources. Subsequent engagement of professional statisticians with rigorous experimental design and analysis led to greatly increased precision in the standard error of an estimate for the digestible energy content of cereal grains for pigs from 0.35 MJ/kg to 0.16 MJ/kg. The other example shows the effect of the percentage of diets replicated during pelleting and of the total number of pigs required in the experiment on theP-values associated with detecting a pairwise difference between two grains differing in digestible energy content by 0.33 MJ/kg. Decisions based on these relationships have animal welfare and resource allocation implications.

High yield is a major objective in canola-breeding programs. We analysed the genetic determinants controlling variation in grain yield in a doubled-haploid (DH) breeding population derived from a single BC1F1 plant from the cross Skipton/Ag-Spectrum//Skipton (designated as theSAgSpopulation).DHlines were evaluated for flowering time and yield in two replicated trials and exhibited significant genetic variation for both traits. Yield showed negative correlation with flowering time; lines that flowered earlier had higher yield than late-flowering lines.Agenetic linkage map comprising 7716 DArTseq markers was constructed for the SAgS population, and a ‘bin’ map based on 508 discrete single-position (non-cosegregating) marker loci was used for quantitative trait locus (QTL) analysis. We identified 20 QTLs (LOD 2) associated with variation in flowering time and grain yield. Two QTLs (Qy.wwai-A7/Qdtf.wwai-A7/Qfs.wwai-A7 and Qy.wwai-C3a/ Qfs.wwai-C3a) appeared repeatedly across experiments, accounting for 4.9–19%of the genotypic variation in flowering time and yield and were located on chromosomes A07 and C03. We identified 22 putative candidate genes for flowering time as well as grain yield, and all were located in a range of 935 bp to 2.97 Mb from markers underlying QTLs. This research provides useful information to be used for breeding high-yielding canola varieties by combining favourable alleles for early flowering and higher grain yield at loci on chromosomes A07, C03 and possibly on A06.

Various studies have highlighted the importance of grain particle size on growth performance of pigs (Choct et al. 2004; Montoya and Leterme 2011). However, the studies concentrated on cereals, used one mill type, or had an insufficient number of treatment levels to probe the performance-size relationships. Field pea is low in anti-nutritional factors, and it is an important protein source in pig feeds (Nguyen et al. 2015). Hammer-, disc- and roller-mills are mainly used in pig feed manufacture, and mill types can influence growth performance (Choct et al. 2004). Using commercial mills to replicate field situations, this study investigated how weaner pigs responded to diets containing hammer- and disc-milled field peas of different particle sizes. The hypothesis tested was that an optimum particle size range exists, within which, growth performance is independent of particle size. Field pea (var.Walana)was milled, in two replicates, using commercial hammer (HM)and disc (DM)mills, in a randomised design with four screen sizes (2, 3, 4, and 5mm) and four disc gaps respectively.The finest (F) and coarsest(VC) sizes fromthemillsweremixed for four additional treatments: HMF- DMF,HMF-DMVC,HMVC-DMF, andHMVC-DMVC. A total of 20 milled grains, but 12 treatments, were used (30%) toformulate the experimental diets [14MJ digestible energy(DE)/kg; available lysine/DE, 0.09g/MJDE; 430 g/kg starch, 190 g/kg crude protein) forweaner pigs [LargeWhite · Landrace, PrimeGroGenetics; 28 days of age andweighing 7.3 0.10 kg (mean SD)]. After adaptation for 6 days on a commercial diet, a total of 400 pigs in two batches were individually housed and fed the 20 diets adlibitumover a 21-dayperiodusinga randomisedblockdesignwithsomeincomplete blocks.Hence, therewere effectively20pigsper diet (or 33 pigs per treatment), and the pigs and feed residues were weighedweekly to calculate average daily feed intake (ADFI), average daily gain (ADG) and feed conversion ratio (FCR). TheRivalea animal ethi

Sorghum is the third most important cereal in Australia, in terms of production, and it is a major feed grain (Mahasukhonthachat et al. 2010). Mahasukhonthachat et al. (2010) and recently, Nguyen et al. (2015), revealed particle size and mill type as the primary determinants of in-vitro digestion properties of grains. However, there are limited studies on the effects of grain particle size and mill type on animal performance. Using sorghum, this study investigated these effects on performance of weaner pigs, and tested the hypothesis that within an optimum particle size range, pig performance is not affected. Sorghum (var. MR43) was milled with industrial-scale hammer (HM) and disc (DM) mills, in a randomised experiment with two replicates. Four screens (2, 3, 4, and 5mm)and four disc gaps were used in theHMandDMrespectively. Four additional treatments were obtained by mixing the finest (F) and coarsest (VC) sizes from the mills (HMF-DMF,HMF-DM VC,HMVC-DMF, andHMVC-DM VC). Experimental diets [15 MJ digestible energy (DE)/kg, 1 g available lysine/MJ DE, 220 g/kg crude protein, and 350 g/kg starch), consisting 49.8% of the milled sorghum, were fed ad libitum to weaner pigs for 21 d.Atotal of 289 weaner pigs (Large White · Landrace, PrimeGro Genetics) aged 28 days and having a bodyweight of 6.8 0.1 kg (mean SD), were individually housed and used in three batches in a randomised block design, with some incomplete blocks. There were 20 diets from the 12 particle size treatments, and 24 pigs were used per treatment. Pigs and feed residues were weighed weekly to calculate average daily feed intake (ADFI), average daily gain (ADG)and feed conversion ratio (FCR). The Rivalea animal ethics committee approved (14N009) the animal experiment. The diets were analysed (Nguyen et al. 2015) for geometric mean particle size diameter (Dgw) and geometric standard deviation of mean particle diameter (Sgw). Statistical methods (ASReml-R) analogous to ANOVA were used (Butler 2009). TheDgw

Pigs exposed to conventional housing systems with high microbial loads grow around 20% more slowly than gnotobiotic pigs or pigs in ‘clean’ environments (Black and Pluske 2011). In-feed antibiotics reduce microbial numbers and modulate the immune system, but result in concerns about microbial resistance to antibiotics in human health (Collignon 2003). Black and Pluske (2011) suggested using a multi-targeted approach to reduce microbial load in pigs, reduce release of pro-inflammatory cytokines and subsequent production of prostaglandin E2 (PGE2), which causes anorexia, fever and decreases protein synthesis. The hypothesis was that multiple treatments targeting the immune system of pigs would improve performance. Treatments initially identified were: i) fatty acids monolaurin and monomyristin (2:1), which are toxic to most microbes; ii) a n-6:n-3 ratio <4:1, to reduce pro-inflammatory cytokine release; iii) aspirin, to reduce pro-inflammatory cytokines and inhibit PGE2 formation; and iv) meloxicam, to inhibit COX-2 action and restrict PGE2 synthesis. Due to regulatory and product availability constraints, aspirin, meloxicam, and monomyristin could not be evaluated in this study. Male (M) and female (F) pigs (1,240 of PrimeGro Genetics, initial weight 8.2 1.25 kg, mean SE) were allocated to five treatments in a designed experiment with nine replicates in three sheds and 13-14 pigs/pen. The treatments, offered feed ad libitum, were: (A) monolaurin at2%of a weaner diet ( 15.3 MJ/kg digestible energy (DE), 216 g/kg crude protein (CP), 13.1 g/kg available lysine); (B) fish-safflower oils with a n-6:n-3 ratio of 2 : 1 at 6%; (C) treatments A and B combined; (D) negative control diet with no antibiotics, zinc oxide and a n-6:n-3 ratio of 20.7:1 at 6%; and (E) positive control, being the weaner diet with sulphatrim (0.1%). Pigs were initially weighed individually, then in pens after 14 days and individually at the end of the experiment (28 days). Pen feed intake was measu

An Illumina Infinium array comprising 5306 single nucleotide polymorphism (SNP) markers was used to genotype 175 individuals of a doubled haploid population derived from a cross between Skipton and Ag-Spectrum, two Australian cultivars of rapeseed (Brassica napus L.). A genetic linkage map based on 613 SNP and 228 non-SNP (DArT, SSR, SRAP and candidate gene markers) covering 2514.8 cM was constructed and further utilized to identify loci associated with flowering time and resistance to blackleg, a disease caused by the fungus Leptosphaeria maculans. Comparison between genetic map positions of SNP markers and the sequenced Brassica rapa (A) and Brassica oleracea (C) genome scaffolds showed several genomic rearrangements in the B. napus genome. A major locus controlling resistance to L. maculans was identified at both seedling and adult plant stages on chromosome A07. QTL analyses revealed that up to 40.2% of genetic variation for flowering time was accounted for by loci having quantitative effects. Comparative mapping showed Arabidopsis and Brassica flowering genes such as Phytochrome A/D, Flowering Locus C and agamous-Like MADS box gene AGL1 map within marker intervals associated with flowering time in a DH population from Skipton/Ag-Spectrum. Genomic regions associated with flowering time and resistance to L. maculans had several SNP markers mapped within 10 cM. Our results suggest that SNP markers will be suitable for various applications such as trait introgression, comparative mapping and high-resolution mapping of loci in B. napus. 2014 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

CSIRO 2014. Early crop vigour in canola, as in other crops, is likely to result in greater competition with weeds, more rapid canopy closure, improved nutrient acquisition, improved water-use efficiency, and, potentially, greater final grain yield. Laborious measurements of crop biomass over time can be replaced with newer remote-sensing technology to aid data acquisition. Normalised difference vegetation index (NDVI) is a surrogate for biomass accumulation that can be recorded rapidly and repeatedly with inexpensive equipment. In seven small-plot field experiments conducted over a 4-year period with diverse canola germplasm (n = 105), we have shown that NDVI measures are well correlated with final grain yield. We found NDVI values were most correlated with yield (r >0.7) if readings were taken when the crop had received 210-320 growing degree-days (usually the mid-vegetative phase of growth). It is suggested that canola breeders may use NDVI to objectively select for vigorous genotypes that are more likely to have higher grain yields.

An Illumina Infinium array comprising 5306 single nucleotide polymorphism (SNP) markers was used to genotype 175 individuals of a doubled haploid population derived from a cross between Skipton and Ag-Spectrum, two Australian cultivars of rapeseed (Brassica napus L.). A genetic linkage map based on 613 SNP and 228 non-SNP (DArT, SSR, SRAP and candidate gene markers) covering 2514.8 cM was constructed and further utilized to identify loci associated with flowering time and resistance to blackleg, a disease caused by the fungus Leptosphaeria maculans. Comparison between genetic map positions of SNP markers and the sequenced Brassica rapa (A) and Brassica oleracea (C) genome scaffolds showed several genomic rearrangements in the B. napus genome. A major locus controlling resistance to L. maculans was identified at both seedling and adult plant stages on chromosome A07. QTL analyses revealed that up to 40.2% of genetic variation for flowering time was accounted for by loci having quantitative effects. Comparative mapping showed Arabidopsis and Brassica flowering genes such as Phytochrome A/D, Flowering Locus C and agamous-Like MADS box gene AGL1 map within marker intervals associated with flowering time in a DH population from Skipton/Ag-Spectrum. Genomic regions associated with flowering time and resistance to L. maculans had several SNP markers mapped within 10 cM. Our results suggest that SNP markers will be suitable for various applications such as trait introgression, comparative mapping and high-resolution mapping of loci in B. napus. © 2014 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Resistance to pod shattering (shatter resistance) is a target trait for global rapeseed (canola, Brassica napus L.), improvement programs to minimise grain loss in the mature standing crop, and during windrowing and mechanical harvest. We describe the genetic basis of natural variation for shatter resistance in B. napus and show that several quantitative trait loci (QTL) control this trait. To identify loci underlying shatter resistance, we used a novel genotyping-by-sequencing approach DArT-Seq. QTL analysis detected a total of 12 significant QTL on chromosomes A03, A07, A09, C03, C04, C06, and C08; which jointly account for approximately 57% of the genotypic variation in shatter resistance. Through Genome-Wide Association Studies, we show that a large number of loci, including those that are involved in shattering in Arabidopsis, account for variation in shatter resistance in diverse B. napus germplasm. Our results indicate that genetic diversity for shatter resistance genes in B. napus is limited; many of the genes that might control this trait were not included during the natural creation of this species, or were not retained during the domestication and selection process. We speculate that valuable diversity for this trait was lost during the natural creation of B. napus. To improve shatter resistance, breeders will need to target the introduction of useful alleles especially from genotypes of other related species of Brassica, such as those that we have identified. © 2014 Raman et al.

Early crop vigour in canola, as in other crops, is likely to result in greater competition with weeds, more rapid canopy closure, improved nutrient acquisition, improved water-use efficiency, and, potentially, greater final grain yield. Laborious measurements of crop biomass over time can be replaced with newer remote-sensing technology to aid data acquisition. Normalised difference vegetation index (NDVI) is a surrogate for biomass accumulation that can be recorded rapidly and repeatedly with inexpensive equipment. In seven small-plot field experiments conducted over a 4-year period with diverse canola germplasm (n = 105), we have shown that NDVI measures are well correlated with final grain yield. We found NDVI values were most correlated with yield (r >0.7) if readings were taken when the crop had received 210-320 growing degree-days (usually the mid-vegetative phase of growth). It is suggested that canola breeders may use NDVI to objectively select for vigorous genotypes that are more likely to have higher grain yields.

Conservation cropping systems with no-till and stubble retention improve soil condition and water conservation. However, tillage is replaced by herbicides for weed control in these systems, increasing the threat of herbicide resistance. In the medium to high rainfall zones of the southern wheatbelt of Australia and under irrigation, wider row spacing is used to enable seeding into heavy stubble loads and to avoid stubble burning. Some evidence suggests that wider rows lead to reduced crop competitive ability and crop yields, greater herbicide dependence, and increased spread of resistance. Our aim was to test the hypothesis that increasing seeding rate compensated for reduced competitive ability at wider row spacings, especially when herbicide performance was suboptimal. We examined the impact of two wheat row spacings (18 and 36cm) and five seeding rates (resulting in a range of densities of 80-700 plants/m2) on control of Lolium rigidum with five rates of post-emergence application of diclofop-methyl (Hoegrass), ranging from label rate to lower rates, over two growing seasons. In the presence of L. rigidum, wheat grain yield was unaffected by row spacing but was significantly reduced at low seeding rates, especially at lower herbicide rates. Lolium rigidum was suppressed at higher crop densities but was also unaffected by row spacing. Grain yield was maximised when post-emergence herbicide was applied at 60-100% of the recommended dose at wheat densities >300 plants/m2. Significant levels of the weed remained in the crop at anthesis in all treatments. Weed dry matter ranged from 525g/m2 at low crop densities and with no herbicide to 150g/m2 with the recommended rate of herbicide and high wheat densities. The implications of manipulating crop competitive ability to improve weed control are discussed, especially in conditions where herbicide performance is unreliable due to weeds developing herbicide resistance or adverse environmental conditions.

Conservation cropping systems with no-till and stubble retention improve soil condition and water conservation. However, tillage is replaced by herbicides for weed control in these systems, increasing the threat of herbicide resistance. In the medium to high rainfall zones of the southern wheatbelt of Australia and under irrigation, wider row spacing is used to enable seeding into heavy stubble loads and to avoid stubble burning. Some evidence suggests that wider rows lead to reduced crop competitive ability and crop yields, greater herbicide dependence, and increased spread of resistance. Our aim was to test the hypothesis that increasing seeding rate compensated for reduced competitive ability at wider row spacings, especially when herbicide performance was suboptimal. We examined the impact of two wheat row spacings (18 and 36cm) and five seeding rates (resulting in a range of densities of ~80-700 plants/m2) on control of Lolium rigidum with five rates of post-emergence application of diclofop-methyl (Hoegrass®), ranging from label rate to lower rates, over two growing seasons. In the presence of L. rigidum, wheat grain yield was unaffected by row spacing but was significantly reduced at low seeding rates, especially at lower herbicide rates. Lolium rigidum was suppressed at higher crop densities but was also unaffected by row spacing. Grain yield was maximised when post-emergence herbicide was applied at 60-100% of the recommended dose at wheat densities >~300 plants/m2. Significant levels of the weed remained in the crop at anthesis in all treatments. Weed dry matter ranged from 525g/m2 at low crop densities and with no herbicide to 150g/m2 with the recommended rate of herbicide and high wheat densities. The implications of manipulating crop competitive ability to improve weed control are discussed, especially in conditions where herbicide performance is unreliable due to weeds developing herbicide resistance or adverse environmental conditions. © 2013 CSIRO

Selection of wheat germplasm for a range of quality traits has been a challenging exercise because of the cost of testing, the variation within testing data, and a poor understanding of the underlying genetics. The objective of this study was to identify quantitative trait loci (QTLs) underlying quality traits in wheat. A doubled haploid population comprising 190 lines from Chara/WW2449 was grown in two different environments and evaluated for various quality traits. A molecular map comprising 362 markers based upon simple sequence repeat, sequence tagged microsatellite, glutenin, and DArT loci was constructed and subsequently exploited to identify QTLs using a whole-genome approach. Fifteen QTLs that were consistent in the two different environments were identified for thousand kernel mass, grain protein content, milling yield, flour protein content, flour colour, flour water absorption, dough development time, dough strength (extensograph height and resistance at 5 cm), and dough extensibility (extensograph length) using the whole genome average interval mapping approach. The amount of genetic variation explained by individual QTLs ranged from 3% to 49%. A number of QTLs associated with dough strength, dough extensibility, dough development time, and flour water absorption were located close to the glutenin Glu-B1 locus on chromosome 1B. Identification of the chromosomal location and effect of the QTLs influencing wheat quality may hasten the development of superior wheats for target markets via marker-assisted selection.

While the genetic control of wheat processing characteristics such as dough rheology is well understood, limited information is available concerning the genetic control of baking parameters, particularly sponge and dough (S&D) baking. In this study, a quantitative trait loci (QTL) analysis was performed using a population of doubled haploid lines derived from a cross between Australian cultivars Kukri × Janz grown at sites across different Australian wheat production zones (Queensland in 2001 and 2002 and Southern and Northern New South Wales in 2003) in order to examine the genetic control of protein content, protein expression, dough rheology and sponge and dough baking performance. The study highlighted the inconsistent genetic control of protein content across the test sites, with only two loci (3A and 7A) showing QTL at three of the five sites. Dough rheology QTL were highly consistent across the 5 sites, with major effects associated with the Glu-B1 and Glu-D1 loci. The Glu-D1 5 + 10 allele had consistent effects on S&D properties across sites; however, there was no evidence for a positive effect of the high dough strength Glu-B1-al allele at Glu-B1. A second locus on 5D had positive effects on S&D baking at three of five sites. This study demonstrated that dough rheology measurements were poor predictors of S&D quality. In the absence of robust predictive tests, high heritability values for S&D demonstrate that direct selection is the current best option for achieving genetic gain in this product category. © 2009 Springer-Verlag.

Mixing measurements provide valuable information about dough strength and stability (STAB) traits. These measurements are important in milling and baking operations, and for varietal selection in wheat breeding programmes. There are several techniques with different sample sizes used for measuring these traits so there is interest in examining the agreement between methods in terms of genotypic (varietal) rankings. This issue has been investigated by using two different mixing methods, a small-scale Mixograph (2 g) and large-scale Farinograph (50 g) using data from a doubled haploid population (190 lines) from a Chara (excellent dough strength)×WW2449 (poor dough strength) cross. The cross was grown in a field trial at the Wagga Wagga Agricultural Institute (WWAI) in 2000. Eleven mixing traits were measured and compared according to a statistical design. The estimated genetic correlation matrix for six of the 11 mixing traits, dough development time (DDT), STAB, mixing tolerance index (MTI), maximum bandwidth (MBW), bandwidth at peak resistance (BWPR) and peak resistance (PR) revealed that for these dough-strength-related parameters, both methods were measuring equivalent traits, although individual parameters had widely different coefficients of variation. In this population, PR was correlated with the extensibility trait length determined by large-scale extension testing. None of the large-scale or small-scale mixing traits was an effective predictor of the small-scale extensibility parameter extensibility at Rmax (Ext_Rmax). The data verified that small-scale Mixograph tests are a robust and efficient alternative to large-scale Farinograph tests for both commercial breeding and research. © 2007.

The variation in field pea grain yield and competitiveness with annual ryegrass due to crop density, row spacing and cultivar was determined to enable farmers to better manage weeds with cultural control tactics. Crop density varied with seeding rate, cultivar, row spacing and year. Higher seeding rates were required to reach equivalent plant densities in cv. Dinkum (short, semi-leafless) compared with cv. Dundale (tall, conventional-leaf), and at 36 cm compared with 18 cm row spacing. Field pea grain yield was reduced more at low crop densities, in Dinkum, at 36 cm row spacing, and in the presence of weeds. Percentage yield losses from weed competition were similar in both cultivars (about 70–80%) at a low density of 10 plants/m2 in 2 seasons. At higher crop densities Dinkum had a larger loss than Dundale (i.e. at 30 plants/m2 losses were 60 and 35%, respectively, compared with 50 and 5% at 60 plants/m2). Seasonal variation influenced the effect of crop density on yield loss from weeds. The percentage yield loss from weeds in 1993 ranged from about 90 to 40% at plant densities of 10 to 40 plants/m2, in contrast to 1995 when 40% yield loss occurred at all these densities. Ryegrass dry weight was reduced with increasing field pea density in both years, and in the tall more than the short cultivar in 1 year. Maintaining recommended field pea seeding rates has considerable financial benefits in both weed-free (around $100/ha) and weed-affected crops (to $400/ha). In weedy situations, integrating cultural practices such as higher seeding rates and choice of cultivar that enhance crop competitiveness will improve weed management in south-eastern Australia.