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Breeding for improved blanchability—the propensity of the testa (skin) to be removed from the kernel following rapid heat treatment—is a priority for improvement in the Australian Peanut Breeding Program (APBP). Easy removal of the testa by blanching is required for processing of peanuts into peanut butter and various other confectionary products. Thus, blanchability is an economically important trait in any newly released cultivar in Australia. A better understanding of the range of genetic variation, nature of inheritance and genotype×environment (G×E) interactions, and the development of a low-cost method to phenotype in early generations, could speed up breeding for this trait. Studies were conducted to develop a low-cost, rapid method utilising minimal amounts of seed to phenotype in early generations, along with an assessment of G×E interactions over a range of years and environments to derive optimal selection protocols. Use of a smaller kernel sample size than standard (50 vs 200g) was effective for accurately assessing blanchability in breeding lines and could allow selection in early generations (e.g. in seed produced from a single F2 plant where seed supply is adequate). G×E interaction for blanchability was shown to be very low. Genotypic variance explained 62–100% of the total variance for blanchability, assessed in two diverse germplasm pools including 107 accessions in the USA mini-core over three environments and multiple APBP breeding lines grown over nine different years–environments. Genotypic correlations between all environments were very high (~0.60–0.96), with heritability for the blanchability trait estimated to be very high (0.74–0.97) across the 13 trials. The results clearly demonstrate that effective selection for improved blanchability can be conducted in early generations and in a limited number of contrasting environments to ensure consistency of results.

PigBal is a mass balance model that uses pig diet, digestibility and production data to predict the manure solids and nutrients produced by pig herds. It has been widely used for designing piggery effluent treatment systems and sustainable reuse areas at Australian piggeries. More recently, PigBal has also been used to estimate piggery volatile solids production for assessing greenhouse gas emissions for statutory reporting purposes by government, and for evaluating the energy potential from anaerobic digestion of pig effluent. This paper has compared PigBal predictions of manure total, volatile, and fixed solids, and nitrogen (N), phosphorus (P) and potassium (K), with manure production data generated in a replicated trial, which involved collecting manure from pigs housed in metabolic pens. Predictions of total, volatile, and fixed solids and K in the excreted manure were relatively good (combined diet R2 ≥ 0.79, modelling efficiency (EF) ≥ 0.70) whereas predictions of N and P, were generally less accurate (combined diet R2 0.56 and 0.66, EF 0.19 and –0.22, respectively). PigBal generally under-predicted lower N values while over-predicting higher values, and generally over-predicted manure P production for all diets. The most likely causes for this less accurate performance were ammonium-N volatilisation losses between manure excretion and sample analysis, and the inability of PigBal to account for higher rates of P uptake by pigs fed diets containing phytase. The outcomes of this research suggest that there is a need for further investigation and model development to enhance PigBal’s capabilities for more accurately assessing nutrient loads. However, PigBal’s satisfactory performance in predicting solids excretion demonstrates that it is suitable for assessing the methane component of greenhouse gas emission and the energy potential from anaerobic digestion of volatile solids in piggery effluent. The apparent overestimation of N and P excretion may result in conservative nutrient application rates to land and the over-prediction of the nitrous oxide component of greenhouse gas emissions.