Defining breeding objectives in chickpea breeding involves deriving economic weights of economically important traits to select varieties that offer improved economic benefits. This process quantifies the economic benefits of genetic improvement by combining multiple traits into a breeding objective used for selection. Although this method is widely used in animal breeding, its application in plant breeding has been limited. This study aims to explore the utilisation of economic weights in plant breeding and to derive the economic weights of grain yield based on economic input parameters and taking genotype by environment interactions into account to improve chickpea breeding objectives.
In Chapter 3, a systematic review was exploring the methodologies for the derivation of economic weights in plant breeding. It identified two primary approaches, a subjective and an objective approach. The subjective approach relies on the opinion of experts, which assign a weight to a trait based on their subjective opinion. In contrast, the objective approach assesses the relative importance of traits using factors like the coefficient of genetic variation, coefficient of environmental variation, heritability and index coefficient for crop breeding. This objective approach does not consider economic parameters, including price and cost of production, which were used to calculate economic weights for pasture and tree breeding. This approach based on economic parameters is recommended to chickpea breeders to prioritise traits taking into account the dynamic nature of the market, evolving consumer needs, and grower challenges in chickpea production.
In chapter 4, economic parameters like production cost and grain price were used to derive the economic weight of grain yield, which were based on economic parameters forecasted for the year 2030. The economic weights, calculated as the first partial derivative of the profit function with respect to grain yield, amounted to AU$730.2 per ton per hectare, since grain yield is evaluated on a land area scale and expressed in tons per hectare. This economic weight of grain yield was further used to calculate the economic differences of chickpea varieties, considering the breeding value of grain yield across distinct interaction classes (iClasses) of northern and southern growing regions of Australia. The iClass refers to the group of environments with minimal variety by environment interaction within environmental groups and maximal between environmental groups. The variation in estimated breeding values of grain yield between varieties across iClasses influenced economic differences between varieties for each growing region. The chickpea varieties were ranked across iClasses and growing regions based on their economic benefits concerning grain yield. Overall, PBA Drummond emerged as the top-performing variety, while PBA Seamer was the least preferable variety due to low consistency. This framework offers a valuable tool for chickpea breeders, facilitating systematic variety selection aligned with economic priorities across diverse environments.
The results highlighted the potential of incorporating economic parameters in describing breeding objectives for genetic improving of chickpea varieties. This study outlines new avenues of determining economic weights for traits, like grain yield, ascochyta blight and phytophthora root rot. When using economic parameters for the derivation of economic weights, challenges remain, such as avoiding double counting in calculating economic weights for complex traits and understanding market fluctuations and emerging trends. However, assessing the implications during the development of breeding objectives can help foresee and address potential issues. As research progresses, the use of economic parameters will become valuable in optimising chickpea breeding, aligned with market trends and opening up further opportunities for improvements.