GENETIC gains from new cultivars, using productivity data from Queensland sugar mills, are estimated by BSES Limited each year. Data from 1980 to 2005 are available and have been analysed to provide the best estimate of the genetic worth of each variety. Restricted maximum likelihood methods were used to provide best linear unbiased predictors (BLUPs) for the random cultivar effects for cane yield, sucrose content (CCS) and sugar yield. Fixed mill and season (year) effects were also estimated. Linear regression of the cultivar effects and year of release provides estimates of the average productivity increase per year. Further, measuring the rate of genetic gain over successive 30-year periods allows breeders and industry to determine if genetic gain is increasing, static or decreasing. Benchmarking these increases over 30-year periods shows that the rate of increase in sugar yield in Queensland has risen from 119 kg sugar/ha/year in 1989 (cultivars released 1960–1989) to 231 kg sugar/ha/year in 2004 (cultivars released 1975–2004). Similar estimates for cane yield (1.46 t/ha/year) and commercial cane sugar (CCS) (0.033 units/year) for cultivars released in the most recent 30-year period are almost double the estimates in 1989. Such quantitative estimates are important to justify appropriate investment in cultivar improvement and allow targets to be set for the future. Our aim is to achieve greater than 300 kg sugar/ha/year by 2015. An R&D program has been developed and we are currently examining the likely impact of the recent smut incursion to determine what is required to ensure that the current high rates of genetic gains are not eroded and future targets can be met. Introduction In the current funding environment for agricultural research in general and sugarcane research in particular, justification for continued funding is increasingly requiring objective estimates of the return on the research investment. While the contribution of new sugarcane cultivars to productivity and reduced disease-loss risk is widely acknowledged in the Australian sugar industry, objective measures of this contribution are relatively new. Hogarth (1976) calculated that the Queensland sugar industry improved sugar yields by 1.9% per year from 1948 to 1975 and concluded that plant breeding may have contributed about half of this increase. However, only recently have productivity data analysis methods been developed that allow annual benchmarking of genetic gains from new cultivars developed in the BSES-CSIRO Joint Venture for Plant Improvement (Cox et al., 2005; Cox and Stringer, 2006). One of the themes at the 13 Australasian Plant Breeding Conference, held in Christchurch, New Zealand in 2006 was ‘Benefits of Plant Improvement’. The importance of this topic for plant breeders, agricultural industries, funding bodies, and governments was highlighted in the eight
[1]
A. J. Conner,et al.
Breeding for success: diversity in action
,
2007,
Euphytica.
[2]
Robin Thompson,et al.
ASREML user guide release 1.0
,
2002
.
[3]
Gurjeet Gill,et al.
The impact of plant breeding on the grain yield and competitive ability of wheat in Australia
,
2004
.
[4]
D. M. Hogarth,et al.
PRODUCTIVITY INCREASES FROM NEW VARIETIES IN THE QUEENSLAND SUGAR INDUSTRY
,
2005
.
[5]
Peter J. Martin,et al.
An Assessment of the Economic, Environmental and Social Impacts of NSW Agriculture's Wheat Breeding Program
,
2004
.
[6]
H. D. Patterson,et al.
Recovery of inter-block information when block sizes are unequal
,
1971
.
[7]
W. M. Johnson,et al.
Trends over Time among Cotton Cultivars Released by the Oklahoma Agricultural Experiment Station
,
2005
.
[8]
Barry Glaz,et al.
Genetic contribution to yield gains in the Florida sugarcane industry across 33 years
,
2005
.