Control of seed purity is vital for all crops, but is of particular importance with vegetable brassicas where the uniformity of the plant stand is essential for the future profitability of the crop. The detection and elimination of siblings is of particular importance where F1 hybrids are predominantly used as cultivars as with most Brassica crops. The sibling problem arises because B. oleracea possesses a single locus, multiallelic, sporophytic incompatibility system. Plant breeders usually maintain their lines by bud pollination (see Chapter 2). All incompatibility alleles are not equally effective, however, and varying amounts of self-fertilization may take place within inbred lines that are homozygous for S alleles. Additionally, the incompatibility reaction may be weakened by environmental factors, and the ratio of selfing to crossing can be affected by the behaviour of pollinating insects and the availability of foreign pollen (Wills et al., 19 79).
Sibling plants are at best far less productive for the grower than the hybrid cultivar, and represent a failure by the seed-producing company. Elimination is achieved by testing hybrid populations or by producing complex multiparent hybrids where any siblings may also be productive. This may not always be feasible and increases the cost and complexity of a breeding programme. Quality control has generally been achieved by sampling hybrid populations as either seed, cotyledons or leaves, followed by visual inspection or by biochemical testing such as the use of isoenzyme markers. Visual inspection is not satisfactory since the morphological differences may require a long time period over which they emerge. Isoenzyme studies are suggested as quick, simple and accurate, but again may not always be applicable since the high level of inbreeding within the parent lines of a hybrid cultivar means that they may express similar isoenzyme bands. Use of DNA probes could circumvent this problem. Image analysis also offers a further solution.
Image analysis has the advantages of being non-invasive, open to automation and is increasingly interactive and user-friendly. Studies have shown that use of image analysis with cotyledons or early adult leaves gives a more accurate evaluation of the number of siblings when compared with isoenzyme analysis. Development of image analysis offers the seed industry opportunities for much improved quality control. Sibling detection and vigour estimations may be made based on mean seed size and population variance. Image analysis may also be applied to monitor seed swelling and expansion, thereby establishing automated critical quality control systems in the early stages of seed development. Image analysis of seed area is identified by Dell'aquilla (2003) as a useful marker for studies of vigour and the effects of deterioration and salt stress. Commercial development requires refinement to the image analysis techniques, subsequent statistical analysis, greater precision in the selection of biological parameters to be analysed (seed part or organ/tissue of the developing seedling) and enhanced user-friendly computerized interfaces.
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