Biology • Year 12 • Module 5 • Lesson 5
Manipulating Reproduction in Agriculture
Apply selective breeding, artificial insemination, embryo transfer and controlled pollination to real yield data, a real case study, and a real prediction problem.
1. Interpret real-yield data, Australian dairy breeding programmes
The table below shows mean annual milk yield per cow in three Australian commercial dairy herds run on different reproductive strategies, recorded over five lactation seasons. 7 marks Band 4
Stylised data adapted from Dairy Australia "InCalf" benchmarking reports (2019–2023) and Pryce et al. (2014), J. Dairy Sci. 97: 1342–1356.
| Season | Herd A, natural service only (L/cow/yr) |
Herd B, AI from local sires (L/cow/yr) |
Herd C, AI from imported elite sires + ET (L/cow/yr) |
|---|---|---|---|
| 1 (baseline) | 5 800 | 6 100 | 6 350 |
| 2 | 5 850 | 6 480 | 7 050 |
| 3 | 5 900 | 6 760 | 7 720 |
| 4 | 5 920 | 7 010 | 8 240 |
| 5 | 5 940 | 7 240 | 8 690 |
1.1 Describe the trend in mean annual milk yield for Herd A, Herd B and Herd C from Season 1 to Season 5. 2 marks
1.2 Using lesson content, explain why Herd C's yield rose much faster than Herd A's even though all three herds began at a similar baseline. Refer to at least two reproductive techniques. 3 marks
1.3 Identify one biological cost that Herd C is most likely to experience by Season 10 if this strategy continues with no other changes, and justify your answer. 2 marks
2. Interpret real data, gene-pool diversity in a dairy cattle breed
The figure below shows a measure of genetic diversity in the breeding stock of a dairy cattle breed over the past 60 years. The decline coincides with the widespread adoption of artificial insemination and frozen-semen storage from a small number of chosen elite sires, as described in the lesson. 6 marks Band 4–5
Figure adapted from Stachowicz et al. (2011), J. Dairy Science 94: 5160–5175 and FAO (2015), The Second Report on the State of the World's Animal Genetic Resources.
2.1 Describe the trend in genetic diversity of this dairy cattle breed's breeding stock between 1960 and 2020. 2 marks
2.2 Read off the approximate genetic diversity score in 1975 and again in 2020, and calculate the approximate percentage decrease. 2 marks
2.3 When genetic diversity falls below the concern threshold shown on the graph, the breed's gene pool is considered dangerously narrow. Use the graph and lesson content to explain how the same technique (AI from elite sires) can both raise milk yields and cause genetic diversity to fall to this level. 2 marks
3. Case study, overuse of elite sires in a sheep stud
A sheep stud in New South Wales chose three rams with outstanding wool-yield genetics as donors for artificial insemination. Over 10 years, semen from these three rams was used to breed the vast majority of lambs across the stud. Yields improved dramatically in early years, but by Year 8 the herd veterinarian reported rising rates of a hereditary limb condition, and by Year 10 the breeder noticed that a new wool-rust pathogen affected nearly every animal in the flock equally. 5 marks Band 4–5
In 4–6 sentences, explain the biological cause of both problems (hereditary condition and uniform disease susceptibility) using lesson terminology including gene pool, selective breeding and animal welfare.
4. Predict-and-justify, wheat monoculture meets a new rust strain
A regional wheat industry uses controlled pollination over twenty years to fix a single high-yielding, drought-tolerant cultivar across 90% of its growing area. In Year 21, a new strain of stem rust (Puccinia graminis) arrives that overcomes the resistance gene carried by this cultivar. 4 marks Band 5
Predict the likely outcome for total regional wheat yield in the following three growing seasons, and justify your prediction using lesson content on the trade-off between uniformity and gene-pool diversity.
Q1.1, Trend description (2 marks)
Herd A (natural service) shows essentially flat yield (5800 → 5940 L/cow/yr; ~2.4% rise over 5 seasons). Herd B (AI from local sires) shows a steady increase (6100 → 7240 L; ~19% rise). Herd C (imported elite AI + ET) shows the steepest rise (6350 → 8690 L; ~37% rise), almost double Herd B's gain over the same period.
Q1.2, Why Herd C accelerates fastest (3 marks)
Artificial insemination from imported elite sires lets Herd C concentrate genes from internationally proven high-yield bulls into every breeding event, instead of being limited to whichever local bull is available [1]. Embryo transfer further multiplies offspring from the herd's own elite donor cows, every season many surrogates can produce calves from a single top-genetic-merit donor, so favoured alleles spread through the herd faster than the donor could carry them herself [1]. Combined, these two techniques compress what would otherwise be several generations of selective breeding into one or two, accelerating the rise in mean yield [1].
Q1.3, Biological cost by Season 10 (2 marks)
The most likely cost is a narrower gene pool and rising homozygosity, because so many calves descend from a small number of imported sires and elite donor cows [1]. This typically appears as a rise in hereditary health conditions (as deleterious alleles become more common) and a fall in the herd's resilience to any new disease that targets the shared genotype, consistent with the lesson's discussion of how intensive selective breeding can inadvertently fix deleterious recessive alleles [1]. Accept also: animal welfare concerns from high-production selection.
Q2.1, Trend description (2 marks)
The genetic diversity of this dairy cattle breed's breeding stock has fallen steadily over the 60-year period, from ~150 in 1960 to ~40 in 2020 [1]. The steepest decline coincides with the widespread adoption of AI from elite sires from ~1975 onward [1]. The 2020 value sits below the concern threshold shown on the graph.
Q2.2, Read-off values + percentage change (2 marks)
1975 value ≈ 120; 2020 value ≈ 40 [1]. Percentage decrease ≈ (120 − 40) / 120 × 100 ≈ 67% [1]. Accept ±5 either side of each read-off and ±5% on the final answer.
Q2.3, Same technique, opposite outcomes (2 marks)
AI from elite sires spreads the alleles of a few high-merit bulls across the breed very efficiently, which raises average milk yield per cow [1]. But because so many offspring now descend from a tiny number of ancestor bulls, the breed's gene pool collapses, fewer and fewer distinct allele combinations exist in the population, pushing the diversity index below the concern threshold shown on the graph [1].
Q3, Case study sample response (5 marks)
Over 10 years the stud's AI programme repeatedly used semen from only three elite rams. This concentrates the alleles of those three animals across the whole flock, which narrows the gene pool considerably. The hereditary limb condition most likely became widespread because all offspring carry the same alleles, if one of the three rams carried a deleterious allele for this condition (even in heterozygous form), the repeated breeding programme would spread it through the flock until many animals became homozygous and expressed the condition. This is the lesson's point that intensive selective breeding can inadvertently fix deleterious alleles. The uniform susceptibility to the wool-rust pathogen is explained by the same underlying cause: the flock's genetic uniformity means every animal shares the same immune and resistance profile, so a pathogen that overcomes one animal's defences can sweep through the whole flock. Both problems reflect the lesson's central trade-off: narrowing the gene pool through heavy selective breeding raises productivity in the short term but reduces genetic diversity, increasing vulnerability to both hereditary disease and new pathogens. This also raises animal welfare concerns because the animals suffer from the consequences of that genetic narrowing.
Marking notes: 1 mark for identifying gene-pool narrowing as the cause; 1 mark for explaining the hereditary condition using selective breeding and allele concentration; 1 mark for using gene pool correctly; 1 mark for explaining why uniform susceptibility to the pathogen follows from genetic uniformity; 1 mark for linking both outcomes to the lesson's benefit-vs-risk trade-off and noting the animal welfare consequence.
Q4, Predict-and-justify sample response (4 marks)
Total regional wheat yield is predicted to collapse sharply across the three following seasons. Because controlled pollination has fixed a single cultivar across 90% of the growing area, the regional crop is genetically uniform and shares the same resistance gene; a new rust strain that overcomes that gene therefore meets almost no resistance and can spread rapidly across the whole region [1]. By the end of Season 1 after arrival, infected fields will lose a significant fraction of yield to rust pustules and grain shrivelling; by Season 2 the rust is likely to be endemic and yields may fall to a fraction of baseline; by Season 3, without a new resistance cultivar, the region remains highly vulnerable [1]. This is the exact trade-off described in Card 4, uniformity raised yield in the favourable years but reduced resilience when conditions changed [1]. A more resilient strategy would have been to maintain a wider gene pool (multiple cultivars or controlled pollination programmes that include diverse resistance backgrounds) so that no single pathogen could affect the whole crop simultaneously [1].