Opening

LAUNCH · SCIENCE · Lesson 2 of 10

Can a breeder improve two traits at once?

Learning intention

Explain selective breeding and justify a breeding plan using inherited traits, performance evidence and genetic diversity.

Mission: plan a productive, disease-resistant crop.

A good choice must use evidence and survive a second check.

Success looks like

Sequence selection, reproduction, offspring testing and repeated selection.
Choose parents and offspring using both yield and damage evidence.
Explain why selected offspring still vary and why diversity matters.

Retrieval

LAUNCH · SCIENCE · Lesson 2 of 10

Retrieve inheritance

R1. What is an allele?

R2. Are sexual offspring always identical to their parents?

R3. Can growing conditions affect measured yield?

I do

LAUNCH · SCIENCE · Lesson 2 of 10

How selective breeding works

Humans decide which organisms reproduce.

Choose inherited traits, breed, compare offspring, select again.

Repeat across generations.

Selective breeding changes later generations

Diagram description

Four linked steps: choose parents for inherited traits, reproduce, compare varied offspring, and select for the next generation. The repeated cycle changes the breeding population; individual plants do not choose to change their genes.

I do

LAUNCH · SCIENCE · Lesson 2 of 10

Inheritance is a mechanism

Offspring receive alleles from both parents.

A simple model can show inheritance.

Real yield and resistance can involve many genes.

Offspring are not photocopies

Diagram description

Conceptual inheritance model using fictitious allele symbols at two loci. Parents AABB and aabb produce AaBb offspring. This shows transmission of alleles only: yield and disease resistance in the breeding activity are multi-gene traits, not assigned to these symbols.

I do

LAUNCH · SCIENCE · Lesson 2 of 10

Read change across generations

The population mean can shift after selection.

G0 to G3: 34 g to 44 g per plant.

A trend is not a guarantee for every plant.

Selection can shift a population

Diagram description

Constructed sample data: mean grain mass per plant is 34, 39, 43 and 44 g in generations 0 to 3, with the same trial conditions. This illustrates a possible outcome, not a guarantee that yield always rises or that every offspring improves.

I do

LAUNCH · SCIENCE · Lesson 2 of 10

Protect useful variation

Repeated close-relative breeding can reduce diversity.

Some harmful recessive combinations become more likely.

Retain suitable unrelated lines and check offspring.

Keep variation in the breeding population

Diagram description

Two conceptual breeding plans: repeatedly select two close relatives, or include suitable unrelated lines. Less diversity can increase shared vulnerability. Different labels represent family lines, not a count of all genes.

Continue within this stage’s shared time.

We do

LAUNCH · SCIENCE · Lesson 2 of 10

Breeding round 1: choose the parents

W1. Both parents: damage at most 2.

At least one parent: yield at least 45 g.

Use different family lines. Choose and justify.

Constructed sample data: matched trial conditions; lower damage is better. Each line mean comes from 10 plants.
Line / family	Mean grain mass (g/plant)	Disease damage (0–10)
A / F1	48	6
B / F2	40	2
C / F3	46	1
D / F1	52	8

My response — say it, sketch on paper or type

We do

LAUNCH · SCIENCE · Lesson 2 of 10

Breeding round 2: respond to new evidence

W2. Offspring target: yield at least 45 g; damage at most 2.

W3. Choose its next partner: sibling P or unrelated E?

Justify the choice and one needed check.

Constructed sample data: P–S are siblings from B × C; E is from a separate suitable line. One trial per plant.
Candidate / family	Grain mass (g/plant)	Disease damage (0–10)
P / F4	45	1
Q / F4	48	6
R / F4	42	0
S / F4	50	2
E / F5 (unrelated)	45	1

My response — say it, sketch on paper or type

Continue within this stage’s shared time.

Hinge

LAUNCH · SCIENCE · Lesson 2 of 10

What changes after selection?

A breeder repeatedly selects resistant plants.

Choose the best biological explanation.

You do

LAUNCH · SCIENCE · Lesson 2 of 10

Write a two-generation breeding log

Use the shared candidate and offspring evidence.

Record selection, rejection and the reason for each.

Finish with a prediction and a test.

My response — say it, sketch on paper or type

You do

LAUNCH · SCIENCE · Lesson 2 of 10

A decision needs its evidence

I selected … because the table shows …

I rejected … because …

I would check … before the next generation.

My response — say it, sketch on paper or type

Continue within this stage’s shared time.

You do

LAUNCH · SCIENCE · Lesson 2 of 10

Do not promise a perfect crop

Predict a possible shift in the population.

Keep uncertainty about individual offspring.

Name a way to retain diversity.

My response — say it, sketch on paper or type

Continue within this stage’s shared time.

Review

LAUNCH · SCIENCE · Lesson 2 of 10

Peer-check the breeding plan

Can your reader follow both selections?

Ask one question about a trait or risk.

Use the response to improve one decision.

My response — say it, sketch on paper or type

Review

LAUNCH · SCIENCE · Lesson 2 of 10

A strong breeding log

Names a valid selection with two data points.

Explains inheritance, variation and repeated selection.

Includes diversity and a practical next check.

My response — say it, sketch on paper or type

Continue within this stage’s shared time.

Exit

LAUNCH · SCIENCE · Lesson 2 of 10

Transfer the method

E1. Give the four main selective-breeding steps.

E2. Why test offspring before choosing again?

E3. Name one risk of repeatedly using close relatives.

My response — say it, sketch on paper or type

My science task sheets

Choose one route with your teacher. Shared evidence and the exit sheet appear in every route. Your work stays here while the page is open; save it before closing.

Shared evidence | Crop breeding programme

All numbers below are constructed sample data for a paper model. Yield and resistance have inherited components; neither is controlled by a single gene in this activity.

Round 1 rule: choose two parents. Both must have disease damage at most 2. At least one must have mean yield at least 45 g per plant. Use different family lines. Lower damage is better; 0 = no visible damage, 10 = severe damage.

Line / family	Mean grain mass (g/plant)	Disease damage (0–10)
A / F1	48	6
B / F2	40	2
C / F3	46	1
D / F1	52	8

Constructed sample data above: each line mean represents 10 plants in matched trial conditions.

Round 2 target: yield at least 45 g and damage at most 2. P–S are siblings from the selected cross; E is from a separate family. Constructed single-plant observations from one matched trial.

Candidate / family	Grain mass (g/plant)	Disease damage (0–10)
P / F4	45	1
Q / F4	48	6
R / F4	42	0
S / F4	50	2
E / F5 (unrelated)	45	1

W1. Parent choice and reasons. W2. Next offspring choice. W3. Its next partner and one check.

Supported route | Record the decisions

Use the shared evidence. Say, write or dictate the same scientific explanation.

S1. Choose two first parents. Give one damage value for each and the qualifying yield value.S2. Explain why A or D fails the programme rule even though it has high yield.S3. Choose one offspring from P–S with high yield and low damage. Give both values.S4. Choose sibling P or unrelated E as its next partner. Explain one reason and one limitation.

S5. Number the method in the correct order. Compare offspring and select useful ones. Select parents with desired inherited traits. Repeat across generations. Breed the selected parents.

S6. Finish: offspring still need testing because … .

Standard route | Two-generation breeding log

Use exact evidence from the shared page. Your log should make the decisions reproducible.

M1. State the programme goal. Choose round 1 parents using three numerical values and family-line evidence.M2. Reject one alternative parent with a specific reason. Why is yield alone insufficient?M3. Use the offspring evidence to select a next-generation candidate and partner. Explain the genetic-diversity decision.M4. Explain how repeatedly selecting suitable parents can change later generations. Include inheritance and variation.M5. Predict one possible outcome and describe how you would test it fairly before extending the programme.

Stretch route | Does the programme work?

Constructed sample data for a follow-up trial. Both lines used the same growing conditions; values are means of 10 plants. Selection line and comparison line began from the same mixed seed population.

Generation	Selected line mean yield (g/plant)	Comparison line mean yield (g/plant)
G0	34	34
G1	39	35
G2	43	35
G3	44	36

T1. Calculate the G0–G3 change for each line and the difference between those changes. What does the comparison add?T2. Evaluate: “Every plant improved by 10 g because breeding guarantees success.” Use the table and its limitations.T3. Propose two improvements to the evidence before recommending this crop: one about sampling/trial design and one about diversity or disease.T4. Choose S with E or S with P from the shared data. Defend the decision while acknowledging one trade-off.

Exit and reflection | Explain the mechanism

Use short scientific statements. No family or medical examples are needed.

E1. Write the main four steps of selective breeding in order.E2. Why test offspring before choosing the next parents?E3. Name one risk of repeatedly breeding close relatives.L1. What question did your audience ask? Which decision or explanation did you improve?

My next useful step is… Read two trait columns together. Explain selection across generations. Explain genetic diversity as a risk issue. Evaluate comparison data.