Agriculture & Future Food Systems · Article
Evaluate Sequences Across Seasons
Compare crop sequences with consistent records of useful harvest, variability, weeds, soil change and the resources committed over time.
Preparation and related reading
Shared Foundations
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This article helps you
- Choose a common product, area and time basis for a sequence comparison.
- Distinguish an observed average from variability and reliable future performance.
- Retain management history and multiple outcomes when judging a rotation.
One harvest is only one view
A new sequence produces an excellent harvest. The grower wants to expand it immediately, but the crop followed an unusually favourable season. Rotation effects unfold through previous hosts, residues, roots and management. One result cannot separate all those influences or describe the entire sequence.
State the question: performance of a particular test crop, total useful output across the sequence, weed control, soil function or operating cost. These measures can disagree. The disease-break, cover-crop and residue articles explain processes; evaluation asks whether their combined practical outcomes persist.
Keep products, land and time comparable
For a test-crop comparison, retain crop identity, harvested condition, area basis and phase in the sequence. Do not compare wet roots directly with dry grain or omit the years occupied by a cover merely because no commercial harvest occurred. The whole sequence can include several products that need separate reporting or an explicit common functional basis.
A chronological record alone confounds sequence with weather when different practices occur in different years. Where practical, comparable repeated units and phased rotations allow relevant crops or phases to be observed in the same seasons. Such a design improves the comparison; it does not automatically remove every field difference.
Retain history and measurement method
Map where each crop and cover grew and record actual operations, cultivars, inputs, dates and deviations. Record relevant weather, disease, emergence and harvest condition. Keep observations attached to their fields and independently treated units rather than combining them into a convenient total before analysis.
Measure weeds with a stated method and crop stage; counts, cover and biomass are different outcomes. For soil change, retain sampling locations, depth, timing and method. A near-surface carbon concentration cannot by itself demonstrate a whole-profile carbon-stock increase, especially if tillage or bulk density changed. Apply the published soil-measurement principles.
Read average and spread together
Consider four hypothetical matched harvest observations of the same test crop at the same sequence phase, with comparable area and grain condition. Sequence A gives 4, 5, 4 and 3 t/ha; B gives 5, 2, 6 and 3 t/ha. Both arithmetic means are 4 t/ha. The averages alone conceal different observed spreads.
A’s range is 5 − 3 = 2 t/ha; B’s is 6 − 2 = 4 t/ha. Range is only maximum minus minimum in this small invented set. It is not a statistical test, a probability of crop failure or a reliable estimate of future stability. It also says nothing about the sequences’ other crops or input costs.
| Matched observation | Sequence A | Sequence B |
|---|---|---|
| 1 | 4 t/ha | 5 t/ha |
| 2 | 5 t/ha | 2 t/ha |
| 3 | 4 t/ha | 6 t/ha |
| 4 | 3 t/ha | 3 t/ha |
| Arithmetic mean | 4 t/ha | 4 t/ha |
| Observed range | 2 t/ha | 4 t/ha |
The same mean can hide different spreads
Read the diagram as text
Four hypothetical matched test-crop observations have equal means, while their observed maximum-minus-minimum ranges differ.
Parts
- A: 4, 5, 4, 3 t/ha
- Same test crop and phase; original hypothetical observations.
- B: 5, 2, 6, 3 t/ha
- Comparable product, area and matched observation periods.
- Both means: 4 t/ha
- A and B each total 16 across four observations; divide by 4.
- Ranges: A 2; B 4 t/ha
- Retain spread; no future probability or statistical test supplied.
Connections
- A: 4, 5, 4, 3 t/ha → Both means: 4 t/ha: Calculate arithmetic mean
- B: 5, 2, 6, 3 t/ha → Both means: 4 t/ha: Calculate arithmetic mean
- Both means: 4 t/ha → Ranges: A 2; B 4 t/ha: Also inspect the original spread
Retain benefits, costs and poor results
Examine weed shifts, diseases, soil condition, nutrient and water use alongside marketable harvest and work. A sequence may reduce one pressure while creating another. Lower work in one crop can be offset by cover establishment or later handling; wider crop diversity can require different skills, storage or markets.
Keep failed establishment, low harvests and missing observations visible. An unmeasured outcome is not zero; an actual zero harvest is not missing data. Appropriate statistical analysis depends on repeated units, design and uncertainty. A locally promising pattern should not become a universal claim of greater sustainability or profitability.
Compare complete cycles and revise
Follow the intended sequence for enough time to address its question and retain evidence across contrasting conditions. Long-term research illustrates why treatment history, repeated test crops and soil records matter. It does not supply a universal cycle length or a result transferable to every site.
Use the evidence to revise a bounded choice: a host break, cover transition, residue operation or workload bottleneck. Preserve the former plan and its outcomes. A useful sequence evaluation connects production with its resources and soil effects over time, rather than ranking systems from a single favourable harvest.
Worked examples
Equal means, different observed ranges
What do the hypothetical test-crop values show?
- A mean: (4 + 5 + 4 + 3)/4 = 4 t/ha.
- B mean: (5 + 2 + 6 + 3)/4 = 4 t/ha.
- A range: 5 − 3 = 2 t/ha; B range: 6 − 2 = 4 t/ha.
The small sets have equal means and different observed ranges. They do not establish a statistically supported stability difference or whole-sequence superiority.
Separate zero from missing
A failed crop produced no harvest, while another field has no harvest measurement. Should both entries be recorded as zero?
- Keep the observed failure and its true zero harvest.
- Mark the absent measurement as missing, with its reason if known.
- Use an analysis that addresses missing information rather than inventing its value.
No. Zero is an observed outcome; missing means the outcome is unknown.
Check your understanding
Do equal mean test-crop yields establish equal total sequence performance?
Show answer and reasoning
No.
Other crops, resource use, work and soil outcomes are outside that mean.
Does the invented range prove how variable next year’s crop will be?
Show answer and reasoning
No.
It describes only four supplied observations and carries no probability model.
Should a low harvest remain in the sequence evaluation?
Show answer and reasoning
Yes.
Removing it would hide risk and overstate performance.
Key ideas
- State which sequence outcome the comparison answers.
- Keep products, area, time and management history attached to results.
- Read observed spread alongside the mean without inventing certainty.
- Retain complete cycles, resource costs and contrary outcomes.
References
Sources supporting the explanations and examples in this article.