Claim · model-written summary
Cubic models found non-linear patterns in soybean cultivation data.
- Taxon
- soybean
Glycine maxt0 - Outcome
- non-linear patternse0
- Comparator
- cubic modelse0
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentSettingDirectionValueQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Trend analysis using cubic models further confirmed non-linear patterns in the data”
t0“soybean cultivation”
Title
Ashutosh Nayak; Pradeep Mishra; Umesh Singh; et al. International Journal of Statistics and Applied Mathematics 2025. doi:10.22271/maths.2025.v10.i6sa.2056
Other claims from this paper (10)
- Observation Soybean area deviated significantly from randomness.
- Observation Soybean production deviated significantly from randomness.
- Observation Soybean yield deviated significantly from randomness.
- Association Soybean area had strong cubic model fits in Madhya Pradesh and India.
- Association Soybean production had strong cubic model fits in Madhya Pradesh and India.
- Observation Soybean yield trends were weaker and more unstable.
- Observation Soybean cultivation area expanded steadily.
- Observation Soybean production expanded steadily.
- Observation Soybean yield remained inconsistent, particularly in Madhya Pradesh.
- Recommendation The authors call for targeted interventions to improve productivity and stabilize soybean yields.