Quality changes in high and low oil content canola during storage: Part II – Mathematical models to predict germination

• Published in: Journal of stored products research Vol. 59; pp. 328 - 337
• Main Authors: Jian, Fuji, Sun, Ke, Chelladurai, Vellaichamy, Jayas, Digvir S., White, Noel D.G.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.10.2014; Elsevier
• Subjects: Agronomy. Soil science and plant productions; Biological and medical sciences; Canola; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; Germination; Harvesting. Postharvest. Storage; Mathematical model; Rapeseed; Storage; Vegetative propagation. Sowing and planting. Harvesting; Storage; Canola; Mathematical model; Rapeseed; Germination; Low content; Brassica napus var. oleifera; Oil content; Prediction; Stored food product; Forecast model; Cruciferae; Dicotyledones; Angiospermae; Spermatophyta; Oil plant (vegetal)
• ISSN: 0022-474X; 1879-1212
• DOI: 10.1016/j.jspr.2014.05.007

Novel mathematical models to predict germination of canola (including rapeseed) stored under laboratory and field conditions were developed with certain assumptions. The models were developed based on the data collected under laboratory condition (constant temperatures). The hypothesis of the developed models was that germination of stored canola was influenced by temperature, moisture content, storage time, and airtightness. The effect of these factors on germination of stored canola was the product of effective storage time and interactive effect of temperature, moisture content, storage time, and airtightness. Data collected under both laboratory and filed conditions were used to calibrate and verify the developed models. The prediction accuracy of the models associated with field conditions (except canola seeds with 14% moisture content stored inside silo bags) was higher than that under laboratory conditions. The developed models could visually or mathematically predict germination of canola or rapeseed stored under any condition. The developed models explained more than 96% variation of observed germination of the canola or rapeseed seeds with ≤10% moisture content stored inside a flat bottom bin or commercial silo bags. •Mathematical models were developed for predicting germination.•Models predicted germination of canola or rapeseed under any storage condition.•Models explained ≥96% variation of seed germination under field conditions.•Predictions of models were better under field than laboratory conditions.