11 SEED TESTING INTERNATIONAL APRIL 2026 FEATURE ARTICLE Discussion SABIMA captures seed vigour quantitatively and objectively. Strong correlations with manual evaluation (R² > 0.90) demonstrate that SABIMA measures to the same quality that technicians assess visually, but without subjective bias. The field emergence correlation (R² = 0.82) validates SABIMA as a strong candidate for a vigour method with real-world predictive capability. Beyond replicating manual evaluation results, SABIMA has potential applications where traditional methods are limited. The quantitative nature of surface area measurements makes SABIMA suitable for evaluating priming effects [4], where enhanced germination rate and uniformity are key performance indicators. For biological seed treatments [5], which can interact differently with seed physiology, SABIMA’s sensitivity to subtle vigour changes offers advantages over binary classification systems. SABIMA could also serve as an alternative to radicle emergence tests [6] or usable plants tests [2], providing continuous measurements of seedling development rather than categorical assessments. Limitations: (i) No individual seedling data due to overlaps, the method aggregates all seedlings in a single paper sheet; (ii) crop- specific quality thresholds may be needed; (iii) cannot calculate % normal seedlings like traditional methods. Future Development: Expand to other crops, compare performance to radicle emergence method [6], optimise imaging model, integrate into laboratory workflows. Conclusions SABIMA’s strong correlations with manual evaluation (R² = 0.902 wheat, R² = 0.918 corn) and field emergence (R² = 0.82) establish it as a good candidate for a vigour evaluation method. For seed safety, where detecting subtle vigour impacts is critical, SABIMA’s objectivity offers distinct advantages over subjective visual assessment. SABIMA also has the potential to detect low vigour seed lots in the seed industry, and to evaluate uniformity and priming effects [4] as an alternative to radicle emergence or usable plants tests [2,6]. As the industry develops sophisticated treatments including biologicals [5], tools combining automation, objectivity and predictive power become increasingly valuable. Acknowledgements The author thanks Pouria Sadeghi-Teheran (Syngenta CP R&D, Switzerland) for creating the model; Helen Day (NIAB, UK) for facilitating germination studies; and Brent Reschly (Syngenta Seeds, USA) for coordinating field trials. References [1] ISTA (2023). International Rules for Seed Testing. International Seed Testing Association, Wallisellen, Switzerland. [2] Hampton, J.G. and TeKrony, D.M. (1995). Handbook of Vigour Test Methods, 3rd Edition. International Seed Testing Association, Zurich, Switzerland. [3] Marcos-Filho, J. (2015). Seed vigor testing: an overview of the past, present and future perspective. Scientia Agricola, 72(4), 363–374. [4] Paparella, S., Araújo, S.S., Rossi, G., Wijayasinghe, M., Carbonera, D. and Balestrazzi, A. (2015). Seed priming: state of the art and new perspectives. Plant Cell Reports, 34(8), 1281–1293. [5] O’Callaghan, M. (2016). Microbial inoculation of seed for improved crop performance: issues and opportunities. Applied Microbiology and Biotechnology, 100(13), 5729–5746. [6] Matthews, S. and Khajeh Hosseini, M. (2006). Mean germination time as an indicator of emergence performance in soil of seed lots of maize (Zea mays). Seed Science and Technology, 34(2), 339–347. Figure 3. Corn field emergence correlation: regression plot showing SABIMA shoot surface area (cm2) vs field emergence at 150 growing degree units (GDU, %) Figure 2. Corn correlation between SABIMA and manual evaluation: [left] regression plot showing SABIMA total surface area (cm2) vs % normal seedlings; [right] representative seedling images showing high vigour sample (robust root and shoot development) and low vigour sample (stunted growth)
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