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Background and Aims <p>A critical methodological gap exists in quantifying effective rooting depth in deep tropical soils, where conventional sampling protocols and normalisation approaches lead to systematic underestimation and mask management effects. The aim of this study was to introduce and validate a reference-corrected logistic dose–response model for the accurate determination of soybean effective rooting depth and establish a minimum sampling threshold to avoid truncation bias in tropical agrosystems.</p> Methods <p>A long-term cropping systems experiment was evaluated on an Oxisol in southern Brazil. The treatments consisted of soybean cultivated under three cropping systems (winter - summer cropping season): (i) maize (<i>Zea mays</i> L.) - soybean, (ii) ruzigrass (<i>Urochloa ruziziensis</i>) - soybean and (iii) fallow - soybean. The soybean effective rooting depth was measured under seven sampling depths in the soil profile: i) 0-30 cm, ii) 0-60 cm, iii) 0-90 cm, iv) 0-120 cm, v) 0-150 cm, vi) 0-180 cm and vii) 0-210 cm. The root length density was quantified on soil profile by monolith sampling methods. The effective rooting depth was calculated for 80 and 95% of cumulative root distribution and fitted to two modified logistic dose-response curves for each treatment and for a reference treatment. </p> Results <p>We demonstrate that restricting sampling to the upper 0–90&#xa0;cm profile induces a truncation bias exceeding 30% in effective rooting depth estimates. Through systematic monolith sampling to a depth of 210&#xa0;cm, we establish a minimum sampling threshold of 150&#xa0;cm as essential for unbiased characterisation of soybean. The proposed methodology effectively discriminates the root system legacy of preceding cover crops by normalising all treatments against a common reference, thereby overcoming the masking effect of traditional relative distribution models. The results reveal that ruzigrass (<i>Urochloa ruziziensis</i>) promotes a substantially deeper effective rooting depth (153.5&#xa0;at 95% cumulative distribution) than maize (124.4) or fallow (119.3&#xa0;cm). </p> Conclusion <p>This paper provides a robust, standardised protocol for effective rooting depth assessment in tropical agrosystems, with direct implications for modelling water uptake and evaluating drought resilience.&#xa0;We developed and validated a reference-corrected logistic dose–response model. This approach, which normalises all treatments against a common reference (the system with maximum root exploration), successfully discriminated the root system legacy of preceding cover crops. Our results establish a minimum sampling threshold of 150 cm for soybean in Oxisols to avoid truncation bias and systematic underestimation of effective rooting depth.</p>

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Sampling depth and calculation method impact on soybean effective rooting depth in Oxisols

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月15日

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  • Matheus Batista Néri Pereira,
  • John Kennedy dos Santos,
  • Luiz Henrique Quecine Grande,
  • Lucas Henrique Amaro da Silva,
  • João de Andrade Bonetti,
  • Henrique Debiasi,
  • Julio Cezar Franchini,
  • Alvadi Antonio Balbinot Junior,
  • Moacir Tuzzin de Moraes

摘要

Background and Aims

A critical methodological gap exists in quantifying effective rooting depth in deep tropical soils, where conventional sampling protocols and normalisation approaches lead to systematic underestimation and mask management effects. The aim of this study was to introduce and validate a reference-corrected logistic dose–response model for the accurate determination of soybean effective rooting depth and establish a minimum sampling threshold to avoid truncation bias in tropical agrosystems.

Methods

A long-term cropping systems experiment was evaluated on an Oxisol in southern Brazil. The treatments consisted of soybean cultivated under three cropping systems (winter - summer cropping season): (i) maize (Zea mays L.) - soybean, (ii) ruzigrass (Urochloa ruziziensis) - soybean and (iii) fallow - soybean. The soybean effective rooting depth was measured under seven sampling depths in the soil profile: i) 0-30 cm, ii) 0-60 cm, iii) 0-90 cm, iv) 0-120 cm, v) 0-150 cm, vi) 0-180 cm and vii) 0-210 cm. The root length density was quantified on soil profile by monolith sampling methods. The effective rooting depth was calculated for 80 and 95% of cumulative root distribution and fitted to two modified logistic dose-response curves for each treatment and for a reference treatment.

Results

We demonstrate that restricting sampling to the upper 0–90 cm profile induces a truncation bias exceeding 30% in effective rooting depth estimates. Through systematic monolith sampling to a depth of 210 cm, we establish a minimum sampling threshold of 150 cm as essential for unbiased characterisation of soybean. The proposed methodology effectively discriminates the root system legacy of preceding cover crops by normalising all treatments against a common reference, thereby overcoming the masking effect of traditional relative distribution models. The results reveal that ruzigrass (Urochloa ruziziensis) promotes a substantially deeper effective rooting depth (153.5 at 95% cumulative distribution) than maize (124.4) or fallow (119.3 cm).

Conclusion

This paper provides a robust, standardised protocol for effective rooting depth assessment in tropical agrosystems, with direct implications for modelling water uptake and evaluating drought resilience. We developed and validated a reference-corrected logistic dose–response model. This approach, which normalises all treatments against a common reference (the system with maximum root exploration), successfully discriminated the root system legacy of preceding cover crops. Our results establish a minimum sampling threshold of 150 cm for soybean in Oxisols to avoid truncation bias and systematic underestimation of effective rooting depth.