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Background and Aims <p>Above ground botanical composition in biodiverse ecosystems can be reliably estimated through taxonomic and morphological identification, but below ground identification is more challenging due to the absence of distinctive root characteristics. In this study, we calibrated and applied a chloroplast DNA-based method to quantify the botanical composition of root mass in tropical forage grass mixtures.</p> Methods <p>The approach focused on three perennial grass species: <i>Andropogon gayanus</i> cv. Planaltina (andropogon grass), <i>Panicum maximum</i> cv. Massai (massai grass), and <i>Brachiaria brizantha</i> cv. BRS Piatã (piata grass). Calibration was conducted using four artificial DNA mixtures with known dry matter proportions: mixture 1 = 33%:33%:33%, mixture 2 = 60%:20%:20%, mixture 3 = 20%:60%:20%, and mixture 4 = 20%:20%:60%.</p> Results <p>Differences between actual and estimated proportions were 0.10 ± 0.01% for andropogon, –8.97 ± 0.99% for massai, and 11.9 ± 0.29% for piata grass. Polynomial correction curves were used to adjust estimates. The method was then applied to root samples collected seasonally over two years from a pasture initially established with equal seeding proportions of each species. Above ground composition was determined via hand separation. A strong positive correlation (R = 0.88) between above- and below-ground botanical proportions indicated consistent patterns in this managed pasture system, while the method’s validity was primarily supported by the calibration with artificial DNA mixtures.</p> Conclusion <p>This calibrated molecular approach provides a useful indicator of below-ground species abundance, although some residual biases remained even after calibration, such as the overestimation of Piata and the underestimation of Massai in specific mixtures. Therefore, the method should be interpreted as a complementary tool that enhances ecological assessments in managed grasslands rather than as a stand-alone quantitative measure.</p>

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Root mass botanical composition of perennial forage grasses mixed pasture: calibration and application of a DNA-chloroplast based method

  • 期刊论文

  • 发表日期：

    2025年11月7日

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  • Alex Marciano dos Santos Silva,
  • Sila Carneiro da Silva,
  • Caio Macret Gomes,
  • Emanoella Karol Saraiva Otaviano,
  • Alexandre Fameli Mammana,
  • Larissa Fernanda Garcia Carvalho,
  • Polyana Cristine Tizioto,
  • Ela Frak,
  • Gaëtan Louarn,
  • Luiz Lehmann Coutinho

摘要

Background and Aims

Above ground botanical composition in biodiverse ecosystems can be reliably estimated through taxonomic and morphological identification, but below ground identification is more challenging due to the absence of distinctive root characteristics. In this study, we calibrated and applied a chloroplast DNA-based method to quantify the botanical composition of root mass in tropical forage grass mixtures.

Methods

The approach focused on three perennial grass species: Andropogon gayanus cv. Planaltina (andropogon grass), Panicum maximum cv. Massai (massai grass), and Brachiaria brizantha cv. BRS Piatã (piata grass). Calibration was conducted using four artificial DNA mixtures with known dry matter proportions: mixture 1 = 33%:33%:33%, mixture 2 = 60%:20%:20%, mixture 3 = 20%:60%:20%, and mixture 4 = 20%:20%:60%.

Results

Differences between actual and estimated proportions were 0.10 ± 0.01% for andropogon, –8.97 ± 0.99% for massai, and 11.9 ± 0.29% for piata grass. Polynomial correction curves were used to adjust estimates. The method was then applied to root samples collected seasonally over two years from a pasture initially established with equal seeding proportions of each species. Above ground composition was determined via hand separation. A strong positive correlation (R = 0.88) between above- and below-ground botanical proportions indicated consistent patterns in this managed pasture system, while the method’s validity was primarily supported by the calibration with artificial DNA mixtures.

Conclusion

This calibrated molecular approach provides a useful indicator of below-ground species abundance, although some residual biases remained even after calibration, such as the overestimation of Piata and the underestimation of Massai in specific mixtures. Therefore, the method should be interpreted as a complementary tool that enhances ecological assessments in managed grasslands rather than as a stand-alone quantitative measure.