Assessing the effects of senescence on mesic subtropical grass quality and quantity using <i>in situ</i> and remotely sensed data
Forage quality is one of the most important factors that determines the distribution and grazing patterns of livestock. During senescence, herbaceous plants redistribute nutrients from leaves to roots. This study quantified the decline in nGongoni (Aristida junciformis) grass quality and quantity due to senescence using in situ and Sentinel-2 data. Forage availability status was assessed based on dry matter (DM) content. Chlorophyll content and biomass were used as surrogates for pre-senescent and senescent grass quality and quantity, while average biomass was used to determine the DM. The Random Forest regression yielded coefficients of determination (R2) of 91.3% and 96.6% plus root mean square errors (RMSEs) of 2.12 and 0.55 µg Chl cm−2 for pre-senescent and senescent grass qualities, respectively. The model further yielded R2 values of 70.9% and 94.2%, and RMSEs of 0.34 and 0.02 kg m−2, for pre-senescent and senescent grass quantities, respectively. Optimal predictions of pre-senescent and senescent grass qualities and quantities were achieved using the red-edge and its associated indices, as well as the near-infrared and red band derivatives. The results also showed a decrease in grass quality (17.2 µg Chl cm−2) and quantity (0.89 kg m−2) following senescence. This study helps to understand variability in forage quality and quantity through space and time.
Authors
- Rob Slotow (ORCID: https://orcid.org/0000-0001-9469-1508)
- Mbulisi Sibanda (ORCID: https://orcid.org/0000-0002-4589-7099)
- Lwando Royimani (ORCID: https://orcid.org/0000-0003-4416-6910)
- Onisimo Mutanga (ORCID: https://orcid.org/0000-0002-7358-8111)
- Timothy Dube (ORCID: https://orcid.org/0000-0003-3456-8991)
Institutions
- RIKEN Center for Sustainable Resource Science (JP)
- University of the Western Cape (ZA)
- University of KwaZulu-Natal (ZA)
Publication Details
- Journal
- African Journal of Range and Forage Science
- Published
- 2026-06-19
- DOI
- https://doi.org/10.2989/10220119.2026.2649134
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Research Foundation