Spectral and Phenological Response of Banana (Musa AAA, Simmonds) to Organic Bio-Inputs Based on Trichoderma spp. and Bacillus spp., in the Central Littoral Region of Ecuador: An Evaluation Using UAV and NDVI Index
DOI:
https://doi.org/10.28940/terra.latinam..v44i.2494Keywords:
precision agriculture, plant biostimulation, spectral indices, remote sensing, rhizobacteriaAbstract
Banana (Musa, AAA, Simmonds), is a globally significant crop, yet its sustainable production faces physical, biological, and social challenges. This study evaluated the impact of two organic bioinputs, an in situ formulated fungal consortium and a commercial bacterial product on the agronomic and spectral response of banana using UAV and spectral technology in Los Ríos province, Ecuador. A completely randomized design was implemented with three treatments: T1 (in situ fungal consortium of Trichoderma spp. and Paecilomyces lilacinus), T2 (commercial bacterial consortium of Bacillus spp.), and T3 (control). A DJI Mavic 3M drone equipped with multispectral sensors was used to calculate the Normalized Difference Vegetation Index (NDVI) at 6 and 28 weeks after treatment, alongside phenological measurements at 28 weeks. Both bioinputs significantly improved NDVI values compared to the control (p < 0.05). T1 showed the best performance with a final NDVI of 0.82 (22.2% improvement over the control), followed by T2 at 0.78 (16.8% improvement). Strong and significant positive correlations (p < 0.01) were found between NDVI and all agronomic variables: plant height (r = 0.8167), pseudostem diameter (r = 0.8572), and leaf number (r = 0.8330). The Kruskal-Wallis analysis confirmed significant differences among all treatments, highlighting the superiority of the in-situ consortium (T1), developed with local samples, due to its better adaptation to regional conditions. The strong correlations validate NDVI as a non-destructive and precise indicator of banana structural growth. This study demonstrates that organic bioinputs, particularly locally formulated multifunctional consortia, can significantly enhance the physiological and agronomic status of banana crops, while UAV-based remote sensing provides an efficient tool for rapid assessment and decision-making in precision agriculture programs for banana cultivation.
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References
Aeberli, A., Johansen, K., Robson, A., Lamb, D. W., & Phinn, S. (2021). Detection of Banana Plants Using Multi-Temporal Multispectral UAV Imagery. Remote Sensing 2021, Vol. 13, Page 2123, 13(11), 2123. https://doi.org/10.3390/RS13112123
Aeberli, A. ;, Phinn, S. ;, Johansen, K. ;, Robson, A. ;, Lamb, D. W., Aeberli, A., Phinn, S., Johansen, K., Robson, A., & Lamb, D. W. (2023). Characterisation of Banana Plant Growth Using High-Spatiotemporal-Resolution Multispectral UAV Imagery. Remote Sensing 2023, Vol. 15, Page 679, 15(3), 679. https://doi.org/10.3390/RS15030679
Alfiky, A., & Weisskopf, L. (2021). Deciphering Trichoderma–Plant–Pathogen Interactions for Better Development of Biocontrol Applications. Journal of Fungi 2021, Vol. 7, Page 61, 7(1), 61. https://doi.org/10.3390/JOF7010061
Beaumelle, L., Tison, L., Eisenhauer, N., Hines, J., Malladi, S., Pelosi, C., Thouvenot, L., & Phillips, H. R. P. (2023). Pesticide effects on soil fauna communities—A meta-analysis. Journal of Applied Ecology, 60(7), 1239–1253. https://doi.org/10.1111/1365-2664.14437;PAGE:STRING:ARTICLE/CHAPTER
Bertola, M., Ferrarini, A., & Visioli, G. (2021). Improvement of Soil Microbial Diversity through Sustainable Agricultural Practices and Its Evaluation by -Omics Approaches: A Perspective for the Environment, Food Quality and Human Safety. Microorganisms 2021, Vol. 9, Page 1400, 9(7), 1400. https://doi.org/10.3390/MICROORGANISMS9071400
Bhandari, M., Chang, A., Jung, J., Ibrahim, A. M. H., Rudd, J. C., Baker, S., Landivar, J., Liu, S., & Landivar, J. (2023). Unmanned aerial system-based high-throughput phenotyping for plant breeding. Plant Phenome Journal, 6(1), e20058. https://doi.org/10.1002/PPJ2.20058;WGROUP:STRING:PUBLICATION
Edelstein, C. P., Isaac, M. E., Orozco-Aguilar, L., Peguero, F., Delgado-Rodríguez, D., & Cerda, R. H. (2024). Effects of functional diversity on ecosystem services in cocoa agroforestry systems in Costa Rica. Frontiers in Sustainable Food Systems, 8, 1507555. https://doi.org/10.3389/FSUFS.2024.1507555/BIBTEX
Fahad, S., Chavan, S. B., Chichaghare, A. R., Uthappa, A. R., Kumar, M., Kakade, V., Pradhan, A., Jinger, D., Rawale, G., Yadav, D. K., Kumar, V., Farooq, T. H., Ali, B., Sawant, A. V., Saud, S., Chen, S., & Poczai, P. (2022). Agroforestry Systems for Soil Health Improvement and Maintenance. Sustainability 2022, Vol. 14, Page 14877, 14(22), 14877. https://doi.org/10.3390/SU142214877
FAO. (2024). Agricultural production statistics 2010–2023. FAO ; https://openknowledge.fao.org/handle/20.500.14283/cd3755en
Gamez, R., Cardinale, M., Montes, M., Ramirez, S., Schnell, S., & Rodriguez, F. (2019). Screening, plant growth promotion and root colonization pattern of two rhizobacteria (Pseudomonas fluorescens Ps006 and Bacillus amyloliquefaciens Bs006) on banana cv. Williams (Musa acuminata Colla). Microbiological Research, 220, 12–20. https://doi.org/10.1016/J.MICRES.2018.11.006
Gargiulo, J., Clark, C., Lyons, N., de Veyrac, G., Beale, P., & Garcia, S. (2020). Spatial and Temporal Pasture Biomass Estimation Integrating Electronic Plate Meter, Planet CubeSats and Sentinel-2 Satellite Data. Remote Sensing 2020, Vol. 12, Page 3222, 12(19), 3222. https://doi.org/10.3390/RS12193222
Greenfield, L. M., Graf, M., Rengaraj, S., Bargiela, R., Williams, G., Golyshin, P. N., Chadwick, D. R., & Jones, D. L. (2022). Field response of N2O emissions, microbial communities, soil biochemical processes and winter barley growth to the addition of conventional and biodegradable microplastics. Agriculture, Ecosystems & Environment, 336, 108023. https://doi.org/10.1016/J.AGEE.2022.108023
Gu, Q., Yang, Y., Yuan, Q., Shi, G., Wu, L., Lou, Z., Huo, R., Wu, H., Borriss, R., & Gao, X. (2017). Bacillomycin D produced by Bacillus amyloliquefaciens is involved in the antagonistic interaction with the plantpathogenic fungus Fusarium graminearum. Applied and Environmental Microbiology, 83(19), 1075–1092. https://doi.org/10.1128/AEM.01075-17;WGROUP:STRING:PUBLICATION
Han, Y., Tang, C., Zhao, Q., Fan, S., Yang, P., & Zhang, J. (2022). Butyrate Mitigates Lipopolysaccharide-Induced Intestinal Morphological Changes in Weanling Piglets by Regulating the Microbiota and Energy Metabolism, and Alleviating Inflammation and Apoptosis. Microorganisms 2022, Vol. 10, Page 2001, 10(10), 2001. https://doi.org/10.3390/MICROORGANISMS10102001
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del Río, J. F., Wiebe, M., Peterson, P., … Oliphant, T. E. (2020). Array programming with NumPy. Nature 2020 585:7825, 585(7825), 357–362. https://doi.org/10.1038/s41586-020-2649-2
Manganiello, G., Nicastro, N., Caputo, M., Zaccardelli, M., Cardi, T., & Pane, C. (2021). Functional Hyperspectral Imaging by High-Related Vegetation Indices to Track the Wide-Spectrum Trichoderma Biocontrol Activity Against Soil-Borne Diseases of Baby-Leaf Vegetables. Frontiers in Plant Science, 12, 630059. https://doi.org/10.3389/FPLS.2021.630059/FULL
Martínez-Solórzano, G. E., & Rey-Brina, J. C. (2021). Bananos (Musa AAA): Importancia, producción y comercio en tiempos de Covid-19. Agronomía Mesoamericana, 32(3), 1034–1046. https://doi.org/10.15517/am.v32i3.43610
Miao, Y., Wang, L., Peng, C., Li, H., Li, X., & Zhang, M. (2022a). Banana plant counting and morphological parameters measurement based on terrestrial laser scanning. Plant Methods, 18(1), 66. https://doi.org/10.1186/S13007-022-00894-Y
Miao, Y., Wang, L., Peng, C., Li, H., Li, X., & Zhang, M. (2022b). Banana plant counting and morphological parameters measurement based on terrestrial laser scanning. Plant Methods, 18(1), 66. https://doi.org/10.1186/S13007-022-00894-Y
Oliveira Almeida, N., Martins de Oliveira, C., José Ulhoa, C., de Carvalho Barros Côrtes, M. V., Lobo Júnior, M., & Rúbia da Rocha, M. (2022). Trichoderma harzianum and Trichoderma asperellum are potential biocontrol agents of Meloidogyne javanica in banana cv. Grande Naine. Biological Control, 175, 105054. https://doi.org/10.1016/J.BIOCONTROL.2022.105054
Omer, E., Szlatenyi, D., Csenki, S., Alrwashdeh, J., Czako, I., & Láng, V. (2024). Farming Practice Variability and Its Implications for Soil Health in Agriculture: A Review. Agriculture 2024, Vol. 14, Page 2114, 14(12), 2114. https://doi.org/10.3390/AGRICULTURE14122114
Poortinga, A., Clinton, N., Saah, D., Cutter, P., Chishtie, F., Markert, K. N., Anderson, E. R., Troy, A., Fenn, M., Tran, L. H., Bean, B., Nguyen, Q., Bhandari, B., Johnson, G., & Towashiraporn, P. (2018). An Operational Before-After-Control-Impact (BACI) Designed Platform for Vegetation Monitoring at Planetary Scale. Remote Sensing 2018, Vol. 10, Page 760, 10(5), 760. https://doi.org/10.3390/RS10050760
Sishodia, R. P., Ray, R. L., & Singh, S. K. (2020). Applications of Remote Sensing in Precision Agriculture: A Review. Remote Sensing 2020, Vol. 12, Page 3136, 12(19), 3136. https://doi.org/10.3390/RS12193136
Tian, L., Zhang, W., Zhou, G. D., Li, S., Wang, Y., Yang, B., Bai, T., Fan, H., He, P., & Zheng, S. J. (2023). A biological product of Bacillus amyloliquefaciens QST713 strain for promoting banana plant growth and modifying rhizosphere soil microbial diversity and community composition. Frontiers in Microbiology, 14, 1216018. https://doi.org/10.3389/FMICB.2023.1216018/BIBTEX
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., … Vázquez-Baeza, Y. (2020). SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods 2020 17:3, 17(3), 261–272. https://doi.org/10.1038/s41592-019-0686-2
Wang, M., Lin, T., Wang, L., Lin, A., Zou, K., Xu, X., Zhou, Y., Peng, Y., Meng, Q., Qian, Y., Deng, G., Wu, Z., Chen, J., Lin, J., Zhang, M., Zhu, W., Zhang, C., Zhang, D., Goh, R. S. M., … Fu, H. (2023). Uncertainty-inspired open set learning for retinal anomaly identification. Nature Communications 2023 14:1, 14(1), 6757-. https://doi.org/10.1038/s41467-023-42444-7
Wang, Y., Liao, J., Zhu, D., Ma, W., & Danesh, Y. R. (2025). Harnessing Beneficial Microbes and Sensor Technologies for Sustainable Smart Agriculture. Sensors 2025, Vol. 25, Page 6631, 25(21), 6631. https://doi.org/10.3390/S25216631
Wei, J., Liu, G., Sun, M., Wang, H., Yang, P., Cheng, S., Huang, L., Wei, S., & Liu, D. (2025a). Comprehensive analysis of morphology, transcriptomics, and metabolomics of banana (Musa spp.) molecular mechanisms related to plant height. Frontiers in Plant Science, 16, 1509193. https://doi.org/10.3389/FPLS.2025.1509193/FULL
Wei, J., Liu, G., Sun, M., Wang, H., Yang, P., Cheng, S., Huang, L., Wei, S., & Liu, D. (2025b). Comprehensive analysis of morphology, transcriptomics, and metabolomics of banana (Musa spp.) molecular mechanisms related to plant height. Frontiers in Plant Science, 16, 1509193. https://doi.org/10.3389/FPLS.2025.1509193/FULL
Yánez-Cajo, D., Vásconez-Montúfar, G., Villamar-Torres, R. O., Godoy-Montiel, L., Jazayeri, S. M., Pérez-Porras, F., & Mesas-Carrascosa, F. (2025). Banana Yield Prediction Using Random Forest, Integrating Phenology Data, Soil Properties, Spectral Technology, and UAV Imagery in the Ecuadorian Littoral Region. Sustainability 2025, Vol. 17, Page 10098, 17(22), 10098. https://doi.org/10.3390/SU172210098
Yin, H., Li, B., Liu, Y. de, Zhang, F., Su, C. tao, & Ou-yang, A. guo. (2022). Detection of early bruises on loquat using hyperspectral imaging technology coupled with band ratio and improved Otsu method. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 283, 121775. https://doi.org/10.1016/J.SAA.2022.121775
