Farmers’ knowledge and perceptions of Cassava (Manihot esculenta Crantz) diseases and management

Authors

  • Dickmi Vaillam Claudette Faculty of Agronomy and Agricultural Sciences, University of Dschang, P.O. Box 96, Dschang, West Region, Cameroon
  • Tchouamo Isaac Roger Faculty of Agronomy and Agricultural Sciences, University of Dschang, P.O. Box 96, Dschang, West Region, Cameroon

DOI:

https://doi.org/10.25081/jsa.2024.v8.9000

Keywords:

Farmers’ knowledge, Farmers’ perception, CMD, CMD management

Abstract

This study aimed to examine farmers’ understanding and views on Cassava diseases and control methods. To achieve the former, k-means clustering and Principal Component Analysis (PCA) were used to identify and visualize response patterns for each group of variables relating to farmers’ understanding of Cassava diseases and control methods, and heatmaps were used to detail the characteristics of each pattern. To achieve the latter, bar plots were used to visualize variables related to farmers’ views. Out of 22 response patterns relating to causes of Cassava Mosaic Disease (CMD), 11 didn’t link a virus to CMD symptoms, while only one pattern associated CMD symptoms with a virus, the whitefly, and infected cuttings, indicating a lack of farmers’ knowledge on cassava viral diseases. Also, only 18.88% of farmers know about Cassava diseases and management technologies. This study highlights the urgent need for education and resources for farmers to safeguard their crops and livelihoods.

Downloads

Download data is not yet available.

References

Adebayo, W. G. (2023). Cassava production in africa: A panel analysis of the drivers and trends. Heliyon, 9(9), e19939. https://doi.org/10.1016/j.heliyon.2023.e19939

Alleyne, A., Mason, S., & Vallès, Y. (2023). Characterization of the Cassava Mycobiome in Symptomatic Leaf Tissues Displaying Cassava Superelongation Disease. Journal of Fungi, 9(12), 12. https://doi.org/10.3390/jof9121130

Alves, A. A. C., de Oliveira, L. A., & da Silva Motta, J. (2022). Transferring Cassava Processing Technology from Brazil to Africa. In G. Thiele, M. Friedmann, H. Campos, V. Polar & J. W. Bentley (Eds.), Root, Tuber and Banana Food System Innovations: Value Creation for Inclusive Outcomes (pp. 207-239) Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-030-92022-7_7

Bailey, S. (2012). Principal Component Analysis with Noisy and/or Missing Data. Publications of the Astronomical Society of the Pacific, 124(919), 1015-1023. https://doi.org/10.1086/668105

Bartkowski, J., Odindo, M. O., & Otieno, W. A. (1988). Some Fungal Pathogens of the Cassava Green Spider Mites Mononychellus spp. (Tetranychidae) in Kenya. International Journal of Tropical Insect Science, 9(4), 457-459. https://doi.org/10.1017/S174275840001095X

Bateni, M., Cohen-Addad, V., Epasto, A., & Lattanzi, S. (2024). A Scalable Algorithm for Individually Fair K-means Clustering. arXiv, arXiv:2402.06730. https://doi.org/10.48550/arXiv.2402.06730

Bloom, E. H., Atallah, S. S., & Casteel, C. L. (2024). Motivating organic farmers to adopt practices that support the pest-suppressive microbiome relies on understanding their beliefs. Renewable Agriculture and Food Systems, 39, e8. https://doi.org/10.1017/S174217052400005X

Bottrell, D. G., & Schoenly, K. G. (2018). Integrated pest management for resource-limited farmers: Challenges for achieving ecological, social and economic sustainability. The Journal of Agricultural Science, 156(3), 408-426. https://doi.org/10.1017/S0021859618000473

Brévault, T., & Clouvel, P. (2019). Pest management: Reconciling farming practices and natural regulations. Crop Protection, 115, 1-6. https://doi.org/10.1016/j.cropro.2018.09.003

Brito, A. C., Oliveira, S. A. S., & Oliveira, E. J. (2017). Genome-wide association study for resistance to cassava root rot. The Journal of Agricultural Science, 155(9), 1424-1441. https://doi.org/10.1017/S0021859617000612

Burns, A., Gleadow, R., Cliff, J., Zacarias, A., & Cavagnaro, T. (2010). Cassava: The Drought, War and Famine Crop in a Changing World. Sustainability, 2(11), 3572-3607. https://doi.org/10.3390/su2113572

Capó, M., Pérez, A., & Lozano, J. A. (2018). An efficient K -means clustering algorithm for massive data. arXiv, arXiv:1801.02949. https://doi.org/10.48550/arXiv.1801.02949

Chavez, V. A., Milne, A. E., van den Bosch, F., Pita, J., & McQuaid, C. F. (2022). Modelling cassava production and pest management under biotic and abiotic constraints. Plant Molecular Biology, 109, 325-349. https://doi.org/10.1007/s11103-021-01170-8

Chen, E., Chen, X., Jing, W., & Zhang, Y. (2024). Distributed Tensor Principal Component Analysis. arXiv, arXiv:2405.11681. https://doi.org/10.48550/arXiv.2405.11681

Chen, Y. T., & Witten, D. M. (2022). Selective inference for k-means clustering. arXiv, arXiv:2203.15267. https://doi.org/10.48550/arXiv.2203.15267

Clum, C., Mixon, D. G., Villar, S., & Xie, K. (2022). Sketch-and-solve approaches to k-means clustering by semidefinite programming. arXiv, arXiv:2211.15744. https://doi.org/10.48550/arXiv.2211.15744

da Silva, J. S. A., Alves, V. C. S., da Silva, S. F., do Nascimento Barbosa, R., de Souza, C. A. F., da Costa, D. P., Machado, A. R., de Medeiros, E. V., & de Souza-Motta, C. M. (2024). Diaporthe ueckeri causing cassava root rot in Pernambuco, Brazil. Crop Protection, 184, 106811. https://doi.org/10.1016/j.cropro.2024.106811

Demšar, U., Harris, P., Brunsdon, C., Fotheringham, A. S., & McLoone, S. (2013). Principal Component Analysis on Spatial Data: An Overview. Annals of the Association of American Geographers, 103(1), 106-128. https://doi.org/10.1080/00045608.2012.689236

Dorabiala, O., Aravkin, A., & Kutz, J. N. (2023). Ensemble Principal Component Analysis. arXiv, arXiv:2311.01826. https://doi.org/10.48550/arXiv.2311.01826

Dorabiala, O., Dabke, D. V., Webster, J., Kutz, N., & Aravkin, A. (2024). Spatiotemporal k-means. arXiv, arXiv:2211.05337. https://doi.org/10.48550/arXiv.2211.05337

Doungous, O., Masky, B., Levai, D. L., Bahoya, J. A. L., Minyaka, E., Mavoungou, J. F., Mutuku, J. M., & Pita, J. S. (2022). Cassava mosaic disease and its whitefly vector in Cameroon: Incidence, severity and whitefly numbers from field surveys. Crop Protection, 158, 106017. https://doi.org/10.1016/j.cropro.2022.106017

Du, L., Wang, B., Wang, P., Ma, Y., & Liu, H. (2015). Noise Reduction Method Based on Principal Component Analysis With Beta Process for Micro-Doppler Radar Signatures. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(8), 4028-4040. https://doi.org/10.1109/JSTARS.2015.2451004

Ekundayo, J. A., & Daniel, T. M. (1973). Cassava rot and its control. Transactions of the British Mycological Society, 61(1), 27-32. https://doi.org/10.1016/S0007-1536(73)80084-1

Elhaik, E. (2022). Principal Component Analyses (PCA)-based findings in population genetic studies are highly biased and must be reevaluated. Scientific Reports, 12, 14683. https://doi.org/10.1038/s41598-022-14395-4

Elliot, S. L., Mumford, J. D., de Moraes, G. J., & Sabelis, M. W. (2002). Age-Dependent Rates of Infection of Cassava Green Mites by a Fungal Pathogen in Brazil. Experimental & Applied Acarology, 27, 169-180. https://doi.org/10.1023/A:1021644321360

Ergun, J. C., Feng, Z., Silwal, S., Woodruff, D. P., & Zhou, S. (2022). Learning-Augmented $k$-means Clustering. arXiv, arXiv:2110.14094. https://doi.org/10.48550/arXiv.2110.14094

Fanou, A. A., Zinsou, V. A., & Wydra, K. (2017). Cassava Bacterial Blight: A Devastating Disease of Cassava. In V. Y. Waisundara (Eds.), Cassava London, UK: IntechOpen. https://doi.org/10.5772/intechopen.71527

Fathima, A. A., Sanitha, M., Tripathi, L., & Muiruri, S. (2023). Cassava (Manihot esculenta) dual use for food and bioenergy: A review. Food and Energy Security, 12(1), e380. https://doi.org/10.1002/fes3.380

Garst, S., & Reinders, M. (2024). Federated K-means Clustering. arXiv, arXiv:2310.01195. https://doi.org/10.48550/arXiv.2310.01195

Gewers, F. L., Ferreira, G. R., de Arruda, H. F., Silva, F. N., Comin, C. H., Amancio, D. R., & Costa, L. da F. (2018). Principal Component Analysis: A Natural Approach to Data Exploration. ACM Computing Surveys, 54(4), 70. https://doi.org/10.1145/3447755

Gniazdowski, Z. (2017). New Interpretation of Principal Components Analysis. Zeszyty Naukowe WWSI, 11(16), 43-65. https://doi.org/10.26348/znwwsi.16.43

Görtler, J., Spinner, T., Streeb, D., Weiskopf, D., & Deussen, O. (2020). Uncertainty-Aware Principal Component Analysis. IEEE Transactions on Visualization and Computer Graphics, 26(1), 822-831. https://doi.org/10.1109/TVCG.2019.2934812

Guo, Q., Wu, W., Massart, D. L., Boucon, C., & de Jong, S. (2002). Feature selection in principal component analysis of analytical data. Chemometrics and Intelligent Laboratory Systems, 61(1-2), 123-132. https://doi.org/10.1016/S0169-7439(01)00203-9

Hareesh, P. S., Resmi, T. R., Sheela, M. N., & Makeshkumar, T. (2023). Cassava mosaic disease in South and Southeast Asia: Current status and prospects. Frontiers in Sustainable Food Systems, 7, 1086660. https://doi.org/10.3389/fsufs.2023.1086660

Hohenfeld, C. S., de Oliveira, S. A. S., Ferreira, C. F., Mello, V. H., Margarido, G. R. A., Passos, A. R., & de Oliveira, E. J. (2024). Comparative analysis of infected cassava root transcriptomics reveals candidate genes for root rot disease resistance. Scientific Reports, 14, 10587. https://doi.org/10.1038/s41598-024-60847-4

Hope, T. M. H., Price, C. J., Halai, A., Salvi, C., Crinion, J., Keijsers, M., Sperber, C., & Bowman, H. (2024). Estimating the construct validity of Principal Components Analysis. arXiv, arXiv:2401.12905. https://doi.org/10.48550/arXiv.2401.12905

Hurwitz, R. M., & Hahn, G. (2023). Penalized Principal Component Analysis using Nesterov Smoothing. ArXiv, arXiv:2309.13838v1. https://doi.org/10.48550/arXiv.2309.13838

Johnstone, I. M., & Lu, A. Y. (2009). On Consistency and Sparsity for Principal Components Analysis in High Dimensions. Journal of the American Statistical Association, 104(486), 682-693. https://doi.org/10.1198/jasa.2009.0121

Jolliffe, I. (2011). Principal Component Analysis. In M. Lovric (Ed.), International Encyclopedia of Statistical Science (pp. 1094-1096) Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-642-04898-2_455

Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 374(2065), 20150202. https://doi.org/10.1098/rsta.2015.0202

Kim, K., Kim, J., & Kennedy, E. H. (2024). Causal K-Means Clustering. arXiv, arXiv:2405.03083. https://doi.org/10.48550/arXiv.2405.03083

Laizer, H. C., Chacha, M. N., & Ndakidemi, P. A. (2019). Farmers’ Knowledge, Perceptions and Practices in Managing Weeds and Insect Pests of Common Bean in Northern Tanzania. Sustainability, 11(15), 4076. https://doi.org/10.3390/su11154076

Lee, J., Cho, H., Yun, S.-Y., & Yun, C. (2023). Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint. arXiv, arXiv:2310.18593. https://doi.org/10.48550/arXiv.2310.18593

Lee, S. (2011). Drawbacks of Principal component analysis. arXiv, arXiv:1005.1770. https://doi.org/10.48550/arXiv.1005.1770

Legg, J. (2008). African cassava mosaic disease. In F. Claude (Eds.), Encyclopedia of virology (pp. 30-36) Oxford: Elsevier. https://doi.org/10.1016/b978-012374410-4.00693-2

Leiva, A. M., Pardo, J. M., Arinaitwe, W., Newby, J., Vongphachanh, P., Chittarath, K., Oeurn, S., Hang, L. T., Gil-Ordóñez, A., Rodriguez, R., & Cuellar, W. J. (2023). Ceratobasidium sp. Is associated with cassava witches’ broom disease, a re-emerging threat to cassava cultivation in Southeast Asia. Scientific Reports, 13, 22500. https://doi.org/10.1038/s41598-023-49735-5

Leroux, A., Crainiceanu, C., & Wrobel, J. (2023). Fast Generalized Functional Principal Components Analysis. arXiv, arXiv:2305.02389. https://doi.org/10.48550/arXiv.2305.02389

Li, B. (2018). A Principal Component Analysis Approach to Noise Removal for Speech Denoising. 2018 International Conference on Virtual Reality and Intelligent Systems (pp. 429-432). IEEE. https://doi.org/10.1109/ICVRIS.2018.00111

Ling-Qun, W., Bing-Bing, L., Jun, L., Bin, X., Qi, W., Yu-Qi, C., & Kai-Guang, Z. (2015). Noise Removal Based on Filtered Principal Component Reconstruction. Chinese Journal of Geophysics, 58(5), 589-598. https://doi.org/10.1002/cjg2.20197

Maćkiewicz, A., & Ratajczak, W. (1993). Principal components analysis (PCA). Computers & Geosciences, 19(3), 303-342. https://doi.org/10.1016/0098-3004(93)90090-R

Makambila, C. (1994). The fungal diseases of cassava in the republic of Congo, central Africa. African Crop Science Journal, 2(4), 4.

Marzban, C., Yurtsever, U., & Richman, M. (2024). Principal Component Analysis for Equation Discovery. arXiv, arXiv:2401.04797. https://doi.org/10.48550/arXiv.2401.04797

McCallum, E. J., Anjanappa, R. B., & Gruissem, W. (2017a). Tackling agriculturally relevant diseases in the staple crop cassava (Manihot esculenta). Current Opinion in Plant Biology, 38, 50-58. https://doi.org/10.1016/j.pbi.2017.04.008

Miao, S., Zheng, L., Liu, J., & Jin, H. (2023). K-means Clustering Based Feature Consistency Alignment for Label-free Model Evaluation. arXiv, arXiv:2304.09758. https://doi.org/10.48550/arXiv.2304.09758

Milne, A. E., Bell, J. R., Hutchison, W. D., van den Bosch, F., Mitchell, P. D., Crowder, D., Parnell, S., & Whitmore, A. P. (2015). The Effect of Farmers’ Decisions on Pest Control with Bt Crops: A Billion Dollar Game of Strategy. PLoS Computational Biology, 11(12), e1004483. https://doi.org/10.1371/journal.pcbi.1004483

Mishra, D., Dash, R., Rath, A. K., & Acharya, M. (2011). Feature selection in gene expression data using principal component analysis and rough set theory. Advances in Experimental Medicine and Biology, 696, 91-100. https://doi.org/10.1007/978-1-4419-7046-6_10

Miyittah, M. K., Kosivi, R. K., Tulashie, S. K., Addi, M. N., & Tawiah, J. Y. (2022). The need for alternative pest management methods to mitigate risks among cocoa farmers in the Volta region, Ghana. Heliyon, 8(12), e12591. https://doi.org/10.1016/j.heliyon.2022.e12591

Mohammadi, S. O., Kalhor, A., & Bodaghi, H. (2022). K-Splits: Improved K-Means Clustering Algorithm to Automatically Detect the Number of Clusters. In A. P. Pandian, X. Fernando & W. Haoxiang (Eds.), Computer Networks, Big Data and IoT (Vol. 117, pp. 197-213) Singapore: Springer. https://doi.org/10.1007/978-981-19-0898-9_15

Mohidin, S. R. N. S. P., Moshawih, S., Hermansyah, A., Asmuni, M. I., Shafqat, N., & Ming, L. C. (2023). Cassava (Manihot esculenta Crantz): A Systematic Review for the Pharmacological Activities, Traditional Uses, Nutritional Values, and Phytochemistry. Journal of Evidence-Based Integrative Medicine, 2023, 28. https://doi.org/10.1177/2515690X231206227

Morgan, N. K., & Choct, M. (2016). Cassava: Nutrient composition and nutritive value in poultry diets. Animal Nutrition, 2(4), 253-261. https://doi.org/10.1016/j.aninu.2016.08.010

Mussabayev, R., Mladenovic, N., Jarboui, B., & Mussabayev, R. (2023). How to Use K-means for Big Data Clustering? Pattern Recognition, 137, 109269. https://doi.org/10.1016/j.patcog.2022.109269

Mustarichie, R., Sulistyaningsih, S., & Runadi, D. (2020). Antibacterial Activity Test of Extracts and Fractions of Cassava Leaves (Manihot esculenta Crantz) against Clinical Isolates of Staphylococcus epidermidis and Propionibacterium acnes Causing Acne. International Journal of Microbiology, 2020, 1975904. https://doi.org/10.1155/2020/1975904

Nakatumba-Nabende, J., Akera, B., Tusubira, J. F., Nsumba, S., & Mwebaze, E. (2020). A dataset of necrotized cassava root cross-section images. Data in Brief, 32, 106170. https://doi.org/10.1016/j.dib.2020.106170

Ndunguru, J., De León, L., Doyle, C. D., Sseruwagi, P., Plata, G., Legg, J. P., Thompson, G., Tohme, J., Aveling, T., Ascencio-Ibáñez, J. T., & Hanley-Bowdoin, L. (2016). Two Novel DNAs That Enhance Symptoms and Overcome CMD2 Resistance to Cassava Mosaic Disease. Journal of Virology, 90(8), 4160-4173. https://doi.org/10.1128/jvi.02834-15

Niño-Jimenez, D.-P., López-López, K., & Cuervo-Ibáñez, M. (2024). Quantitative detection of cassava common mosaic virus for health certification of cassava (Manihot esculenta Crantz) germplasm using qPCR analysis. Heliyon, 10(6), e27604. https://doi.org/10.1016/j.heliyon.2024.e27604

Okike, I., Wigboldus, S., Samireddipalle, A., Naziri, D., Adesehinwa, A. O. K., Adejoh, V. A., Amole, T., Bordoloi, S., & Kulakow, P. (2022). Turning Waste to Wealth: Harnessing the Potential of Cassava Peels for Nutritious Animal Feed. In G. Thiele, M. Friedmann, H. Campos, V. Polar, & J. W. Bentley (Eds.), Root, Tuber and Banana Food System Innovations: Value Creation for Inclusive Outcomes (pp. 173-206) Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-030-92022-7_6

Onyeka, T. J., Dixon, A. G. O., & Ekpo, E. J. A. (2005). Identification of levels of resistance to cassava root rot disease (Botryodiplodia theobromae) in African landraces and improved germplasm using in vitro inoculation method. Euphytica, 145(3), 281-288. https://doi.org/10.1007/s10681-005-1646-8

Otim-Nape, G. W., & Thresh, J. M. (1998). The current pandemic of cassava mosaic virus disease in Uganda. In D. G. Jones (Eds.), The Epidemiology of Plant Diseases (pp. 423-443) Netherlands: Springer. https://doi.org/10.1007/978-94-017-3302-1_21

Owomugisha, G., Nakatumba-Nabende, J., Dhikusooka, J. J., Taravera, E., Nuwamanya, E., & Mwebaze, E. (2023). A labeled spectral dataset with cassava disease occurrences using virus titre determination protocol. Data in Brief, 49, 109387. https://doi.org/10.1016/j.dib.2023.109387

Pardo, J. M., Chittarath, K., Vongphachanh, P., Hang, L. T., Oeurn, S., Arinaitwe, W., Rodriguez, R., Sophearith, S., Malik, A. I., & Cuellar, W. J. (2023). Cassava Witches’ Broom Disease in Southeast Asia: A Review of Its Distribution and Associated Symptoms. Plants, 12(11), 2217. https://doi.org/10.3390/plants12112217

Pérez, D., Duputié, A., Vernière, C., Szurek, B., & Caillon, S. (2022). Biocultural Drivers Responsible for the Occurrence of a Cassava Bacterial Pathogen in Small-Scale Farms of Colombian Caribbean. Frontiers in Ecology and Evolution, 10, 841915. https://doi.org/10.3389/fevo.2022.841915

Pham, C. V., & Tran, H. T. (2021). Cunninghamella elegans causing cassava root rot in Vietnam. Australasian Plant Disease Notes, 16, 14. https://doi.org/10.1007/s13314-021-00427-x

Phung, Q. A., & Dao, N. (2024). Farmers’ perceptions of sustainable agriculture in the Red River Delta, Vietnam. Heliyon, 10(7), e28576. https://doi.org/10.1016/j.heliyon.2024.e28576

Poggiali, A., Berti, A., Bernasconi, A., Del Corso, G. M., & Guidotti, R. (2024). Quantum Clustering with k-Means: A Hybrid Approach. Theoretical Computer Science, 992, 114466. https://doi.org/10.1016/j.tcs.2024.114466

Rahmat, F., Zulkafli, Z., Ishak, A. J., Abdul Rahman, R. Z., Stercke, S. D., Buytaert, W., Tahir, W., Ab Rahman, J., Ibrahim, S., & Ismail, M. (2024). Supervised feature selection using principal component analysis. Knowledge and Information Systems, 66, 1955-1995. https://doi.org/10.1007/s10115-023-01993-5

Razifar, P., Muhammed, H. H., Engbrant, F., Svensson, P.-E., Olsson, J., Bengtsson, E., Långström, B., & Bergström, M. (2009). Performance of Principal Component Analysis and Independent Component Analysis with Respect to Signal Extraction from Noisy Positron Emission Tomography Data—A Study on Computer Simulated Images. The Open Neuroimaging Journal, 3, 1-16. https://doi.org/10.2174/1874440000903010001

Rey, C., & Vanderschuren, H. (2017). Cassava Mosaic and Brown Streak Diseases: Current Perspectives and Beyond. Annual Review of Virology, 4, 429-452. https://doi.org/10.1146/annurev-virology-101416-041913

Sangpueak, R., Duchanee, S., Saengchan, C., Papathoti, N. K., Hoang, N. H., Thanh, T. L., Phansak, P., Buensanteai, N., Sangpueak, R., Duchanee, S., Saengchan, C., Papathoti, N. K., Hoang, N. H., Thanh, T. L., Phansak, P., & Buensanteai, N. (2023). Identification of cassava black stem and root rot agents in Thailand. Chilean Journal of Agricultural Research, 83(1), 70-82. https://doi.org/10.4067/S0718-58392023000100070

Schubert, E. (2023). Stop using the elbow criterion for k-means and how to choose the number of clusters instead. ACM SIGKDD Explorations Newsletter, 25(1), 36-42. https://doi.org/10.1145/3606274.3606278

Shlens, J. (2014). A Tutorial on Principal Component Analysis. arXiv, arXiv:1404.1100 https://doi.org/10.48550/arXiv.1404.1100

Song, F., Guo, Z., & Mei, D. (2010a). Feature Selection Using Principal Component Analysis. Engineering Design and Manufacturing Informatization 2010 International Conference on System Science, 1, 27-30. https://doi.org/10.1109/ICSEM.2010.14

Sedano, J. C. S., Moreno, R. E. M., Mathew, B., Léon, J., Gómez Cano, F. A., Ballvora, A., & López Carrascal, C. E. (2017). Major Novel QTL for Resistance to Cassava Bacterial Blight Identified through a Multi-Environmental Analysis. Frontiers in Plant Science, 8, 1169. https://doi.org/10.3389/fpls.2017.01169

Soto-Quiros, P., & Torokhti, A. (2021). Extended Principal Component Analysis. arXiv, arXiv:2111.03040. https://doi.org/10.48550/arXiv.2111.03040

Statheropoulos, M., Pappa, A., Karamertzanis, P., & Meuzelaar, H. L. C. (1999). Noise reduction of fast, repetitive GC/MS measurements using principal component analysis (PCA). Analytica Chimica Acta, 401(1), 35-43. https://doi.org/10.1016/S0003-2670(99)00494-8

Suzen, N., Gorban, A., Levesley, J., & Mirkes, E. (2020). Principal Components of the Meaning. arXiv, arXiv:2009.08859. https://doi.org/10.48550/arXiv.2009.08859

Szyniszewska, A. M. (2020). CassavaMap, a fine-resolution disaggregation of cassava production and harvested area in Africa in 2014. Scientific Data, 7(1), 159. https://doi.org/10.1038/s41597-020-0501-z

Tang, T. M., & Allen, G. I. (2021). Integrated Principal Components Analysis. arXiv, arXiv:1810.00832. https://doi.org/10.48550/arXiv.1810.00832

Taramuel-Taramuel, J. P., Montoya-Restrepo, I. A., & Barrios, D. (2023). Drivers linking farmers’ decision-making with farm performance: A systematic review and future research agenda. Heliyon, 9(10), e20820. https://doi.org/10.1016/j.heliyon.2023.e20820

Teixeira, J. H. dos S., Guimarães, M. A. S., Cardoso, S. C., Brito, A. dos S., Diniz, R. P., de Oliveira, E. J., & de Oliveira, S. A. S. (2021). Evaluation of resistance to bacterial blight in Brazilian cassava germoplasm and disease-yield relationships. Tropical Plant Pathology, 46, 324-335. https://doi.org/10.1007/s40858-021-00419-3

Thepbandit, W., Papathoti, N. K., Hoang, N. H., Siriwong, S., Sangpueak, R., Saengchan, C., Laemchiab, K., Kiddeejing, D., Tonpho, K., & Buensanteai, K. (2024b). Bio-synthesis and characterization of silver nanoparticles from Trichoderma species against cassava root rot disease. Scientific Reports, 14(1), 12535. https://doi.org/10.1038/s41598-024-60903-z

Tize, I., Fotso, A. K., Nukenine, E. N., Masso, C., Ngome, F. A., Suh, C., Lendzemo, V. W., Nchoutnji, I., Manga, G., Parkes, E., Kulakow, P., Kouebou, C., Fiaboe, K. K. M., & Hanna, R. (2021). New cassava germplasm for food and nutritional security in Central Africa. Scientific Reports, 11(1), 7394. https://doi.org/10.1038/s41598-021-86958-w

Toure, H. M. A. C., Ehui, K. J. N., Abo, K., & Kone, D. (2020). Four years assessment of Cassava Bacterial Blight expression according to weather conditions in Côte d’Ivoire. SN Applied Sciences, 2(7), 1301. https://doi.org/10.1007/s42452-020-3135-z

Uke, A., Tokunaga, H., Utsumi, Y., Vu, N. A., Nhan, P. T., Srean, P., Hy, N. H., Ham, L. H., Lopez-Lavalle, L. A. B., Ishitani, M., Hung, N., Tuan, L. N., Van Hong, N., Huy, N. Q., Hoat, T. X., Takasu, K., Seki, M., & Ugaki, M. (2022b). Cassava mosaic disease and its management in Southeast Asia. Plant Molecular Biology, 109(3), 301-311. https://doi.org/10.1007/s11103-021-01168-2

Van den Berg, H., & Jiggins, J. (2007). Investing in Farmers—The Impacts of Farmer Field Schools in Relation to Integrated Pest Management. World Development, 35(4), 663-686. https://doi.org/10.1016/j.worlddev.2006.05.004

van Elst, H. (2021). Tutorial on principal component analysis, with applications in R. https://doi.org/10.13140/RG.2.2.20075.16168/2

Vardakas, G., & Likas, A. (2023). Global $k$-means$++$: An effective relaxation of the global $k$-means clustering algorithm. arXiv, arXiv:2211.12271. https://doi.org/10.48550/arXiv.2211.12271

Veley, K. M., Elliott, K., Jensen, G., Zhong, Z., Feng, S., Yoder, M., Gilbert, K. B., Berry, J. C., Lin, Z.-J. D., Ghoshal, B., Gallego-Bartolomé, J., Norton, J., Motomura-Wages, S., Carrington, J. C., Jacobsen, S. E., & Bart, R. S. (2023). Improving cassava bacterial blight resistance by editing the epigenome. Nature Communications, 14(1), 85. https://doi.org/10.1038/s41467-022-35675-7

Wang, C., Chen, Y., Chen, S., Min, Y., Tang, Y., Ma, X., Li, H., Li, J., & Liu, Z. (2023a). Spraying chitosan on cassava roots reduces postharvest deterioration by promoting wound healing and inducing disease resistance. Carbohydrate Polymers, 318, 121133. https://doi.org/10.1016/j.carbpol.2023.121133

Wang, G., Lou, M., & Pananjady, A. (2023b). Do algorithms and barriers for sparse principal component analysis extend to other structured settings? arXiv, arXiv:2307.13535. https://doi.org/10.48550/arXiv.2307.13535

Wang, S. G. W., Patilea, V., & Klutchnikoff, N. (2024). Adaptive functional principal components analysis. arXiv, arXiv:2306.16091. https://doi.org/10.48550/arXiv.2306.16091

Wydra, K., & Verdier, V. (2002). Occurrence of cassava diseases in relation to environmental, agronomic and plant characteristics. Agriculture, Ecosystems & Environment, 93(1-3), 211-226. https://doi.org/10.1016/S0167-8809(01)00349-8

Yfantis, V., Wagner, A., & Ruskowski, M. (2023). Federated K-Means Clustering via Dual Decomposition-based Distributed Optimization. arXiv, arXiv:2307.13267. https://doi.org/10.48550/arXiv.2307.13267

Yoodee, S., Kobayashi, Y., Songnuan, W., Boonchird, C., Thitamadee, S., Kobayashi, I., & Narangajavana, J. (2018). Phytohormone priming elevates the accumulation of defense-related gene transcripts and enhances bacterial blight disease resistance in cassava. Plant Physiology and Biochemistry, 122, 65-77. https://doi.org/10.1016/j.plaphy.2017.11.016

Zárate-Chaves, C. A., Gómez de la Cruz, D., Verdier, V., López, C. E., Bernal, A., & Szurek, B. (2021). Cassava diseases caused by Xanthomonas phaseoli pv. Manihotis and Xanthomonas cassavae. Molecular Plant Pathology, 22(12), 1520-1537. https://doi.org/10.1111/mpp.13094

Zhang, J. (2019). Machine Learning With Feature Selection Using Principal Component Analysis for Malware Detection: A Case Study. arXiv, arXiv:1902.03639. https://doi.org/10.48550/arXiv.1902.03639

Zhu, B., Bedeer, E., Nguyen, H. H., Barton, R., & Henry, J. (2021). Improved Soft-k-Means Clustering Algorithm for Balancing Energy Consumption in Wireless Sensor Networks. IEEE Internet of Things Journal, 8(6), 4868-4881. https://doi.org/10.1109/JIOT.2020.3031272

Zhuang, Y., Chen, X., Yang, Y., & Zhang, R. Y. (2024). Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming. arXiv, arXiv:2305.18436. https://doi.org/10.48550/arXiv.2305.18436

Published

02-07-2024

How to Cite

Claudette, D. V., & Roger, T. I. (2024). Farmers’ knowledge and perceptions of Cassava (Manihot esculenta Crantz) diseases and management. Journal of Scientific Agriculture, 8, 15–30. https://doi.org/10.25081/jsa.2024.v8.9000

Issue

Section

Articles