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Research Articles

Enhancing agriculture production through smart assessment of soil nutrients

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Pages 392-409 | Received 20 Sep 2023, Accepted 10 May 2024, Published online: 21 May 2024

References

  • Alex, S. A., and A. Kanavalli. 2019. “Intelligent Computational Techniques for Crops Yield Prediction and Fertilizer Management Over Big Data Environment.” International Journal of Innovative Technology and Exploring Engineering 8 (12): 3521–3526. https://doi.org/10.35940/ijitee.L2622.1081219.
  • Bhattacharyya, P., H. Pathak, S. Pal, P. Bhattacharyya, H. Pathak, and S. Pal. 2020. “Crop Management for Climate-Smart Agriculture.” Climate Smart Agriculture: 85–111. https://doi.org/10.1007/978-981-15-9132-7_7.
  • Breiman, L. 1996. “Stacked Regressions.” Machine Learning 24:49–64. https://doi.org/10.1007/BF00117832.
  • Chiemeka, I. U. 2010. “Soil Temperature Profile at Uturu, Nigeria.” The Pacific Journal of Science and Technology 11 (1): 478–482.
  • Chukhray, N., N. Shakhovska, O. Mrykhina, L. Lisovska, and I. Izonin. 2022. “Stacking Machine Learning Model for the Assessment of R&D product’s Readiness and Method for Its Cost Estimation.” Mathematics 10 (9): 1466. https://doi.org/10.3390/math10091466.
  • Durai, S. K. S., and M. D. Shamili. 2022. “Smart Farming Using Machine Learning and Deep Learning Techniques.” Decision Analytics Journal 3:100041. https://doi.org/10.1016/j.dajour.2022.100041.
  • Elavarasan, D., D. R. Vincent, V. Sharma, A. Y. Zomaya, and K. Srinivasan. 2018. “Forecasting Yield by Integrating Agrarian Factors and Machine Learning Models: A Survey.” Computers and Electronics in Agriculture 155:257–282. https://doi.org/10.1016/j.compag.2018.10.024.
  • Elias, E. A., R. Cichota, H. H. Torriani, and Q. De Jong Van Lier. 2004. “Analytical Soil–Temperature Model: Correction for Temporal Variation of Daily Amplitude.” Soil Science Society of America 68 (3): 784–788. https://doi.org/10.2136/sssaj2004.7840.
  • Gaikwad, S. V., and S. G. Galande. 2015. “Measurement of NPK, Temperature, Moisture, Humidity Using WSN.” International Journal of Engineering Research and Applications 5 (8): 84–89.
  • Ganapathi, S., S. Bharathi, and K. Jayalalitha. 2018. “Effect of Nutrient Management and Moisture Conservation Practices on Plant NPK Content (%), Plant Uptake at Harvest and Post-Harvest Soil Fertility Under Rainfed Bt Cotton.” International Journal of Current Microbiology and Applied Sciences 7 (10): 2832–2838. https://www.researchgate.net/publication/337137336.
  • Géron, A. 2019. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. O’Reilly Media, Inc. ISBN: 9781492032649. http://oreilly.com/catalog/errata.csp?isbn=9781492032649.
  • Liew, Y. W., S. K. Arumugasamy, and A. Selvarajoo. 2022. “Potential of Biochar As Soil Amendment: Prediction of Elemental Ratios from Pyrolysis of Agriculture Biomass Using Artificial Neural Network.” Water, Air, & Soil Pollution 233 (2): 54. https://doi.org/10.1007/s11270-022-05510-2.
  • Lohchab, V., M. Kumar, G. Suryan, V. Gautam, and R. K. Das. 2018. “A Review of IoT Based Smart Farm Monitoring.” Second International IEEE Conference on Inventive Communication and Computational Technologies, 1620–1625. https://doi.org/10.1109/ICICCT.2018.8473337.
  • Manoj Kumar, D. P., N. Malyadri, and M. S. Srikanth. 2021. “A Machine Learning Model for Crop and Fertilizer Recommendation.” Natural Volatiles and Essential Oils Journal 8 (5): 10531–10539.
  • Mucherino, A., P. Papajorgji, and P. M. Pardalos. 2009. “A Survey of Data Mining Techniques Applied to Agriculture.” Operational Research: An International Journal 9:121–140. https://doi.org/10.1007/s12351-009-0054-6.
  • Navidi, M. N., and J. Seyedmohammadi. 2022. “Mapping and Spatial Analysis of Soil Chemical Effective Properties to Manage Precise Nutrition and Environment Protection.” International Journal of Environmental Analytical Chemistry 102 (8): 1948–1961. https://doi.org/10.1080/03067319.2020.1746775.
  • Navidi, M. N., J. Seyedmohammadi, and S. A. Seyed Jalali. 2022. “Predicting Soil Water Content Using Support Vector Machines Improved by Meta-Heuristic Algorithms and Remotely Sensed Data.” Geomechanics and Geoengineering 17 (3): 712–726. https://doi.org/10.1080/17486025.2020.1864032.
  • Neenu, S., and K. Ramesh. 2020. “Weather-Micronutrient Interactions in Soil and Plants–A Critical Review.” Chemical Science Review and Letters 9 (33): 205–219. https://doi.org/10.37273/chesci.CS20510136.
  • Onwuka, B., and B. Mang. 2018. “Effects of Soil Temperature on Some Soil Properties and Plant Growth.” Advances in Plants & Agriculture Research 8 (1): 34–37. https://doi.org/10.15406/apar.2018.08.00288.
  • Prakash, S., A. Sharma, and S. S. Sahu. 2018. “Soil Moisture Prediction Using Machine Learning.” Second International IEEE Conference on Inventive Communication and Computational Technologies, 1–6. https://doi.org/10.1109/ICICCT.2018.8473260.
  • Rao, A., A. Gowda, and R. Beham. 2016. “Machine Learning in Soil Classification and Crop Detection.” International Journal for Scientific Research and Development 4 (1): 792–794. https://www.researchgate.net/publication/325107675.
  • Rust, N. A., E. N. Ptak, M. Graversgaard, S. Iversen, M. S. Reed, J. R. de Vries, and T. Dalgaard. 2020. “Social Capital Factors Affecting Uptake of Sustainable Soil Management Practices: A Literature Review.” Emerald Open Research 1 (10). https://doi.org/10.1108/EOR-10-2023-0002.
  • Seyedmohammadi, J., M. N. Navidi, A. Zeinadini, and R. W. McDowell. 2024. “Random Forest, an Efficient Smart Technique for Analyzing the Influence of Soil Properties on Pistachio Yield.” Environment, Development and Sustainability 26 (1): 2615–2636. https://doi.org/10.1007/s10668-023-03926-2.
  • Seyedmohammadi, J., A. Zeinadini, M. N. Navidi, and R. W. McDowell. 2023. “A New Robust Hybrid Model Based on Support Vector Machine and Firefly Meta-Heuristic Algorithm to Predict Pistachio Yields and Select Effective Soil Variables.” Ecological Informatics 74:102002. https://doi.org/10.1016/j.ecoinf.2023.102002.
  • Sinha, B. B., and R. Dhanalakshmi. 2022. “Recent Advancements and Challenges of Internet of Things in Smart Agriculture: A Survey.” Future Generation Computer Systems 126:169–184. https://doi.org/10.1016/j.future.2021.08.006.
  • Suchithra, M. S., and M. L. Pai. 2020. “Improving the Prediction Accuracy of Soil Nutrient Classification by Optimizing Extreme Learning Machine Parameters.” Information Processing in Agriculture 7 (1): 72–82. https://doi.org/10.1016/j.inpa.2019.05.003.
  • Tatli, S., E. Mirzaee-Ghaleh, H. Rabbani, H. Karami, and A. D. Wilson. 2022. “Prediction of Residual NPK Levels in Crop Fruits by Electronic-Nose VOC Analysis Following Application of Multiple Fertilizer Rates.” Applied Sciences 12 (21): 11263. https://doi.org/10.3390/app122111263.
  • Thorat, T., B. K. Patle, and S. K. Kashyap. 2023. “Intelligent Insecticide and Fertilizer Recommendation System Based on TPF-CNN for Smart Farming.” Smart Agricultural Technology 3 (100114): 100114. https://doi.org/10.1016/J.ATECH.2022.100114.
  • Tkaczyk, P., A. Mocek-Płóciniak, M. Skowrońska, W. Bednarek, S. Kuśmierz, and E. Zawierucha. 2020. “The Mineral Fertilizer-Dependent Chemical Parameters of Soil Acidification Under Field Conditions.” Sustainability 12 (17): 7165. https://doi.org/10.3390/su12177165.
  • Yang, G., R. Liu, P. Ma, H. Chen, R. Zhang, X. Wang, Y. Li, and Y. Hu. 2022. “Effects of Nitrogen and Phosphorus Regulation on Plant Type, Population Ecology and Sheath Blight of Hybrid Rice.” Plants 11 (17): 2306. https://doi.org/10.3390/plants11172306.
  • Yao, Y., Q. Dai, R. Gao, Y. Gan, X. Yi, and V. G. Aschonitis. 2021. “Effects of Rainfall Intensity on Runoff and Nutrient Loss of Gently Sloping Farmland in a Karst Area of SW China.” Public Library of Science ONE 16 (3): e0246505. https://doi.org/10.1371/journal.pone.0246505.
  • Yost, J. L., and A. E. Hartemink. 2020. “How Deep Is the Soil Studied–An Analysis of Four Soil Science Journals.” Plant and Soil 452:5–18. https://doi.org/10.1007/s11104-020-04550-z.

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