Improvement of a fertilization system for corn through control of the nutritional status of plants
Call Number: AIT Thesis no.AE-92-40 Material type:
SeriesSeries: Asian Institute of Technology. Thesis ; no. AE-92-40Publication details: Bangkok : Asian Institute of Technology, 1992Description: 63 leavesSubject(s): Online resources: Dissertation note: Thesis (M.Sc.) - Asian Institute of Technology, 1992 Summary: A field experiment on corn crop was conducted on acid-sulphate soil at Agricultural Systems farm at Asian Institute of Technology, Bangkok from January - May 1882 . It focused on (i) improving the fertilization system mod e l for corn by providing additional data on yield response to different N and P application rates, (ii) determining the synergistic and antagonistic effects of N, P, and K through plant analysis. The experiment complete block design N and P resulting in and P were Nl , NZ, N3 P3 (50 kg, 125 kg and was laid- out in a factorial randomized with three replications at three levels of 8 treatment combinations. The levels of N (50 kg, 150 kg and 250 kg N/ha) and Pl, P2, 200 kg P/ha) respectively . The above-ground plant parts were N, P, and K six. times during the entire P concentration was corrected at a fixed of 5 gm/plant. This established the developing the preliminary diagnosis and A synergistic effect was found among N, u se of N a nd P resulted in antagonism. sampled and analysed for growth period. The N and dry matter weight level basis for testing and yield prognosis models. P, and K but imbalanced Results from this experiment we re in agreement with the results of Amit (1890), Sumitrai (1889), Krishda (1988) , Labhsetwar (1878) and Lawongsa (1879). However, new areas were revealed in the correction models from the n ew experimental results. Yield prognosis models for N and P were broadened at the yield level of 7.60 ton/ha, which was the highest among all previous experiments conducted in connection with t his fertilization system model. Predicted yield based on diagnosis and yield prognosis models was very near to the obtained yield , which further substantiated the reliability and accuracy of the models.
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A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science, School of Environment, Resources and Development
Thesis (M.Sc.) - Asian Institute of Technology, 1992
A field experiment on corn crop was conducted on acid-sulphate soil at Agricultural Systems farm at Asian Institute of Technology, Bangkok from January - May 1882 . It focused on (i) improving the fertilization system mod e l for corn by providing additional data on yield response to different N and P application rates, (ii) determining the synergistic and antagonistic effects of N, P, and K through plant analysis. The experiment complete block design N and P resulting in and P were Nl , NZ, N3 P3 (50 kg, 125 kg and was laid- out in a factorial randomized with three replications at three levels of 8 treatment combinations. The levels of N (50 kg, 150 kg and 250 kg N/ha) and Pl, P2, 200 kg P/ha) respectively . The above-ground plant parts were N, P, and K six. times during the entire P concentration was corrected at a fixed of 5 gm/plant. This established the developing the preliminary diagnosis and A synergistic effect was found among N, u se of N a nd P resulted in antagonism. sampled and analysed for growth period. The N and dry matter weight level basis for testing and yield prognosis models. P, and K but imbalanced Results from this experiment we re in agreement with the results of Amit (1890), Sumitrai (1889), Krishda (1988) , Labhsetwar (1878) and Lawongsa (1879). However, new areas were revealed in the correction models from the n ew experimental results. Yield prognosis models for N and P were broadened at the yield level of 7.60 ton/ha, which was the highest among all previous experiments conducted in connection with t his fertilization system model. Predicted yield based on diagnosis and yield prognosis models was very near to the obtained yield , which further substantiated the reliability and accuracy of the models.
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