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Effects of Combined Application of Nitrogen and Phosphorus Fertilizers on Photosynthetic Characteristics of Silage Corn, Laying the Foundation of Agricultural Information

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIOT 2020)

Abstract

At this stage, it is undeniable that smart agriculture has become an inevitable development direction of agricultural production. The most basic part of smart agriculture is the collection and arrangement of big data. This paper discusses the effects of combined application of nitrogen and phosphorus fertilizers on photosynthetic characteristics and dry matter yield of silage corn, and uses silage corn varieties “Jinzhu 100” to provide theoretical support for big data in smart agriculture. In this experiment, 25 kinds of mixed treatments were set up, and the relevant indexes of corn were measured. Among the 25 treatments, N4P4 (nitrogen application 240.00 kg/hm2, phosphorus application P2O5 112.50 kg/hm2) and N4P3 (nitrogen application 240.00 kg/hm2, phosphorus application P2O5 75.00 kg/hm2) applied to “Jinzhu 100” plant height, leaf nitrogen and chlorophyll accumulation promoted the effects most significantly. N4P3 (nitrogen application 240.00 kg/hm2, phosphorus application P2O5 575.00 kg/hm2) had the most significant effect on increasing the dry matter weight of “Jinzhu 100”. Among the 25 treatments, N4P4 treatment had the best photosynthetic physiology and growth promotion effect of “Jinzhu 100”.

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Acknowledgements

This work was supported by Tianjin Seed Industry Science and Technology Major Project 16ZXZYNC00150.

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Correspondence to Chunyang Xiang .

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Shi, X. et al. (2021). Effects of Combined Application of Nitrogen and Phosphorus Fertilizers on Photosynthetic Characteristics of Silage Corn, Laying the Foundation of Agricultural Information. In: MacIntyre, J., Zhao, J., Ma, X. (eds) The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. SPIOT 2020. Advances in Intelligent Systems and Computing, vol 1282. Springer, Cham. https://doi.org/10.1007/978-3-030-62743-0_79

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