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Development of an algorithm for optimizing nitrogen fertilization in wheat using GreenSeeker proximal optical sensor

Published online by Cambridge University Press:  14 October 2020

Ali M. Ali*
Affiliation:
Department of Soil Fertility and Microbiology, Desert Research Center, 1 Mathaf El-Matarya St., P.O. Box 11753 Cairo, Egypt
*
*Corresponding author. Email: alimohamed1982@gmail.com

Abstract

Proximal plant sensing with active canopy sensors offers a leap in the non-destructive assessment of crop agronomic information. For managing fertilizer nitrogen (N), sensor readings must be translated using functional models or algorithms to fertilizer amounts. Six field experiments were conducted in three wheat seasons in the West Nile Delta in Egypt to develop and validate an algorithm based on GreenSeeker canopy reflectance sensor for field-specific fertilizer N management in wheat, which takes into account both spatial and temporal variability of N during the crop growth season. The proposed algorithm is based on the prediction of total N uptake and response index of N uptake determined from normalized difference vegetation index measured by the sensor from plots differing in yield potential as established by applying a range of fertilizer N levels in the four experiments conducted in the first two wheat seasons. The treatments in the two experiments conducted in the third wheat season were designed to define appropriate fertilizer N management prior to applying a sensor-based dose at Feekes 6 stage (jointing stage). The application of 40 and 60 kg N ha−1 at 10 and 30 days after sowing of wheat and a sensor-guided dose of N estimated by using the algorithm developed in this study resulted in yields similar to those obtained by following the general recommendation, but with an average of 66 kg N ha−1 less fertilizer N. These results were also reflected in a substantial increase in N recovery (21.9%) and agronomic (7.7 kg grain kg−1 N) efficiencies compared with the general recommendation, thereby proving the usefulness of the sensor-based algorithm in optimizing fertilizer N management in wheat.

Type
Research Article
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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References

Ali, A.M., Abou-Amer, I. and Ibrahim, S.M. (2018). Using GreenSeeker active optical sensor for optimizing maize nitrogen fertilization in calcareous soils of Egypt. Archives of Agronomy and Soil Science 64, 10831093.CrossRefGoogle Scholar
Ali, A.M., Ibrahim, S.M. and Bijay-Singh (2020). Wheat grain yield and nitrogen uptake prediction using atLeaf and GreenSeeker portable optical sensors at jointing growth stage. Information Processing Agriculture 7 (3), 375383. https://doi.org/10.1016/j.inpa.2019.09.008 CrossRefGoogle Scholar
Ali, A.M., Thind, H.S., Varinderpal-Singh and Bijay-Singh (2015). A framework for refining nitrogen management in dry direct-seeded rice using GreenSeeker™ optical sensor. Computers and Electronics in Agriculture 110, 114120.CrossRefGoogle Scholar
Bijay-Singh, and Ali, A.M. (2020). Using hand-held chlorophyll meters and canopy reflectance sensors for fertilizer nitrogen management in cereals in small farms in developing countries. Sensors 20, 1127.CrossRefGoogle ScholarPubMed
Bijay-Singh, , Sharma, R.K., Jaspreet, K., Jat, M.L., Martin, K.L., Yadvinder-Singh, , Varinderpal-Singh, , Chandna, P., Choudhary, O.P., Gupta, R.K., Thind, H.S., Jagmohan-Singh, , Uppal, H.S., Khurana, H.S., Kumar, A., Uppal, R.K., Vashistha, M., Raun, W.R. and Gupta, R. (2011). Assessment of the nitrogen management strategy using an optical sensor for irrigated wheat. Agronomy for Sustainable Development 31, 589603.CrossRefGoogle Scholar
Bijay-Singh, , Varinderpal-Singh, , Purba, J., Sharma, R.K., Jat, M.L., Yadvinder-Singh, , Thind, H.S., Gupta, R.K., Choudhary, O.P., Chandna, P., Khurana, H.S., Kumar, A., Jagmohan-Singh, , Uppal, H.S., Uppal, R.K., Vashistha, M. and Gupta, R.K. (2015). Site-specific nitrogen management in irrigated transplanted rice (Oryza sativa) using an optical sensor. Precision Agriculture 16, 455475.CrossRefGoogle Scholar
Bijay-Singh, , Varinderpal-Singh, , Yadvinder-Singh, , Thind, H.S., Kumar, A., Choudhary, O.P., Gupta, R.K. and Vashistha, M. (2017). Site-specific fertilizer nitrogen management using optical sensor in irrigated wheat in the Northwestern India. Agricultural Research 6, 159168.CrossRefGoogle Scholar
Bremner, J.T. (1965). Inorganic forms of nitrogen. Methods of Soil Analysis: Part 2 Chemical and Microbiological Properties 9, 11791237.Google Scholar
Cao, Q., Miao, Y., Feng, G., Gao, X., Liu, B., Liu, Y., Li, F., Khosla, R., Mulla, D.J. and Zhang, F. (2017). Improving nitrogen use efficiency with minimal environmental risks using an active canopy sensor in a wheat-maize cropping system. Field Crops Research 214, 365372.CrossRefGoogle Scholar
Cassman, K.G., Peng, S., Olk, D.C., Ladha, J.K., Reichardt, W., Dobermann, A. and Singh, U. (1998). Opportunities for increased nitrogen-use efficiency from improved resource management in irrigated rice systems. Field Crops Research 56, 739.CrossRefGoogle Scholar
Fox, R.H. and Walthall, C.L. (2008). Crop monitoring technologies to assess nitrogen status. Nitrogen in Agricultural Systems 49, 647674.Google Scholar
Franzen, D., Kitchen, N., Holland, K., Schepers, J. and Raun, W. (2016). Algorithms for in-season nutrient management in cereals. Agronomy Journal 108, 17751781.CrossRefGoogle Scholar
Gomez, K.A. and Gomez, A.A. (1984). Statistical Procedures for Agricultural Research. Hoboken, NJ: John Wiley & Sons.Google Scholar
Hatfield, J.L., Gitelson, A.A., Schepers, J.S. and Walthall, C.L. (2008). Application of spectral remote sensing for agronomic decisions. Agronomy Journal 100, S-117.CrossRefGoogle Scholar
Johnson, G.V. (1991). General model for predicting crop response to fertilizer. Agronomy Journal 83, 367373.CrossRefGoogle Scholar
Johnson, G.V. and Raun, W.R. (2003). Nitrogen response index as a guide to fertilizer management. Journal of Plant Nutrition 26, 249262.CrossRefGoogle Scholar
Johnson, G.V., Raun, W.R. and Mullen, R.W. (2000). Nitrogen use efficiency as influenced by crop response index. In Agronomy Abstracts. Madison, WI: ASA, CSSA, and SSSA, p. 291.Google Scholar
Kalra, Y. (1997). Handbook of Reference Methods for Plant Analysis. Boca Raton, FL: CRC Press.Google Scholar
Large, E.C. (1954). Growth stages in cereals: Illustration of the Feekes scale. Plant Pathology 3, 128129.CrossRefGoogle Scholar
Morris, K.B., Martin, K.L., Freeman, K.W., Teal, R.K., Girma, K., Arnall, D.B., Hodgen, P.J., Mosali, J., Raun, W.R. and Solie, J.B. (2006). Mid-season recovery from nitrogen stress in winter wheat. Journal of Plant Nutrition 29, 727745.CrossRefGoogle Scholar
Mullen, R.W., Freeman, K.W., Raun, W.R., Johnson, G.V., Stone, M.L. and Solie, J.B. (2003). Identifying an in-season response index and the potential to increase wheat yield with nitrogen. Agronomy Journal 95, 347351.CrossRefGoogle Scholar
Nelson, R.E. (1983). Carbonate and gypsum. Methods of Soil Analysis: Part 2 Chemical and Microbiological Properties 9, 181197.Google Scholar
Olsen, S.R. (1954). Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate (No. 939). Washington, DC: US Department of Agriculture.Google Scholar
Page, A.L., Miller, R.H. and Keeney, D.R. (1982). Methods of Soil Analysis, Part 2: Chemical and Microbiological Properties, 2nd Edn. Madison, WI: Am. Soc. Agron. Inc. Soil Sci. Soc. Am. Inc.Google Scholar
Perry, E.M., Fitzgerald, G.J., Nuttall, J.G., O’Leary, G.J., Schulthess, U. and Whitlock, A. (2012). Rapid estimation of canopy nitrogen of cereal crops at paddock scale using a canopy chlorophyll content index. Field Crops Research 134, 158164.CrossRefGoogle Scholar
Pinter, P.J. Jr, Jackson, R.D., Idso, S.B. and Reginato, R.J. (1981). Multidate spectral reflectance as predictors of yield in water stressed wheat and barley. International Journal of Remote Sensing 2, 4348.CrossRefGoogle Scholar
Pratt, P.F. (1965). Potassium. Methods of Soil Analysis: Part 2 Chemical and Microbiological Properties 9, 10221030.Google Scholar
Raun, W.R., Dhillon, J., Aula, L., Eickhoff, E., Weymeyer, G., Figueirdeo, B., Lynch, T., Omara, P., Nambi, E., Oyebiyi, F. and Fornah, A. (2019). Unpredictable nature of environment on nitrogen supply and demand. Agronomy Journal 111, 27862791.CrossRefGoogle Scholar
Raun, W.R., Solie, J.B., Johnson, G.V., Stone, M.L., Mullen, R.W., Freeman, K.W., Thomason, W.E. and Lukina, E.V. (2002). Improving nitrogen use efficiency in cereal grain production with optical sensing and variable rate application. Agronomy Journal 94, 815820.CrossRefGoogle Scholar
Rickman, R.W., Waldman, S.E. and Klepper, B. (1996). MODWht3: A development-driven wheat growth simulation. Agronomy Journal 88, 176185.CrossRefGoogle Scholar
Solie, J.B., Raun, W.R., Whitney, R.W., Stone, M.L. and Ringer, J.D. (1996). Optical sensor based field element size and sensing strategy for nitrogen application. Transactions of the ASAE 39, 19831992.CrossRefGoogle Scholar
Stanford, G. (1973). Rationale for optimum nitrogen fertilization in corn production. Journal of Environmental Quality 2, 159166.CrossRefGoogle Scholar
Stone, M.L., Solie, J.B., Raun, W.R., Whitney, R.W., Taylor, S.L. and Ringer, J.D. (1996). Use of spectral radiance for correcting in-season fertilizer nitrogen deficiencies in winter wheat. Transactions of the ASAE 39, 16231631.CrossRefGoogle Scholar
Sulochna, M., Alam, P. and Ali, M.N. (2019). Effect of precision nitrogen management on protein content in grain of wheat. International Journal of Communication Systems 7, 12621264.Google Scholar
Tucker, C.J., Holben, B.N., Elgin, J.H. Jr and McMurtrey, J.E. III (1980). Relationship of spectral data to grain yield variation. Photogrammetric Engineering and Remote Sensing 46, 657666.Google Scholar
Varinderpal-Singh, , Bijay-Singh, , Yadvinder-Singh, , Thind, H.S., Buttar, G.S., Kaur, S., Kaur, S. and Bhowmik, A. (2017). Site-specific fertilizer nitrogen management for timely sown irrigated wheat (Triticum aestivum L. and Triticum turgidum L. ssp. durum) genotypes. Nutrient Cycling in Agroecosystems 109, 116.CrossRefGoogle Scholar
Walkley, A. and Black, I.A. (1934). An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Science 37, 2938.CrossRefGoogle Scholar
Xue, L., Li, G., Qin, X., Yang, L. and Zhang, H. (2014). Topdressing nitrogen recommendation for early rice with an active sensor in south China. Precision Agriculture 15, 95110.CrossRefGoogle Scholar
Yao, Y., Miao, Y., Huang, S., Gao, L., Ma, X., Zhao, G., Jiang, R., Chen, X., Zhang, F., Yu, K. and Gnyp, M.L. (2012). Active canopy sensor-based precision N management strategy for rice. Agronomy for Sustainable Development 32, 925933.CrossRefGoogle Scholar
Zhang, J., Liu, X., Liang, Y., Cao, Q., Tian, Y., Zhu, Y., Cao, W. and Liu, X. (2019). Using a portable active sensor to monitor growth parameters and predict grain yield of winter wheat. Sensors 19, 1108.CrossRefGoogle ScholarPubMed