ACTIVE OPTICAL SENSORS TO DEVELOP NITROGEN FERTILIZER RECOMMENDATIONS FOR POTATO CROP
DOI:
https://doi.org/10.36103/ijas.v54i2.1725Keywords:
nitrogen, greenseeker, crop circle, in-season estimated yieldAbstract
This study was performed to determine whether active optical sensors could develop an algorithm for N recommendation for the potato crop (Solanum tuberosum L.). The experiment was conducted in Maine State, (USA) during the growing season of 2018-2019. Six N rates (0-280 kg ha-1) were applied on eleven locations under a randomized complete block design (RCBD), with four replications. Data of normalized difference vegetation index-(NDVI) were collected via active sensors, GreenSeeker-(GS), and Crop Circle-(CC). Sensors measurements collected at the 20th of the leaf stage were significantly associated with tuber yield, where the exponential model exhibited a better fit for the regression curve. Conventionally, 168 kg N ha-1 produced the maximum potato yield. The N rate computed based on in-season sensors reading reduced by about 12-14% from the total N rate that growers use to apply based on the conventional approach. Studying potato cultivars separately in the same soil properties can improve the algorithm accurately.
References
Ahmed, A., M. A. El-Baky., A. Ghoname., G. Riad and S. El-Abd. 2009. Potato tuber quality is affected by nitrogen form and rate. Middle Eastern Russian Journal of Plant Sciences and Biotechnology, 3, 47-52.
Ahmed, A. Z., S. Lakesh., J. Ahmed., B. Sukhwinder., B. Aaron and A. Andrei. 2020. In-season potato yield prediction with active optical sensors. Agrosystems, Geosciences and Environment, 3(3), 1-15.
Ali, A. M., H. S. Thind., S. Sharma and Y. Singh. 2015. Site-specific nitrogen management in dry direct-seeded rice using chlorophyll meter and leaf colour chart. Pedosphere, 25(1), 72-81.
Alkhafaji, A. R and N. H. Khalil. 2019. Effect Of Fertilization, Rootstocks and Growth Stimulant On Growth Of Citrus Limon L. Sapling. Iraqi Journal of Agricultural Science, 50(3), 990-1000 https://doi.org/10.36103/ijas.v50i4.743
Alva, L. 2004. Potato nitrogen management. Journal of Vegetable Crop Production, 10(1), 97-132.
Baligar, V., N. Fageria and Z. He. 2001. Nutrient use efficiency in plants. Communications in Soil Science and Plant Analysis, 32(7-8), 921-950.
Ball, D. F. 1964. Loss-on-ignition as an estimate of organic matter and organic carbon in non-calcareous soils. Journal of Soil Science, 15(1), 84-92
Basyouni, R and B. Dunn. 2013. Use of optical sensors to monitor plant nitrogen status in horticultural plants. Division of Agricultural Sciences and Natural Resources, Oklahoma State University. HLA-6719:1-4pp
Blackmer, T., J. Schepers., G. Varvel and Walter-Shea, E. 1996. Nitrogen deficiency detection using reflected shortwave radiation from irrigated corn canopies. Agronomy Journal, 88(1), 1-5.
Blackmer, T. M and J. S. Schepers. 1996. Aerial photography to detect nitrogen stress in corn. Journal of plant physiology, 148(3-4), 440-444.
Bronson, K. F., T. T. Chua., J. Booker., J. W. Keeling and R. J. Lascano. 2003. In-season nitrogen status sensing in irrigated cotton. Soil science society of America Journal, 67(5), 1439-1448.
Bu, H., L. K. Sharma., A. Denton and D. W. Franzen. 2016. Sugar beet yield and quality prediction at multiple harvest dates using active-optical sensors. Agronomy Journal, 108(1), 273-284.
Butchee, K. S., J. May and B. Arnall. 2011. Sensor-based nitrogen management reduced nitrogen and maintained yield. Crop Management, 10(1), 0-0.
Cassman, K. G., A. Dobermann and D. T. Walters. 2002. Agroecosystems, nitrogen-use efficiency, and nitrogen management. AMBIO: A Journal of the Human Environment, 31(2), 132-141.
Dilz, K. 1988. Efficiency of uptake and utilization of fertilizer nitrogen by plants. Nitrogen efficiency in agricultural soils, 1-26.
Donavon, J., P. Diane., P. Todd., K. Ted and R. Andy. 1946. Yield estimates -northern plains potato growers association-NPPGA. Retrieved from http://nppga.org/ crop_science/measurements.php
Errebhi, M., C. J. Rosen., S. C. Gupta and D. E. Birong. 1998. Potato yield response and nitrate leaching as influenced by nitrogen management. Agronomy Journal, 90(1), 10-15.
Fageria, N. 2009. The use of nutrients in crop plants. In Earth Sciences, Environment and Agriculture. pp: 448. doi:https://doi.org /10.1201/9781420075113
Felton, W. L., C. L. Alston., B. M. Haigh., P. G. Nash., G. A. Wicks and G. E. Hanson. 2002. Using reflectance sensors in agronomy and weed science. Weed Technology, 16(3), 520-527.
Franzen, D. W., L. K. Sharma and H. Bu. 2014. Active optical sensor algorithms for corn yield prediction and a corn side-dress nitrogen rate aid: NDSU Extension Service, North Dakota State University. NDSU Extension Circular SF1176-5
Bean, G. M., N. R. Kitchen., J. J. Camberato., R. B. Ferguson., F. G. Fernandez., D. W. Franzen and J. S. Shanahan. 2018. Active-optical reflectance sensing corn algorithms evaluated over the United States Midwest Corn Belt. Agronomy Journal, 110(6), 2552.
Liu, N., R. Zhao., L. Qiao., Y. Zhang., M. Li., H. Sun and X. Wang. 2020. Growth stages classification of potato crop based on analysis of spectral response and variables optimization. Sensors, 20(14), 3995
Gitelson, A., A. Viña., T. Arkebauer., D. Rundquist., G. Keydan and B. Leavitt. 2003. Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophysical Research Letters, 30(5).
Govender, M., K. Chetty and H. Bulcock. 2007. A review of hyperspectral remote sensing and its application in vegetation and water resource studies. Water Sa, 33(2), 145-151.
Hendershot, W. H and M. Duquette. 1986. A simple barium chloride method for determining cation exchange capacity and exchangeable cations. Soil science society of America journal, 50(3), 605-608.
Herrmann, I., A. Karnieli., D. J. Bonfil., Y. Cohen and V. Alchanatis. 2010. SWIR-based spectral indices for assessing nitrogen content in potato fields. International Journal of Remote Sensing, 31(19), 5127-5143
Hodgen, P., W. Raun., G. Johnson., R. Teal., K. Freeman., K. Brixey and M. Stone. 2005. Relationship between response indices measured in-season and at harvest in winter wheat. Journal of Plant Nutrition, 28(2), 221-235.
Holzapfel, C., G. Lafond., S. Brandt., P. Bullock., R. Irvine., M. Morrison and D. James. 2009. Estimating canola (Brassica napus L.) yield potential using an active optical sensor. Canadian Journal of Plant Science, 89(6), 1149-1160.
Johnson, G. 1991. A general model for predicting crop response to fertilizer. Agronomy Journal, 83(2), 367-373.
Johnson, G and W. Raun. 1995. Nitrate leaching in continuous winter wheat: use of a soil-plant buffering concept to account for fertilizer nitrogen. Journal of Production Agriculture, 8(4), 486-491.
Johnson, G and W. Raun. 2003. Nitrogen response index as a guide to fertilizer management. Journal of Plant Nutrition, 26(2), 249-262
Jongschaap, R. E. E. 2006. Integrating crop growth simulation and remote sensing to improve resource use efficiency in farming systems. Wageningen University and Research. 1-24pp
Keeney, D. R and D. W. Nelson. 1982. Nitrogen—Inorganic Forms 1. Methods of soil analysis. Part 2. Chemical and microbiological properties (methods of soil an2), 643-698.
Knudsen, D and D. Beegle. 1988. Recommended phosphorus tests. Recommended chemical soil tests procedures for the north central region. Bulletin No. 499 (Revised). p. 12-15.
Large, E. C. 1954. Growth stages in cereals illustration of the Feekes scale. Plant pathology, 3(4), 128-129.
Lukina, E., K. Freeman., K. Wynn., W. Thomason., R. Mullen., M. Stone and R. Elliott. 2001. Nitrogen fertilization optimization algorithm based on in-season estimates of yield and plant nitrogen uptake. Journal of Plant Nutrition, 24(6), 885-898.
Maine, U. O. Analytical Lab and Maine Soil Testing Service. Retrieved from https://umaine.edu/soiltestinglab/
Masood, T. K and S.S. Shahadha. 2021. Simulating The Effect Of Climate Change On Winter Wheat Production And Water/Nitrogen Use Efficiency In Iraq: Case Study. The Iraqi Journal of Agricultural Science, 52(4), 999-1007
McIntosh, J. L. 1969. bray and morgan soil extractants modified for testing acid soils from different parent materials. Agronomy Journal, 61, 259-265.
Microsoft-Corporation. 2018. Microsoft Excel. Retrieved from https://office. microsof.com/excel
Mullen, R. W., K. W. Freeman., W. R. Raun., G. V. Johnson., M. L. Stone and J. B. Solie. 2003. Identifying an in-season response index and the potential to increase wheat yield with nitrogen. Agronomy Journal, 95(2), 347-351.
Raun, W. R and G. V. Johnson. 1999. Improving nitrogen use efficiency for cereal production. Agronomy Journal, 91(3), 357-363.
Raun, W. R., J. B. Solie., G. V. Johnson., M. L. Stone., E. V. Lukina., W. E. Thomason and J. S. Schepers. 2001. In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agronomy Journal, 93(1), 131-138.
Raun, W. R., J. B. Solie., G. V. Johnson., M. L. Stone., R. W. Mullen., K. W. Freeman and E. V. Lukina. 2002. Improving nitrogen use efficiency in cereal grain production with optical sensing and variable rate application. Agronomy Journal, 94(4), 815-820.
Sharma, L and S. Bali. 2017. A review of methods to improve nitrogen use efficiency in agriculture. Sustainability, 10(1), 51.
Sharma, L., S. Bali., J. Dwyer., A. Plant and A. Bhowmik. 2017. A case study of improving yield prediction and sulfur deficiency detection using optical sensors and relationship of historical potato yield with weather data in maine. Sensors, 17(5), 1095.
Sharma, L., A. Zaeen., S. Bali and J. Dwyer. 2017. Improving nitrogen and phosphorus efficiency for optimal plant growth and yield. in new visions in plant science: IntechOpen. New Vision in Plant Science, 13-40pp
Sharma, L. K. 2014. Evaluation of active optical ground-based sensors to detect early Nitrogen Deficiencies in Corn. North Dakota State University. ProQuest Dissertations.1-224 pp
Sharma, L. K., H. Bu., A. Denton and D. Franzen. 2015. Active-optical sensors using red NDVI compared to red edge NDVI for prediction of corn grain yield in North Dakota, USA. Sensors, 15(11), 27832-27853.
Sharma, L. K., H. Bu and D. W. Franzen. 2016. Comparison of two ground-based active-optical sensors for in-season estimation of corn (Zea mays, L.) yield. Journal of Plant Nutrition, 39(7), 957-966.
Shayaa H, Hussein W. A. 2019. Effect of Neem (Azadirachta indica) leaves extract and organic fertilizer in the productivity and quality of two potatoes Varieties, Iraqi Journal of Agricultural Sciences, 50(1): 275- 285. https://doi.org/10.36103/ijas.v50i1.293
SPSS-IBM-Corp. 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp. Released 2017. (Version 25.0). Armonk, NY
Swain, E. Y., L. Rempelos., C. H. Orr., G. Hall., R. Chapman., M. Almadni and J. M. Cooper, J. M. 2014. Optimizing nitrogen use efficiency in wheat and potatoes: interactions between genotypes and agronomic practices. Euphytica, 199 (1-2), 119-136.
Teal, R., B. Tubana., K. Girma., K. Freeman., D. Arnall., O. Walsh and W. Raun. 2006. In-season prediction of corn grain yield potential using normalized difference vegetation index. Agronomy Journal, 98(6), 1488-1494.
Teboh, J. M., B. S. Tubaña., T. K. Udeigwe., Y. Y. Emendack and J. Lofton. 2012. Applicability of ground-based remote sensors for crop N management in Sub Saharan Africa. Journal of Agricultural Science, 4(3), 175.
Thind, H., A. Kumar and M. Vashistha. 2011. Calibrating the leaf colour chart for need based fertilizer nitrogen management in different maize (Zea mays L.) genotypes. Field Crops Research, 120(2), 276-282.
Tilman, D., K. G. Cassman., P. A. Matson., R. Naylor and S. Polasky. 2002. Agricultural sustainability and intensive production practices. Nature, 418(6898), 671.
Tremblay, N. 2004. Determining nitrogen requirements from crops characteristics. Benefits and challenges. Recent Research Developments in Agronomy and Horticulture, 157-182.
Tyler, K., F. Broadbent and J. Bishop. 1983. Efficiency of nitrogen uptake by potatoes. American Potato Journal, 60(4), 261-269.
United States Climate Data. 2018. Climate data for Maine, ME, Temperature-Precipitation-Sunshine-Snowfall. version 2.3. Retrieved from http://www. usclima -tedata.com
United States Department of Agriculture. 2019. Natural Resources Conservation Service. Web Soil Survey. Retrieved from https://www.nrcs.usda.gov/wps/portal/nrcs/main/national/contact/
Vos, J and D. MacKerron. 2000. Basic concepts of the management of supply of nitrogen and water in potato production.
Wang, C., J. Johnston., D. Vail., J. Dickinson., and D. Putnam 2015. High-Precision Land-Cover-Land-Use GIS Mapping and Land Availability and Suitability Analysis for Grass Biomass Production in the Aroostook River Valley, Maine, USA. Land, 4(1), 231-254
Wang, H and X. Xu. 2018. Cloud classification in wide-swath passive sensor images aided by narrow-swath active sensor data. Remote Sensing, 10(6), 812.
Watson, D and J. R. Brown. 1998. pH and Lime Requirement, p. 13-16. In: Recommended Chemical Soil Test Procedures for the North Central Region. NCR Publication No. 221. Missouri Agricultural Experiment Station, Columbia, MO, USA
Westermann, D. 1993. Fertility management. In: RC Rowe (ed), Potato Health Management. APS Press, St. Paul, MN (pp. 77-86).
Zaeen, A. A., L. K. Sharma., A. Jasim., S. Bali., A. Buzza and A. Alyokhin. 2020. Yield and quality of three potato cultivars under series of nitrogen rates. Agrosystems, Geosciences & Environment, 3(1), e20062.
Zainaldeen M, Abdul Rasool E. J. 2018. Effect of foliar application of gibberellin and nutrients on growth and yield of potato var. “burren”, Iraqi Journal of Agricultural Sciences,49(2):168-176. https://doi.org/10.36103/ijas.v49i2.232
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