Use of GreenSeeker and CM-100 as manual tools for nitrogen management and yield prediction in irrigated potato (Solanum tuberosum) production
Abstract
This study evaluated the possibility of the use of GreenSeeker sensor and CM-100 chlorophyll content meter for in-season N and yield prediction in order to promote timely split N application in potato production in Kenya. Four N-fertilization rates; N0 (0), N1 (60), N2 (90) and N3 (130 kg N/ha) were led out in a Randomized Complete Block Design (RCBD) in a Greenhouse for two seasons. The results showed that % N leaf content was significantly affected by N rates. The % N leaf content and potato leaf chlorophyll content decreased as the season continued whereas the Normalized Difference Vegetation Index (NDVI) increased as the season continued. CM-100 values were significantly correlated with % N leaf content at vegetative (r=0.86***) and tuber initiation (r=0.74***) growth stages of the crop whereas the NDVI values were only significantly correlated with % N leaf at tuber initiation (r=0.82***). A significant relationship was found between CM-100 values taken at different potato stages (end of vegetative, tuber initiation, bulking and maturation stages) and tuber yield (r=0.90***, 0.82***, 0.47* and 0.41*). The NDVI values at end of vegetative growth, tuber initiation and maturation of potato were also significantly correlated with tuber yield (r=0.81***, 0.43* and 0.54*), except at bulking stage (r=0.33). For efficient in-season N management and yield prediction, CM-100 and GreenSeeker are recommended at an early stage of the crop. Further research in the different potato growing areas in Kenya to establish the different thresholds at different potato growth stages is recommended.
Keywords:
% N leaf, Chlorophyll, NDVI, Potato-stages, ThresholdDownloads
References
Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration-guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome, 300(9), D05109.
Anderson, J., & Ingram, J. (1993). A handbook of methods. CAB International, Wallingford, Oxfordshire, 221.
Aschonitis, V., Antonopoulos, V., Lekakis, E., Litskas, V., Kotsopoulos, S., & Karamouzis, D. (2013). Estimation of field capacity for aggregated soils using changes of the water retention curve under the effects of compaction. European Journal of Soil Science, 64(5), 688-698, https://doi.org/10.1111/ejss.12058
Badr, M., El-Tohamy, W., & Zaghloul, A. (2012). Yield and water use efficiency of potato grown under different irrigation and nitrogen levels in an arid region. Agricultural Water Management, 110, 9-15, https://doi.org/10.1016/j.agwat.2012.03.008
Ballester, C., Hornbuckle, J., Brinkhoff, J., Smith, J., & Quayle, W. (2017). Assessment of in-season cotton nitrogen status and lint yield prediction from unmanned aerial system imagery. Remote Sensing, 9(11), 1149, https://doi.org/10.3390/rs9111149
Bauder, T. A., Waskom, R., Sutherland, P., & Davis, J. (2011). Irrigation water quality criteria. Colorado State University. Libraries.
Bijay, S., & 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(4), 1127, https://doi.org/10.3390/s20041127
Black, C. A., & American Society of Agronomy. (1965). Methods of soil analysis: Part 1 Physical and mineralogical properties, including statistics of measurement and sampling, 9.1
Bouyoucos, G. J. (1962). Hydrometer method improved for making particle size analyses of soils 1. Agronomy Journal, 54(5), 464-465, https://doi.org/10.2134/agronj1962.00021962005400050028x
C.A. Black, editor-in-chief. Madison, Wis: American Society of Agronomy. https://doi.org/10.2134/agronmonogr9.1
Cao, Q., Miao, Y., Feng, G., Gao, X., Li, F., Liu, B., & Khosla, R. (2015). Active canopy sensing of winter wheat nitrogen status: An evaluation of two sensor systems. Computers and Electronics in Agriculture, 112, 54-67, https://doi.org/10.1016/j.compag.2014.08.012
Chlingaryan, A., Sukkarieh, S., & Whelan, B. (2018). Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: A review. Computers and Electronics in Agriculture, 151, 61-69. https://doi.org/10.1016/j.compag.2018.05.012
Cilia, C., Panigada, C., Rossini, M., Meroni, M., Busetto, L., Amaducci, S., Boschetti, M., Picchi, V., & Colombo, R. (2014). Nitrogen status assessment for variable rate fertilization in maize through hyperspectral imagery. Remote Sensing, 6(7), 6549-6565, https://doi.org/10.3390/rs6076549
Cohen, Y., Alchanatis, V., Zusman, Y., Dar, Z., Bonfil, D.J., Karnieli, A., Zilberman, A., Moulin, A., Ostrovsky, V., Levi, A., & Brikman, R. (2010). Leaf nitrogen
estimation in potato based on spectral data and on simulated bands of the VENμS satellite. Precision Agriculture, 11(5), 520-537, https://doi.org/10.1007/s11119-009-9147-8
Crain, J., Ortiz-Monasterio, I., & Raun, B. (2012). Evaluation of a reduced cost active NDVI sensor for crop nutrient management. Journal of Sensors, 2012. https://doi.org/10.1155/2012/582028
El Mokh, F., Nagaz, K., Masmoudi, M. M., & Mechlia, N. B. (2015). Yield and water productivity of drip-irrigated potato under different nitrogen levels and irrigation regime with saline water in arid Tunisia. American Journal of Plant Sciences, 6(04), 501. http://dx.doi.org/10.4236/ajps.2015.64054
Elsaid, E., & Silva, R. (2017). Potential of sun hemp residue to provide potato with adequate nitrogen. Journal of Plant Nutrition, 40(6), 851-860, https://doi.org/10.1080/01904167.2016.1262397
Fernandes, F. M., Soratto, R. P., Fernandes, A. M., & Souza, E. F. (2021). Chlorophyll meter-based leaf nitrogen status to manage nitrogen in tropical potato production. Agronomy Journal. https://doi.org/10.1002/agj2.20589
Gabriel, J. L., Zarco-Tejada, P. J., López-Herrera, P. J., Pérez-Martín, E., Alonso-Ayuso, M., & Quemada, M. (2017). Airborne and ground level sensors for monitoring nitrogen status in a maize crop. Biosystems Engineering, 160, 124-133, https://doi.org/10.1016/j.biosystemseng.2017.06.003
García-Martínez, H., Flores-Magdaleno, H., Ascencio-Hernández, R., Khalil-Gardezi, A., Tijerina-Chávez, L., Mancilla-Villa, O. R., & Vázquez-Peña, M. A. (2020). Corn Grain Yield Estimation from Vegetation Indices, Canopy Cover, Plant Density, and a Neural Network Using Multispectral and RGB Images Acquired with Unmanned Aerial Vehicles. Agriculture, 10(7), 277. https://doi.org/10.3390/agriculture10070277
Goffart, J.-P., Olivier, M., & Frankinet, M. (2011). Crop nitrogen status assessment tools in a decision support system for nitrogen fertilization management of potato crops. HortTechnology, 21(3), 282-286, https://doi.org/10.21273/HORTTECH.21.3.282
Güler, S. (2009). Effects of nitrogen on yield and chlorophyll of potato (Solanum tuberosum L.) cultivars. Bangladesh Journal of Botany, 38(2), 163-169, https://doi.org/10.3329/bjb.v38i2.5141
Jackson, S. D. (1999). Multiple signaling pathways control tuber induction in potato. Plant Physiology, 119(1), 1-8, https://doi.org/10.1104/pp.119.1
Koch, M., Naumann, M., Pawelzik, E., Gransee, A., & Thiel, H. (2019). The importance of nutrient management for potato production Part I: Plant nutrition and yield. Potato Research, 63(1), 97-119, https://doi.org/10.1007/s11540-019-09431-2
Li, L., Qin, Y., Liu, Y., Hu, Y., & Fan, M. (2012). Leaf positions of potato suitable for determination of nitrogen content with a SPAD meter. Plant Production Science, 15(4), 317-322, https://doi.org/10.1626/pps.15.317
Li, R., Chen, J., Qin, Y., & Fan, M. (2019). Possibility of using a SPAD chlorophyll meter to establish a normalized threshold index of nitrogen status in different potato cultivars. Journal of Plant Nutrition, 42(8), 834-841, https://doi.org/10.1080/01904167.2019.1584215
Lofton, J., Tubana, B. S., Kanke, Y., Teboh, J., Viator, H., & Dalen, M. (2012). Estimating sugarcane yield potential using an in-season determination of normalized difference vegetative index. Sensors, 12(6), 7529-7547, https://doi.org/10.3390/s120607529
Louvieaux, J., Leclercq, A., Haelterman, L., & Hermans, C. (2020). In-field observation of root growth and nitrogen uptake efficiency of winter oilseed rape. Agronomy, 10(1), 105. https://doi.org/10.3390/agronomy10010105
Majić, A., Poljak, M., Sabljo, A., Knezović, Z., & Horvat, T. (2008). Efficiency of use of chlorophyll meter and Cardy-ion meter in potato nitrogen nutrition supply. Cereal Research Communications, 36, 1431-1434. Retrieved May 24, 2021, from http://www.jstor.org/stable/90002983
Maresma, Á., Ariza, M., Martínez, E., Lloveras, J., & Martínez-Casasnovas, J. A. (2016). Analysis of vegetation indices to determine nitrogen application and yield prediction in maize (Zea mays L.) from a standard UAV service. Remote Sensing, 8(12), 973, https://doi.org/10.3390/rs8120973
Maresma, Á., Ariza, M., Martínez, E., Lloveras, J., & Martínez-Casasnovas, J. A. (2018). Erratum: Maresma, A., et al. Analysis of Vegetation Indices to Determine Nitrogen Application and Yield Prediction in Maize (Zea mays L.) from a Standard UAV Service. Remote Sensing, 10(3), 368, https://doi.org/10.3390/rs10030368
Marouani, A., Behi, O., Salah, H. B. H., & Quilez, O. A. (2015). Establishment of chlorophyll meter measurements to manage crop nitrogen status in potato crop. Communications in Soil Science and Plant Analysis, 46(4), 476-489. https://doi.org/10.1080/00103624.2014.997386
Mengist, M. F., Milbourne, D., Griffin, D., McLaughlin, M. J., Creedon, J., Jones, P. W., & Alves, S. (2021). Zinc uptake and partitioning in two potato cultivars: implications for biofortification. Plant and Soil, 1-13, https://doi.org/10.1007/s11104-021-04874-4
Muñoz-Huerta, R. F., Guevara-Gonzalez, R. G., Contreras-Medina, L. M., Torres-Pacheco, I., Prado-Olivarez, J., & Ocampo-Velazquez, R. V. (2013). A review of methods for sensing the nitrogen status in plants: advantages, disadvantages and recent advances. Sensors, 13(8), 10823-10843, https://doi.org/10.3390/s130810823
Németh, T., Máthé-Gáspár, G., Radimszky, L., & Győri, Z. (2007). Effect of nitrogen fertilizer on the nitrogen, sulphur and carbon contents of canola (Brassica napus L.) grown on a calcareous chernozem soil. Cereal Research Communications, 35(2), 837-840, http://www.jstor.org/stable/45138058
Ojala, J., Stark, J., & Kleinkopf, G. (1990). Influence of irrigation and nitrogen management on potato yield and quality. American Potato Journal, 67(1), 29-43, https://doi.org/10.1007/BF02986910
Okalebo, J. R., Gathua, K. W., & Woomer, P. L. (2002). Laboratory methods of soil and plant analysis: a working manual second edition. Sacred Africa, Nairobi, 21.
Scherer, T. F., Seelig, B., & Franzen, D. (1996). Soil, water and plant characteristics important to irrigation.
Sharma, L. K., & Bali, S. K. (2018). A review of methods to improve nitrogen use efficiency in agriculture. Sustainability, 10(1), 51, https://doi.org/10.3390/su10010051
Waaswa, A., & Satognon, F. (2020). Development and the Environment: Overview of the Development Planning Process in Agricultural Sector, in Uganda. Journal of Sustainable Development, 13(6). https:doi.org/10.5539/jsd.v13n6p1
Waaswa, A., Oywaya Nkurumwa, A., Mwangi Kibe, A., & Ngeno Kipkemoi, J. (2021). Climate-Smart agriculture and potato production in Kenya: review of the determinants of practice. Climate and Development, 1-16. https://doi.org/10.1080/17565529.2021.1885336
Wilcox, L. (1955). Classification and use of irrigation waters (No. 969). US Department of Agriculture.
Wilkinson, S., Weston, A. K., & Marks, D. J. (2019). Stabilising Urea amine nitrogen increases potato tuber yield by increasing chlorophyll content, reducing shoot growth rate and increasing biomass partitioning to roots and tubers. Potato Research, 1-23. https://doi.org/10.1007/s11540-019-09436-x
Zaeen, A. A. (2020). Improving Nitrogen Management in Potatoes with Active Optical Sensors. Electronic Theses and Dissertations. 3202. https://digitalcommons.library.umaine.edu/etd/3202
Zebarth, B., & Rosen, C. J. (2007). Research perspective on nitrogen BMP development for potato. American Journal of Potato Research, 84(1), 3-18, https://doi.org/10.1007/BF02986294
Zheng, H. l., Liu, Y. C., Qin, Y. l., Yang, C., & Fan, M. S. (2015). Establishing dynamic thresholds for potato nitrogen status diagnosis with the SPAD chlorophyll meter. Journal of Integrative Agriculture, 14(1), 190-195, https://doi.org/10.1016/S2095-3119(14)60925-4
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