Plant Soil Environ., 2025, 71(8):525-533 | DOI: 10.17221/633/2024-PSE
Harnessing chlorophyll and canopy reflectance indices relationship for grain yield, protein and starch content in maize cultivars under different nitrogen treatmentsOriginal Paper
- 1 Kálmán Kerpely Doctoral School, University of Debrecen, Debrecen, Hungary
- 2 Department of Crop Science and Beekeeping Technology, College of Agriculture and Food Technology, University of Dar es Salaam, Dar es Salaam, Tanzania
- 3 Institute of Plant Science, University of Debrecen, Debrecen, Hungary
Crop production faces increased climate change and land degradation stresses, compromising global food security with the growing population. Maize (Zea mays L.) is a versatile crop used for food, feed, and raw materials, contributing significantly to global food systems. Abiotic stresses like drought and soil fertility limit its production. Fertilisation is an amelioration technique that optimises maize growth and yield by maintaining optimum nutrition and leveraging nutrient deficiency conditions. Precision agricultural tools like chlorophyll meters are essential for non-destructive chlorophyll assessment and nitrogen status. An experiment conducted at the University of Debrecen evaluated the impact of nitrogen (N) fertilisation (0, 90, and 150 kg/ha) and three maize cultivars (P9610-FAO 340, DKC4590-FAO360, and GKT376-FAO360) on physiological parameters, namely: relative chlorophyll content (SPAD), normalised differences vegetation index (NDVI) and grain quality. Results showed that SPAD and NDVI positively correlated (P < 0.05) with grain quality and yield. Nitrogen application significantly influenced SPAD. Maize cultivars and N rates with higher chlorophyll content had maximum yield. Cultivar responses to nitrogen rates significantly (P < 0.05) varied by crop year. Higher SPAD and NDVI values were associated with higher protein content. Therefore, SPAD and NDVI values could be used to analyse the nutrient requirements of maize under field conditions to estimate grain yield.
Keywords: macronutrient; spectrometry; phenotyping; remotesensing; bioindicator; hybrid selection
Received: December 1, 2024; Revised: June 23, 2025; Accepted: June 24, 2025; Prepublished online: July 31, 2025; Published: August 28, 2025 Show citation
ACS | AIP | APA | ASA | Harvard | Chicago | Chicago Notes | IEEE | ISO690 | MLA | NLM | Turabian | Vancouver |
References
- Ali A.M., Salem H.M. (2024): Site-specific nitrogen fertilizer management using canopy reflectance sensors, chlorophyll meters and leaf color charts: a review. Nitrogen, 5: 828-856.
Go to original source...
- Badu-Apraku B., Fakorede M.A.B., Menkir A., Sanogo D. (2012): Conduct and Management of Maize Field Trials. Nigeria, International Institute of Tropical Agriculture. ISBN: 978-978-8444-02-2
- Belmahi M., Hanchane M., Krakauer N.Y., Kessabi R., Bouayad H., Mahjoub A., Zouhri D. (2023): Analysis of the relationship between grain yield and NDVI from MODIS in the Fez-Meknes region, Morocco. Remote Sensing, 15: 2707.
Go to original source...
- Berger K., Verrelst J., Féret J.-B., Wang Z.H., Wocher M., Strathmann M., Danner M., Mauser W., Hank T. (2020): Crop nitrogen monitoring: recent progress and principal developments in the context of imaging spectroscopy missions. Remote Sensing of Environment, 242: 111758.
Go to original source...
Go to PubMed...
- Bojtor C., Mousavi S.M.N., Illés Á., Golzardi F., Széles A., Szabó A., Nagy J., Marton C.L. (2022): Nutrient composition analysis of maize hybrids affected by different nitrogen fertilization systems. Plants, 11: 1593.
Go to original source...
Go to PubMed...
- Bojtor C., Mousavi S.M.N., Illés Á., Széles A., Nagy J., Marton C.L. (2021): Stability and adaptability of maize hybrids for precision crop production in a long-term field experiment in Hungary. Agronomy, 11: 2167.
Go to original source...
- Correia P.M., da Silva A.B., Vaz M., Carmo-Silva E., Marques da Silva J. (2021): Efficient regulation of CO2 assimilation enables greater resilience to high temperature and drought in maize. Frontiers in Plant Science, 12: 675546.
Go to original source...
Go to PubMed...
- Gao C., El-Sawah A.M., Ali D.F.I., Alhaj Hamoud Y., Shaghaleh H., Sheteiwy M.S. (2020): The integration of bio and organic fertilizers improves plant growth, grain yield, quality and metabolism of hybrid maize (Zea mays L.). Agronomy, 10: 319.
Go to original source...
- Gheith E.M.S., El-Badry O.Z., Lamlom S.F., Ali H.M., Siddiqui M.H., Ghareeb R.Y., El-Sheikh M.H., Jebril J., Abdelsalam N.R., Kandil E.E. (2022): Maize (Zea mays L.) productivity and nitrogen use efficiency in response to nitrogen application levels and time. Frontiers in Plant Science, 13: 941343.
Go to original source...
Go to PubMed...
- Javed A., Ahmad N., Ahmed J., Hameed A., Ashraf M.A., Zafar S.A., ... & Ali E.F. (2022): Grain yield, chlorophyll and protein contents of elite wheat genotypes under drought stress. Journal of King Saud University-Science, 34: 102279.
Go to original source...
- Luo X., Keenan T.F., Chen J.M., Croft H., Colin Prentice I., Smith N.G., Walker A.P., Wang H., Wang R., Xu C. Zhang Y. (2021): Global variation in the fraction of leaf nitrogen allocated to photosynthesis. Nature Communications, 12: 4866.
Go to original source...
Go to PubMed...
- Melash A.A., Bogale A.A., Bytyqi B., Nyandi M.S., Ábrahám É.B. (2023): Nutrient management: as a panacea to improve the caryopsis quality and yield potential of durum wheat (Triticum turgidum L.) under the changing climatic conditions. Frontiers in Plant Science, 14: 1232675.
Go to original source...
Go to PubMed...
- Mu X., Chen Y. (2021): The physiological response of photosynthesis to nitrogen deficiency. Plant Physiology and Biochemistry, 158: 76-82.
Go to original source...
Go to PubMed...
- Panek E., Gozdowski D., Stêpieñ M., Samborski S., Ruciñski D., Buszke B. (2020): Within-field relationships between satellite-derived vegetation indices, grain yield and spike number of winter wheat and triticale. Agronomy, 10: 1842.
Go to original source...
- Prathap V., Ali K., Singh A., Vishwakarma C., Krishnan V., Chinnusamy V., Tyagi A. (2019): Starch accumulation in rice grains subjected to drought during grain filling stage. Plant Physiology and Biochemistry, 142: 440-451.
Go to original source...
Go to PubMed...
- Rhezali A., Aissaoui A.E. (2021): Feasibility study of using absolute SPAD values for standardized evaluation of corn nitrogen status. Nitrogen, 2: 298-307.
Go to original source...
- Sishodia R.P., Ray R.L., Singh S.K. (2020): Applications of remote sensing in precision agriculture: a review. Remote Sensing, 12: 3136.
Go to original source...
- Tamás A., Kovács E., Horváth É., Juhász C., Radócz L., Rátonyi T., Ragán P. (2023): Assessment of NDVI dynamics of maize (Zea mays L.) and its relation to grain yield in a polyfactorial experiment based on remote sensing. Agriculture, 13: 689.
Go to original source...
- Wang Z., Chen J., Zhang J., Fan Y., Cheng Y., Wang B., Yong T., Liu W., Liu J., Du J., Wu Y. Yang F. (2021): Predicting grain yield and protein content using canopy reflectance in maize grown under different water and nitrogen levels. Field Crops Research, 260: 107988.
Go to original source...
- Wang Z., Chen J., Zhang J., Tan X., Raza M.A., Ma J., Zhu Y., Yang F., Yang W. (2022): Assessing canopy nitrogen and carbon content in maize by canopy spectral reflectance and uninformative variable elimination. The Crop Journal, 10: 1224-1238.
Go to original source...
- Wood C.W., Reeves D.W., Himelrick D.G. (1993): Relationships between chlorophyll meter readings and leaf chlorophyll concentration, N status, and crop yield: a review. Proceedings of the Agronomy Society of New Zealand, 23: 1-9.
- Yan Y., Hou P., Duan F., Niu L., Dai T., Wang K., Zhao M., Li S., Zhou W., Zhou W. (2021): Improving photosynthesis to increase grain yield potential: an analysis of maize hybrids released in different years in China. Photosynthesis Research, 150: 295-311.
Go to original source...
Go to PubMed...
- Yang B., Zhu W., Rezaei E.E., Li J., Sun Z., Zhang J. (2022): The optimal phenological phase of maize for yield prediction with high-frequency UAV remote sensing. Remote Sensing, 14: 1559.
Go to original source...
- Yang F., Zhang Y., Zhang H., Hu J., Zhu W., Liu L., Liu H., Fahad S., Gao Q. (2023): Comparative physiological and transcriptome analysis of leaf nitrogen fluxes in stay-green maize during the vegetative stage. Plant Physiology and Biochemistry, 204: 108147.
Go to original source...
Go to PubMed...
This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.