Harnessing chlorophyll and canopy reflectance indices relationship for grain yield, protein and starch content in maize cultivars under different nitrogen treatments

Muhoja Sylivester Nyandi, Ebenezer Ayew Appiah and Petér Pepó
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Muhoja Sylivester Nyandi: Kálmán Kerpely Doctoral School, University of Debrecen, Debrecen, Hungary
Ebenezer Ayew Appiah: Kálmán Kerpely Doctoral School, University of Debrecen, Debrecen, Hungary
Petér Pepó: Institute of Plant Science, University of Debrecen, Debrecen, Hungary

Plant, Soil and Environment, vol. preprint

Abstract: 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 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlpse:v:preprint:id:633-2024-pse

DOI: 10.17221/633/2024-PSE

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