An Inverse Correlation between Corn Temperature and Nitrogen Stress: A Field Case Study

Abstract

Nitrogen is one of the most important yield‐limiting nutrients for corn (Zea mays). The ability of thermal remote sensing to detect nitrogen deficiency in corn may enable precision agriculture to modify nitrogen rates according to field conditions. This study applies the exergy destruction principle as a theory to explain the inverse relationship between surface temperature and nitrogen rate. Two hypotheses were developed. First, it was hypothesized that agricultural crops experiencing greater growth and providing greater yield will have lower surface temperature. The second hypothesis was that corn grown under optimum levels of nitrogen will have lower surface temperatures compared to corn grown under nitrogen stressed conditions. Field studies were conducted during two summer seasons (2016 and 2017) on an established long‐term field trial of corn yield response to varying rates of nitrogen. It was found that corn surface temperature decreased as the rate of nitrogen increased. A shallow but statistically significant (P < 0.05) negative slope was observed consistently with increasing rates of nitrogen. Surface temperature measurements, however, were variable. This variability was the result of external and weather dependent variables that influenced leaf surface temperature. Despite this variability, the exergy destruction principle provides a theory from which thermal remote sensing can be applied through the use of surface temperature measurements to detect physiological stress in crop plants. Core Ideas Thermal remote sensing was proposed to detect nitrogen stress in corn plants. Nitrogen stressed plants had higher surface temperatures than less stressed plants. Temperature trends were consistent with the exergy destruction principle. Nitrogen‐temperature correlations were statistically significant at the 0.05 significance level. Corn yield increases with nitrogen rate increase and surface temperature decrease.

Corn Nitrogen Status Diagnosis with an Innovative Multi-Parameter Crop Circle Phenom Sensing System

“…Yan et al [42] found that rice canopy temperature responded to N rate, with N stress causing higher temperatures. Similarly, Alzaben, Fraser, and Swanton [22] used thermal imagery to investigate the relation between canopy temperature and N status. The study observed that both corn leaf and whirl temperatures statistically responded to N treatment, with optimal N corresponding to lower canopy temperature.…”

“…These additional metrics can be used to calculate physiological metrics such as fractional PAR (fPAR) and canopy-air temperature difference (∆Temp). Previous research indicated that PAR [21] and canopy temperature [22] could be used to estimate biomass and crop N stress. Therefore, through measuring spectral, estimated structural characteristics, and climatic variables, the Crop Circle Phenom sensor system is hypothesized to be able to improve corn N status estimation and diagnosis compared to only using vegetation indices such as NDVI and NDRE.…”

Canonical interrelationships in morphological characters, yield and nutritional components of corn

“…The second canonical pair explains that the increase in the content of the amino acids Alanine (ALA), Arginine (ARG), Asparagine (ASP), Proline (PROL), Serine (SER), Tryptophan (TRYP) and Methionine (MET), are correlated to reduction of the seed length (SL) and seed thickness (ST) components. This situation can be explained by nitrogen deficiency, given that this element is a component of the structure of amino acids, as well as, emphasizes Alzaben, Fraser and Swanton (2019), by stating that nitrogen is one of the most important nutrients to limit corn yield, and supported by Cates and Ruark (2017) with decreases in the yield of Poaceae due to the reduction of the organic matter content of the soil and consequently the supply of nitrogen. Positive correlation of the amino acids alanine (ALA), asparagine (ASP), serine (SER), tryptophan (TRYP) and methionine (MET), was verified with the components of the yield ear mass (EM), ear grain mass (EGM), seed thickness (ST) and grain yield (GY), in the third canonical pair.…”

The Role of Engineering Thermodynamics in Explaining the Inverse Correlation between Surface Temperature and Supplied Nitrogen Rate in Corn Plants: A Greenhouse Case Study

“…Furthermore, the thermal camera was calibrated under laboratory conditions, using a blackbody source (463 cavity black-body, Infrared industries, Hayward, CA, USA) with a 2.2 cm diameter selected measurement aperture. The difference between the temperature obtained by the thermal camera and the temperature obtained by using the black-body cavity was no more than the accuracy of the thermal camera (±2 • C) [63]. The sample size for each experiment was randomly selected as 10 corn plants in the middle two rows out of 30 plants per bench, to avoid border effects.…”