Chlorophyll Meter Readings Can Predict Nitrogen Need and Yield Response of Corn in the North‐Central USA

Abstract

Nitrogen fertilizer is a fundamental input for production of corn (Zea mays L.) that can move to ground and surface waters when overapplied. Previous research has shown that chlorophyll meter (CM) readings can indicate N stress in corn, but has not addressed whether the amount of N needed can be predicted by CM readings. Our objective was to evaluate whether CM readings can predict corn N need and yield response to N. Sixty-six N rate experiments were conducted in seven north-central states over a 4-yr period. Linear regression was used to relate absolute and relative CM readings over a range of growth stages to economically optimal N rate (EONR) and yield response to N applied at growth stage V7 or earlier. Chlorophyll meter readings at all growth stages from V5 to R5 were significantly related (P , 0.0001 in 22 of 24 models, P , 0.01 in 2 models) to EONR and yield response to N. Relationships were stronger for relative than for than absolute CM readings, and also were stronger when the corn had received no N fertilizer at planting. Coefficients of determination ranged from 0.53 to 0.76 for relative CM reading as a predictor of EONR or yield response to N, and were lower for the V5 to V9 stage than for later stages. Earlier research has indicated that measurements with this level of predictive accuracy can produce N rate recommendations that are more profitable than current N management practices. Our findings suggest that CM readings (and potentially other measures of corn color) are quantitatively related to early-season EONR and yield response to N over a wide range of environments with enough accuracy to be helpful in making management decisions.

Responsive in-season nitrogen management for cereals

“…Furthermore, they noted that when the sufficiency index at V8 was below 90%, maximum yields were not achieved with in-season N fertilizer applications, in part because early season N was below that needed for optimum growth and yield potentials had already been reduced. In another study involving 66 N rate experiments conducted in seven north-central states in the U.S. over a 4-year period, Scharf et al (2006) found that CM readings at all growth stages from V5 to R5 were significantly correlated with the economically optimal N rate and yield response to N applied at growth stage V7 or earlier. They concluded that CM readings are a good predictor of corn yield response to N over a wide range of soil types, geography, landscape forms, weather environments, corn hybrids, and management practices, and would be useful in making N-fertilizer management decisions.…”

Strengths and Limitations of Nitrogen Rate Recommendations for Corn and Opportunities for Improvement

“…6); (v) high and variable N prices; and (vi) cross-state agency programs, crop advisors, and producers desiring uniform recommendations across state boundaries. Of most importance was the poor correlation between yield-goal-based rate recommendations and optimal rates found in research trials; long-term research from the 1970s to the 1990s indicated that optimal N rates had not changed despite yield increases ; and yield level was found to be unrelated to EONR Bundy, 1994a, 1994b;Lory and Scharf, 2003;Scharf et al, 2006a).…”

“…The latter application is of use mainly when manure N is part of the N supply, creating a significant proportion of fields where the correct decision is "no additional N needed". Systems for making N rate decisions based on chlorophyll meter readings were later developed by Scharf et al (2006a), Hawkins et al (2007), and Varvel et al (2007). The relationships between relative chlorophyll meter reading and optimal N rate (or suggested N rate) are similar for these three references, suggesting that these sets of available interpretations are robust.…”

A Public–Industry Partnership for Enhancing Corn Nitrogen Research and Datasets: Project Description, Methodology, and Outcomes

“…Additionally, the experimental design for that research did not include the necessary N treatments to calculate a precise optimal N rate, so tool performance evaluation was limited. In another study, a wide range of soil and weather environments may have been explored, but only one N management decision tool was evaluated (Scharf et al, 2006).…”