Visually Rating the Nitrogen Status of Corn

Most producers use firing, the premature death of lower leaves, to visually rate the N status of corn ( Zea mays L.). Although such visual rating is often done, there is a severe lack of quantitative information about the relationships between firing and N status. Here we establish such relationships by using data collected in 43 N response trials over 5 yr in Iowa. Visual signs of N deficiency were quantified by “leaf ratings,” which indicate the average number of green leaves below the primary ear, and “adjusted leaf ratings,” which indicate leaf ratings subtracted from the highest leaf ratings that can be attained by adding N fertilizers under otherwise similar conditions. Observed relationships between yields and leaf ratings clearly indicate that casual observations of firing do not provide a reliable indicator of N status. The results showed, however, that adjusted leaf ratings were at least as reliable as leaf N analysis, the most commonly used tissue test for evaluating the N status of corn. Visual rating, like leaf N analysis, lacks the ability to detect excesses of N. The visual rating system has the obvious advantage of requiring less time, equipment, and expense. Research Question Most corn ( Zea mays L.) producers examine amounts of firing (the premature death of lower leaves) to visually rate the N status of their fields. Although such visual rating is common, there is little quantitative information concerning relationships between firing and N status. This study was done to define relationships between firing and corn yields. Literature Summary Lack of interest in describing relationships between firing and yields probably is best explained by widespread recognition that amounts of firing are influenced by moisture availability and other factors in addition to N availability. Also, tissue analysis generally has been accepted as a superior tool for evaluating N status. The superiority of tissue testing has not been demonstrated in controlled studies, however, and visual rating is much more widely used. Study Description This project involved 43 N‐response trials that were conducted over 5 yr (1986–1990). The trials included 10 rates of N (ranging from 0 to 300 lb N/acre). The plots were visually rated at various times between silking (R1 stage) and dent (R5 stage). Leaf ratings for a plant were defined as the number of green leaves below the primary ear. When counting the number of green leaves on a plant, each leaf was given a value of 1, 3/4, 2/3, 1/2, 1/3, 1/4, or 0 indicating the portion of the leaf that was green. Adjusted leaf ratings were defined as the leaf ratings on plants within a test area subtracted from the highest leaf rating that could be attained by adding N fertilizer under otherwise similar conditions. Applied Questions How good were relationships between leaf ratings and yields? Good relationships were observed between leaf ratings and yields within individual response trials (Fig. ). This explains why corn producers frequently use firing as an indicator of N status. Because leaf ratings tended to vary with moisture availability and other site‐related factors, however, leaf ratings did not provide a reliable indicator of N status across trials. How good were relationships between adjusted leaf ratings and yields? Example of observed relationships between leaf ratings and grain yields within a trial. image Adjusted leaf ratings done at the R4 stage of growth explained 80% of the variability in observed yields. Adjusted leaf ratings were at least as reliable as tissue tests based on the N concentration of leaves at silking and they offer advantages of cost and convenience. Like leaf analysis, adjusted leaf ratings do not detect excesses of N. How could corn producers use adjusted visual ratings to improve N management? Application of above‐normal rates of N to test areas within their fields enables producers to use adjusted leaf ratings to determine if deficiencies occurred at their normal rates of fertilization. Application of below‐normal rates of N to test plots enables producers to use adjusted leaf ratings to determine if the normal rate was higher than needed to maximize yields. Information presented in this paper could be used to help interpret the results.