Irrigation and Tillage Management Effects on Canopy Formation in Corn

Effects of canopy formation and function are frequently represented in irrigation management models by crop coefficients, which can be used to calculate expected crop water requirements. Soil tillage alters the microenvironment of a developing corn canopy. The objective of this study was to evaluate irrigation capacity and tillage effects on seasonal changes in maize canopy and above-ground biomass productivity. Leaf area index (LAI) and above-ground biomass (AGB) were quantified by non-destructive methods during four growing seasons for corn under two irrigation capacities (1 in./4 days or 1 in./8 days) and three tillage regimes (notillage (NT), strip tillage (ST), or conventional tillage (CT)). Irrigation capacity and tillage effects were evaluated for each sampling period; seasonal trends were evaluated for year and treatment effects. Conventional tillage management resulted in earlier canopy formation and greater AGB accumulation during early vegetative growth in three of four years. No-tillage management resulted in extended canopy duration and greater AGB at tassel stage in two of four years; ST management resulted in greatest canopy duration in one year. Evaluated during four years, seasonal trends in LAI indicated earliest development under CT and delayed canopy development under NT management. The intermediate rate of canopy development of corn under ST management, and favorable yield and water productivity, indicates utility of ST management for irrigated corn production.


Introduction
The canopy of maize crops generates the structural biomass and carbohydrates which support grain yield formation. Stomata embedded in leaves mediate the atmospheric demand, which results in the transpiration component of evapotranspiration (ET). Effects of canopy formation are frequently represented in irrigation management models by crop coefficients, which can be combined with reference or potential ET to calculate expected crop water requirements (Allen et al., 1998). The relationship of crop canopy formation and function to crop water requirements suggests the question: Can crop management alter canopy formation and subsequent productivity?
Soil tillage alters the micro-environment of a developing corn canopy, affecting crop residue distribution and soil physical properties in the tillage zone. Full surface coverage by residue was required to reduce energy-limited evaporation by 50% or more, relative to bare soil with no shading by crop canopy; partial residue coverage (25 to 75%) resulted in limited evaporation suppression relative to that of bare soil with no shading (Klocke et al., 2009). Corn grown under NT management required five to seven days Kansas Field Research 2017 longer to reach V6 development stage than corn under CT management in Ontario (Fortin, 1993). Corn yields were numerically greater under ST and NT management, relative to CT management . The objective of this study was to evaluate irrigation capacity and tillage effects on seasonal changes in maize canopy and above-ground biomass productivity.

Procedures
A corn hybrid of approximately 110-day relative maturity (Dekalb DCK60-19 in 2004and DCK60-18 in 2005through 2007 was planted in 30-inch spaced circular rows on May 8, 2004;April 27, 2005;April 20, 2006;and May 8, 2007. The two hybrids differ only slightly, with the latter hybrid having an additional genetic modification of corn rootworm control. Three target seeding rates (27,000; 30,000; and 33,000 seeds/a) were superimposed onto each tillage treatment in a complete randomized block design. Irrigation was scheduled with a weather-based water budget but was limited to the three treatment capacities of 1 in. every 4, 6, or 8 days respectively). This results in typical seasonal irrigation amounts of 12-20, 11-15, and 8-12 in., respectively. The weather-based water budget was constructed using data collected from a National Oceanic and Atmospheric Administration (NOAA) weather station located approximately 600 yd. northeast of the study site. The reference evapotranspiration (ETr) was calculated using a modified Penman combination equation similar to the procedures outlined by Kincaid and Heermann (1974). The specifics of the ETr calculations used in this study are fully described by Lamm et al. (1987). The basal crop coefficients were calculated for the area by assuming 70 days from emergence to full canopy for corn with physiological maturity at 130 days.
Leaf area index (LAI) was quantified, approximately bi-weekly, by a non-destructive light transmission technique (Welles and Norman, 1991;LAI-2000 Plant Canopy Analyzer (Li-Cor, Lincoln, NE). Three sets of four below-canopy measurements were each referenced to an above-canopy measurement, minimizing sensor exposure to direct (beam) irradiance. Readings were screened against apparent transmittance ratios exceeding 1 using the manufacturer's software, FV2000 (Li-Cor, Lincoln, NE). An inverse solution to a model of light transmission through a vegetative canopy, provided by the manufacturer, was used to quantify apparent LAI.
Above-ground biomass (AGB) was quantified by non-destructive allometric measurements from V6 through early grain fill stages. Three representative plants in each experimental unit were identified for repeated measure, commencing from V6 stage. Stem measurements included diameter of the second internode and at the upper sheath of the youngest fully expanded leaf, distance from the ground to the base of the youngest fully expanded leaf, and number of fully expanded leaves. For each sampling period, identical measurements were made for similar plants, outside the plot area but receiving similar management. These plants were cut at ground level and dried, to determine above-ground biomass. An allometric model was developed by regressing AGB against stem volume (calculated using cylindrical geometry) and cumulative growing degree days (cGDD). Coefficients of this model were then applied to in-plot measurements to calculate apparent above-ground biomass.
Growing degree days (GDD) were calculated from daily temperature extremes (Equation 1) recorded at the Kansas State University Northwest Research and Extension Center weather station, using a mercury thermometer.

GDD = T max -T min -T b Equation 1 2
Upper and lower limits to temperature extremes were 86 and 50°F, respectively. Cumulative GDD was computed by summation of GDD, commencing from planting date.
Experimental design was randomized complete block, with some restrictions based on distance from the center pivot point. Treatment design was split-plot with irrigation capacity (1 in./4 days or 1 in./8 days) as whole-plot treatment and tillage method (NT, ST, or CT) as split plot treatment. Population treatments were sampled for LAI and AGB at the mid-level (30,000 seeds/a) only.
Statistical analysis included analysis of variance (ANOVA), analysis of covariance (ANCOVA), and regression techniques (linear and non-linear). Repeated measure of LAI and maximum LAI observed in a year were analyzed by ANOVA, using Proc GLM from SAS 9.4 (SAS Institute Inc., Cary, NC). Seasonal trends in LAI and AGB were analyzed by ANCOVA using third order linear terms of cGDD or days after planting (DAP) as covariates. A logistic model was also used to quantify changes in LAI through pollen shed stage, when all leaves were fully expanded. A three-parameter form of the logistic equation (equation 2) was fit to each set of LAI measurements from V6 through R1, for each set of treatment combinations of each year, using the non-linear feature of Statistix v9.1 (Analytical Software, Tallahassee, FL). Coefficients for 'a', 'b', and 'c' terms were subjected to univariate analysis of variance, with year as a sampling environment.

LAI = a Equation 2 1 + e b -c * cGDD
A linearized form of the logistic equation (Equation 3) was also evaluated.

LAI = L o * L m Equation 3 L o + (L m -L o )e -kL m t
Here, L o and L m are initial and maximum leaf area, t represents days following emergence and k is a logistic coefficient for this linearized form (Aiken, 2005).  Early canopy formation and senescence for CT is evident (Figure 5c), with delayed canopy formation for NT; maximum canopy occurred with ST management. Similarly, more AGB accumulated during early vegetative growth under CT management ( Figure  5b) with similar AGB for ST by tassel and maximum AGB at maturity for NT. Vegetative crop water use was similar among tillage treatments (Figure 6a), but greater for NT and ST than for CT by maturity, reflecting differences in canopy senescence.

Discussion
Earlier canopy formation and AGB accumulation under CT, detected in three of four years, is consistent with a report of more rapid corn development under CT management in Ontario (Fortin, 1993). This likely results from warmer soil conditions, early emergence, and more vigorous seedling growth under CT management. Earlier canopy senescence and maturity also resulted from CT management in the same three growing seasons, indicating tillage management can cause a shift in canopy formation and senescence.

Kansas Field Research 2017
The delayed canopy formation and extended canopy duration for NT and, to a lesser extent, ST appears to be related to increased grain yield and increased water use. This could result in extended water use during the late grain fill period, which may not be sufficiently represented in standard crop coefficients used in irrigation scheduling.
Vegetative water use was similar among tillage treatments (an exception: water use was least for NT in 2006, 1 in./8 days irrigation capacity). Klocke et al. (2009) reported that virtually 100% residue cover was required to achieve evaporation suppression with incomplete canopy closure. Field observations on April 17, 2007, indicated 80%, 91%, and 99% residue cover for CT, ST, and NT, respectively. However, greater seasonal water use for ST and NT treatments appears to be associated with delayed canopy senescence and with greater grain yields.
The two forms of the logistic equation (three-term and linearized) provide scaling tools with applications to functional representation of corn canopy formation. In this regard, the tillage effect on the three-term model provides a useful basis for simulating tillage effects. Similarly, the linearized scaling relationship between LAI max and the 'k' coefficient could be useful for adjusting seasonal LAI values for remote sensing and geographic information system (GIS) applications (Maas, 1988;Coyne et al., 2009).

Conclusions
Reduced tillage delayed corn canopy formation and AGB accumulation during early-to mid-vegetative growth, relative to conventional tillage management, in three of four growing seasons. Delayed canopy senescence was also detected in the same three growing seasons. Greater grain yield and crop water use was associated with this shift in canopy formation. Two forms of the logistic equation provide opportunities to functionally represent tillage effects on corn canopy formation and for use in remote sensing/GIS applications.