Relationship Between Percentage Emergence and Growing Degree Days for Corn

Hayhoe, H. N.; Dwyer, L. M.

doi:10.4141/cjss90-048

Cited by 12 publications

(5 citation statements)

References 2 publications

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“…Growth stages for crops are defined as total degree days needed to reach the beginning of each developmental phase (e.g., Cutforth and Shaykewich, 1989; Carlson and Gage, 1989; Hayhoe and Dwyer, 1990). All GDD summations are relative to the crop planting date.…”

Section: Appendixmentioning

confidence: 99%

Integrated BIosphere Simulator (IBIS) Yield and Nitrate Loss Predictions for Wisconsin Maize Receiving Varied Amounts of Nitrogen Fertilizer

2003

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Agriculture in the U.S. Midwest faces the formidable challenge of improving crop productivity while simultaneously mitigating the environmental consequences of intense management. This study examined the simultaneous response of nitrate nitrogen (NO3-N) leaching losses and maize (Zea mays L.) yield to varied fertilizer N management using field observations and the Integrated BIosphere Simulator (IBIS) model. The model was validated against six years of field observations in chisel-plowed maize plots receiving an optimal (180 kg N ha(-1)) fertilizer N application and in N-unfertilized plots on a silt loam soil near Arlington, Wisconsin. Predicted values of grain yield, harvest index, plant N uptake, residue C to N ratio, leaf area index (LAI), grain N, and drainage were within 20% of observations. However, simulated NO3-N leaching losses, NO3-N concentrations, and net N mineralization exhibited less interannual variability than observations, and had higher levels of error (20-65%). Potential effects of 30% higher (234 kg N ha(-1)) and 30% lower (126 kg N ha(-1)) fertilizer N use (from optimal) on NO3-N leaching loss and maize yield were simulated. A 30% increase in fertilizer N use increased annual NO3-N leaching by 56%, while yield increased by only 1%. The NO3-N concentration in the leachate solution at 1.4 m below the soil surface was 30.7 mg L(-1). When fertilizer N use was reduced by 30% (from optimal), annual NO3-N leaching losses declined by 42% after seven years, and annual average yield only decreased by 8%. However, NO3-N concentration in the leachate solution remained above 10 mg L(-1) (11.3 mg L(-1)). Clearly, nonlinear relationships existed between changes in fertilizer use and NO3-N leaching losses over time. Simulated changes in NO3-N leaching were greater in magnitude than fertilizer N use changes.

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Section: Appendixmentioning

confidence: 99%

Integrated BIosphere Simulator (IBIS) Yield and Nitrate Loss Predictions for Wisconsin Maize Receiving Varied Amounts of Nitrogen Fertilizer

2003

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“…The reported values of GDD for T50% from the previous studies for a 10 • C T base are 58 [1], 58.56 [14], 69 [38], 80 [39], 58 [10], 69 GDD [7] (Table 1). Based on this, an average value of 65 GDD with a 10 • C T base is considered as the GDD model from the literature.…”

Section: Comparison Of the Developed Models With The Existing Gdd-bas...mentioning

confidence: 95%

“…At lower temperatures, the seeds absorb water but do not initiate root or shoot growth, which leads to seed rot and poor emergence [12]. The optimum temperature for corn seedling emergence is observed to be between 20 and 30 • C, as reported in several studies [10,[13][14][15]. Early planting is sometimes adopted for corn to avoid excessive heat/drought that may impact grain production during its reproductive phase [12,16,17].…”

Section: Introductionmentioning

confidence: 99%

Examining the Corn Seedling Emergence–Temperature Relationship for Recent Hybrids: Insights from Experimental Studies

Beegum,

Walne,

Reddy

et al. 2023

Plants

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Corn seedling emergence is a critical factor affecting crop yields. Accurately predicting emergence is crucial for precise crop growth and development simulation in process-based crop models. While various experimental studies have investigated the relationship between corn seedling emergence and temperature, there remains a scarcity of studies focused on newer corn hybrids. In the present study, statistical models (linear and quadratic functional relationships) are developed based on the seedling emergence of ten current corn hybrids, considering soil and air temperatures as influencing factors. The data used for model development are obtained from controlled soil plant atmospheric research chamber experiments focused on corn seedling emergence at five different temperatures. Upon evaluating the developed models, the quadratic model relating the air temperature with time to emergence was found more accurate for all corn hybrids (coefficient of determination (R2): 0.97, root mean square error (RMSE): 0.42 day) followed by the quadratic model based on soil temperature (R2: 0.96, RMSE: 1.42 days), linear model based on air (R2: 0.94, RMSE: 0.53 day) and soil temperature (R2: 0.94, RMSE: 0.70 day). A growing degree day (GDD)-based model was also developed for the newer hybrids. When comparing the developed GDD-based model with the existing GDD models (based on old hybrids), it was observed that the GDD required for emergence was 16% higher than the GDD used in the current models. This showed that the existing GDD-based models need to be revisited when adopted for newer hybrids and adapted to corn crop simulation models. The developed seedling emergence model, integrated into a process-based corn crop simulation model, can benefit farmers and researchers in corn crop management. It can aid in optimizing planting schedules, supporting management decisions, and predicting corn crop growth, development, and it yields more accurately.

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“…19 The FE model allows us to address endogeneity due to time-invariant 17 Use of degree days, especially DD10, rather than temperature variables per se, is reasonable given that prolonged exposure to cold temperatures naturally influences soil temperature at a particular time (e.g., in the planting window). Low soil temperatures can then adversely influence emergence and eventual yields of the cash crops (Hayhoe & Dwyer, 1990;Nemergut et al, 2021). Hence, exposure to cold would likely be more appropriate than average air temperatures over a 2-month planting window (which can mask exposures to cold temperature at planting).…”

Section: Empirical Specification and Estimation Strategiesmentioning

confidence: 99%

Understanding the effect of cover crop use on prevented planting losses

Won

Rejesus

Goodwin

et al. 2023

American J Agri Economics

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Cover cropping has the potential to improve resilience of agriculture to climate‐change‐induced extreme weather events. However, rigorous quantitative evidence on the resilience effect of cover crops is still lacking. Using a novel data set that combines satellite‐based cover crop information and county‐level crop insurance data, we examine the impact of planting cover crops on prevented‐planting‐related losses that are typically caused by heavy rainfall events. The US federal crop insurance program offers “prevented planting” coverage, which pays indemnities if insured growers are unable to plant their crop due to adverse weather. Linear fixed effects models, instrument‐based estimation methods, long‐difference models, and a number of other robustness checks are utilized in the empirical analysis to achieve the study objective. Our findings suggest that counties with higher cover crop adoption rates tend to have lower levels of crop insurance losses due to prevented planting. The resulting reduction in prevented planting risk also becomes larger with longer term, multiyear cover crop use. These results support the notion that cover crops improve soil conditions such that the likelihood and magnitude of prevented planting losses decrease. We posit that the ability of cover crops to handle excess moisture (i.e., through better water absorption and improved water infiltration in the soil) is the main factor in its ability to reduce prevented planting losses in the US Midwest.

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Relationship Between Percentage Emergence and Growing Degree Days for Corn

Cited by 12 publications

References 2 publications

Integrated BIosphere Simulator (IBIS) Yield and Nitrate Loss Predictions for Wisconsin Maize Receiving Varied Amounts of Nitrogen Fertilizer

Integrated BIosphere Simulator (IBIS) Yield and Nitrate Loss Predictions for Wisconsin Maize Receiving Varied Amounts of Nitrogen Fertilizer

Examining the Corn Seedling Emergence–Temperature Relationship for Recent Hybrids: Insights from Experimental Studies

Understanding the effect of cover crop use on prevented planting losses

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