Evaluation of the PNM Model for Simulating Drain Flow Nitrate-N Concentration Under Manure-Fertilized Maize

Sogbedji, Jean Mianikpo; Es, Harold M. van; Melkonian, Jeff; Schindelbeck, Robert R.

doi:10.1007/s11104-006-0006-3

Cited by 29 publications

(32 citation statements)

References 54 publications

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“…Adapt-N's underlying soil model, LEACHN, has been extensively tested Jemison et al, 1994;Sogbedji et al, 2001aSogbedji et al, , 2006. The crop subroutines were developed as reported in Muchow and Sinclair (1991), Muchow et al (1990), Sinclair and Amir (1992), and equations and validation are presented in Sinclair and Muchow (1995).…”

Section: Adapt-nmentioning

confidence: 99%

“…The crop subroutines were developed as reported in Muchow and Sinclair (1991), Muchow et al (1990), Sinclair and Amir (1992), and equations and validation are presented in Sinclair and Muchow (1995). The combined PNM model was tested by Sogbedji et al (2006) and and showed low prediction errors. Graham et al (2010) applied the model to generate within-field site-specific N recommendations.…”

Section: Adapt-nmentioning

confidence: 99%

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

et al. 2018

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A gronomy J our n al • Volume 110 , I ssue 1 • 2 018 1 T he goal of an N recommendation system is to accurately estimate the gap between the N provided by the soil and the N required by the plant. Accurately estimating this gap depends on the ability of the recommendation system to accurately estimate fi eld or subfi eld specifi c economically optimal nitrogen rates (EONR). Current recommendation systems are not as accurate as needed to provide consistently reliable estimates of N needs across years at the fi eld or subfi eld scale. Uncontrollable factors like temperature, rainfall timing, intensity and amount, and interactions of temperature and rainfall with factors such as N source, timing and placement, plant genetics, and soil characteristics combine to make N rate recommendations for an individual fi eld or rates for subfi elds a process guided as much by science as by the best professional judgement of farmers and farm advisors.Substantial evidence has accumulated that EONRs can vary widely across fi elds, within fi elds and over years in the same fi eld for a wide range of crops and geographies. Examples ABSTRACTNitrogen fi xation by the Haber-Bosch process has more than doubled the amount of fi xed N on Earth, signifi cantly infl uencing the global N cycle. Much of this fi xed N is made into N fertilizer that is used to produce nearly half of the world's food. Too much of the N fertilizer pollutes air and water when it is lost from agroecosystems through volatilization, denitrifi cation, leaching, and runoff . Most of the N fertilizer used in the United States is applied to corn (Zea mays L.), and the profi tability and environmental footprint of corn production is directly tied to N fertilizer applications. Accurately predicting the amount of N needed by corn, however, has proven to be challenging because of the eff ects of rainfall, temperature, and interactions with soil properties on the N cycle. For this reason, improving N recommendations is critical for profi table corn production and for reducing N losses to the environment. Th e objectives of this paper were to review current methods for estimating N needs of corn by: (i) reviewing fundamental background information about how N recommendations are created; (ii) evaluating the performance, strengths, and limitations of systems and tools used for making N fertilizer recommendations; (iii) discussing how adaptive management principles and methods can improve recommendations; and (iv) providing a framework for improving N fertilizer rate recommendations.

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Section: Adapt-nmentioning

confidence: 99%

Section: Adapt-nmentioning

confidence: 99%

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

et al. 2018

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“…In some areas of Africa, vegetable cropping systems such as maize and cowpea often are practiced (Mead and Willey, 1980). Some factors that will influence or not whether two crops can be successfully intercropped include plant height (Spiejer et al 2006), the size of the leaves and the orientation and distribution of these leaves in the plant canopy (Sogbedji et al 2006). These variables affect the amount of sunlight that passes through the canopies (Grossman and Quales, 1993), which could influence the photosynthetic rates of the leaves within the canopy.…”

Section: Vegetable Cropsmentioning

confidence: 99%

“…These variables affect the amount of sunlight that passes through the canopies (Grossman and Quales, 1993), which could influence the photosynthetic rates of the leaves within the canopy. In intercropping systems with different canopy heights the crop in the under story needs to be shade tolerant for the plant to be productive (Sogbedji et al, 2006).…”

Section: Vegetable Cropsmentioning

confidence: 99%

Sustainable horticultural crop production through intercropping: The case of fruits and vegetable crops: A review

Ouma¹,

Jeruto²

2010

ABJNA

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Sustainable agriculture seeks to at least use nature as the model for designing agricultural systems. Since nature integrates her plants and animals into diverse landscape, a major tenet of sustainable agriculture is efficiency and lack of waste products in nature. When domestication of crops replaced hunting and gathering of food, landscape changed accordingly. By producing a limited selection of crop plants and animals, human kind has substantially reduced the level of biological diversity over much of the earth. There is more cooperation in nature than competition. Cooperation is exemplified by mutually beneficial relationships that occur between species within communities. If left undistributed and unplanted an abandoned crop field will first be colonized by just a few species of organisms but after several years a complex community made up of many wild species develops. Stability is reached by a community when it has reached a high level of diversity. Diverse communities have fewer fluctuations in numbers of a given species and are stable. The practices which promote diversity and stability on the farm are enterprise diversification, crop rotation, use of wind breaks, provision of more habitats for microorganisms, intercropping and integration of crop farming with livestock production. Intercropping is the cultivation of two or more crops at the same time in the same field. Its advantages are risk minimization, increased income and food security, reduction of soil erosion and pest and disease control. This paper discusses the practice of intercropping in horticultural crop production to promote sustainability. Many crop systems are discussed.

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“…Data required by the PNM model to simulate crop residue mineralization include the total C (kg C ha -1 ) and total N (kg N ha -1 ) of the residue at termination. The C in the residue is mineralized using a first order rate equation and rate constants based on PNM model calibration studies (Sogbedji et al, 2006;Marjerison et al, 2016). Residue N is either released to the soil (net mineralization) or temporarily immobilized depending primarily on the residue C/N ratio.…”

Section: Estimating Nitrogen Mineralization From Cover Crop Mixturesmentioning

confidence: 99%

Estimating Nitrogen Mineralization from Cover Crop Mixtures Using the Precision Nitrogen Management Model

Melkonian

Poffenbarger

Mirsky³

et al. 2017

Agronomy Journal

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A gronomy J our n al • Volume 10 9, I ssue 5 • 2 017 C over crops can serve multiple beneficial functions in cropping systems including improving soil aggregate stability and infiltration, reducing soil erosion, weed suppression, and managing N (Snapp et al., 2005). The dual roles of cover crops for N management in cropping systems, both as a scavenger of excess soil N following a cash crop (often maize), and as a potential source of crop-available N to the subsequent main crop following cover crop termination in the spring, have been reported on extensively (ThorupKristensen et al., 2003). Kladivko et al. (2014) reported that, if wide spread adoption of cover crops (primarily cereal rye, Secale cereale L.) occurred in the central U.S. Corn Belt, nitrate N (NO 3 -N) loading to the Mississippi River could be reduced by approximately 20%. Despite the potentially beneficial functions of cover crops, they are used on less than 1% of cropland in the United States (Wallander, 2013). Increased costs and only minimal yield benefits with cover crops reported by farmers are among the top factors that limit their adoption (Werblow, 2015). Estimating the N contribution of cover crops to a cash crop following cover crop termination can potentially improve N management of cropping systems, increase profits and reduce N losses to the environment. The potential of cover crops to improve N management where maize is the main crop has been of particular interest because of the high N losses and relatively low N use efficiency (<40%) of maize production systems (Cassman et al., 2002).The N content, C/N ratio, chemical composition, winter hardiness, and biomass accumulation of a cover crop or cover crop mixture are important determinants of cover crop residue decomposition and N availability to the subsequent main crop due to this decomposition (Vigil et al., 1991; ThorupKristensen and Dresbøll, 2010;Weinert et al., 2002;Cabrera et al., 2005 ABSTRACTCover crops influence soil N dynamics and N availability to a subsequent crop. Dynamic simulation models, if properly calibrated and tested, can simulate C and N dynamics of a terminated cover crop and estimate crop-available N over diverse production environments. We calibrated and tested a dynamic simulation model modified to simulate C and N cover crop residue dynamics in maize (Zea mays L.) production systems. Data from a 2-yr field study of different cover crop residue mixtures, fertilizer rates, and tillage practices were used in model calibration and testing. First order rate constants governing cover crop residue decomposition were calibrated so that statistical measures of model best fit were optimized. Calibration resulted in a good fit between measured and modeled N release from the terminated cover crop mixtures (root mean square error [RMSE] = 14 kg N ha -1 ; Willmott's index of agreement (IA) = 0.92). The calibrated model performed reasonably well in the testing phase (RMSE = 25; IA = 0.88) with significantly better performance for the no-till (NT) treatments compared to t...

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Evaluation of the PNM Model for Simulating Drain Flow Nitrate-N Concentration Under Manure-Fertilized Maize

Cited by 29 publications

References 54 publications

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

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

Sustainable horticultural crop production through intercropping: The case of fruits and vegetable crops: A review

Estimating Nitrogen Mineralization from Cover Crop Mixtures Using the Precision Nitrogen Management Model

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