Environmental influences on optimum nitrogen fertiliser rates for temperate dairy pastures

Pembleton, KG; Rawnsley, RP; Burkitt, LL

doi:10.1016/j.eja.2012.09.006

Cited by 22 publications

(20 citation statements)

References 47 publications

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“…Permanent pastures are the main source of food for cattle in temperate regions of the World, being the lowest-cost food for grazing animals (Pembletona et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Seasonal variation of the productivity and quality of permanent pastures in Adisols of temperate regions

Demanet

Mora

Herrera

et al. 2015

J. Soil Sci. Plant Nutr.

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With the aim of evaluating the productivity (dry matter yield) and quality (protein and fiber) of pastures in temperate regions of Chile a long-term monitoring experiment was carried out in a representative farm in these regions. The study was carried during the years 2002 -2012 in a farm located at Region of Los Ríos, Chile. The study area was split into fifteen pasture sites, which were evaluated dry matter production by means of the standardized methodology, which considers the location on each pasture site a grazing exclusion cage. With the information generated during the 11 years of measurements, a trend pattern interpolation was developed by a polynomial regression model using fifth grade and centering the independent variable from the second grade on. Each result was classified according to the ranking provided by the BLUP methodology, comparing the results obtained with the average. The analysis of variance mixed model, determined by the variance components, indicated that 60% of the total variation in dry matter production is attributed to seasonality. Only 2.6% of the variation was attributable to the year while a 0.9% was due to differences between pastures sites, during the eleven years of study, with no significant data (p> 0.05). The seasonal distribution of production, concentrated its performance in spring and highest performing months were November, December, January. The quality measured as protein and fiber content of the pasture, does not present statistical differences between years and only differences were determined by seasonality.

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“…Permanent pastures are the main source of food for cattle in temperate regions of the World, being the lowest-cost food for grazing animals (Pembletona et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Seasonal variation of the productivity and quality of permanent pastures in Adisols of temperate regions

Demanet

Mora

Herrera

et al. 2015

J. Soil Sci. Plant Nutr.

View full text Add to dashboard Cite

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“…In New Zealand, as in Australia, pasture‐based dairy farms employ an intensively managed rotational stocking system throughout the year (Pembleton et al ., ). These highly productive pastures require a regular supply of mineral nitrogen (N) to replace the N removed through consumption and the export of animal products (e.g.…”

Section: Introductionmentioning

confidence: 97%

“…The intensification of farming systems in the last 20 years, with increased stocking rates, has been driven by in an increased use of N fertilizers (Clark et al ., ). Information on N fertilizer requirements for optimum pasture growth is, however, lacking (Pembleton et al ., ). Early estimates of N requirements are desirable to ensure fertilizers can be applied at the right time to supply adequate N for targeted pasture growth.…”

Section: Introductionmentioning

confidence: 97%

Deriving seasonally optimal nitrogen fertilization rates for a ryegrass pasture based on agricultural production systems simulator modelling with a refined AgPasture model

Vogeler

Cichota

2015

Grass and Forage Science

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Productive pasture systems require a regular supply of mineral nitrogen (N) to replace the N removed through the export of animal products and other loss pathways such as leaching and emissions. High spatial and temporal variability of both N supply by the soil and demand by the plant means that synchronizing these is challenging, and early indicators are lacking. Optimum fertilization rates for an irrigated ryegrass pasture in Canterbury, New Zealand, were determined in a simulation study with twenty fertilization rates using the Agricultural Production Systems Simulator with a refined version of APSIM's pasture module (AgPasture). Improvements in AgPasture included ideal N concentrations for tissues of different ages (growing, mature, senescent and dead) and allowing N remobilization to occur from all tissue stages. The critical N concentration curve (the minimum N concentration required to achieve maximum aerial biomass) was tested as an early indicator for guiding N fertilization, which maximizes plant growth while avoiding unnecessary environmental impacts. Highest pasture yields were achieved with application rates of 20, 30, 140 and 160 kg N ha−1 for winter, autumn, summer and spring. These rates also minimized simulated N losses. Pasture N contents corresponding to the standing dry matter of the pastures were similar to the critical N curve in summer and spring, but lower critical N concentrations were obtained for autumn and winter. Before the critical N reference curve can be used to guide fertilization for pastures, further experimental studies, model testing and parameterization are required. It is also possible that season‐specific critical N curves need to be established for pastures.

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“…In New Zealand and Australia, pasture‐based dairy farms typically employ an intensively managed rotational grazing system throughout the year (Pembleton, Rawnsley, & Burkitt, ), which predominantly rely on home‐grown feed. The relatively low costs of these systems can provide a cost advantage over dairy industries in the Northern Hemisphere, which rely more on purchased feed (Bell, Hayes, Pembleton, & Waters, ).…”

Section: Introductionmentioning

confidence: 99%

“…For example, Pembleton et al. () found coefficients of variation (CV) in total available soil N ranging between 10% and 45% in pastures in Australia, and Bogaert et al. () observed CVs within individual grazed fields of up to 81%.…”

Section: Introductionmentioning

confidence: 99%

Development of an algorithm for relating pasture nitrogen status to yield response curves

Vogeler

Cichota

2017

Grass and Forage Science

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Determination of optimum nitrogen (N) fertilization rates which maximize pasture growth is challenging due to variability in plant requirements and likely near‐future supply of N by the soil. Remote sensing can be used for mapping N nutrition status of plants and to rapidly assess the spatial variability within a field. An algorithm is, however, lacking which relates the N status of the plants to the expected yield response to additions of N. An algorithm was developed based on a simulation study carried out using the APSIM model. Simulations were performed for an irrigated ryegrass pasture in Canterbury, New Zealand. Nitrogen fertilizer was applied monthly at different rates, ranging from 0 to 150 kg N/ha. To obtain a range of different pasture N contents, a total of 1456 different fertilization rules were set up and evaluated over 20 different years of weather giving 29,120 combinations of pasture herbage N contents and growth responses for each month. The analysis focused on November (spring), a month with generally vigorous growth. A three‐dimensional surface response function, based on the Mitscherlich yield response function, was developed. This function was used to determine required N fertilization rates, which achieve 90% of the maximum yield, based on the antecedent pasture N content. At low pasture herbage N contents (25 g/kg), the required fertilization rate was estimated as 130 kg N/ha, whereas at N contents of 40 g/kg, only 60 kg N/ha was required to obtain the same yield, reflecting the much higher supply of N by the soil.

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Environmental influences on optimum nitrogen fertiliser rates for temperate dairy pastures

Cited by 22 publications

References 47 publications

Seasonal variation of the productivity and quality of permanent pastures in Adisols of temperate regions

Seasonal variation of the productivity and quality of permanent pastures in Adisols of temperate regions

Deriving seasonally optimal nitrogen fertilization rates for a ryegrass pasture based on agricultural production systems simulator modelling with a refined AgPasture model

Development of an algorithm for relating pasture nitrogen status to yield response curves

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