Long-term performance of white clover varieties grown with perennial ryegrass under rotational grazing by sheep with different nitrogen applications

Williams, Tom A.; Evans, David R.; Rhodes, I.; Abberton, Michael T.

doi:10.1017/s0021859603002958

Cited by 19 publications

(19 citation statements)

References 11 publications

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“…Harris et al (1999) reported that deferred grazing of pasture increased clover proportion in pasture in subsequent seasons. Williams et al (2003b) reported that under rotational stocking with sheep, white clover can give reliably high yield over a 10-yr period. Brink and Pederson (1993) made several important observations on white clover response to grazing method.…”

Section: Growth and Persistencementioning

confidence: 99%

A Novel Approach to Grass–Legume Management

et al. 2011

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Section: Growth and Persistencementioning

confidence: 99%

A Novel Approach to Grass–Legume Management

et al. 2011

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“…Nitrogen fertilization, which tends to enhance both total forage yield and grass competitive ability, may have a major impact on white clover–grass dynamics. Fertilization rates of c .100 kg ha −1 per year allow for a compromise between high forage yield and allowing sufficient clover content in white clover–perennial ryegrass mixtures in the UK (Frame and Boyd, 1987; Williams et al. , 2003) and in New Zealand (Clark and Harris, 1996).…”

Section: Introductionmentioning

confidence: 99%

Optimizing legume content and forage yield of mown white clover–Italian ryegrass mixtures through nitrogen fertilization and grass row spacing

Annicchiarico

Tomasoni

2010

Grass and Forage Science

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Mixed swards of white clover-grass mixtures in highly productive environments often fail to reach the minimum recommended annual clover proportion of about 0AE30. This study assessed the effect on clover content and total dry matter (DM) yield of two spring N applications (0 and 45 kg N ha )1 ) and two distances between drilled grass-rows (0AE18 and 0AE36 m) over 3 years for mown swards of white clover-Italian ryegrass (Trifolium repens-Lolium multiflorum) in binary mixtures in northern Italy. An additional aim was to determine the advantage of association of grass-clover compared with grass and clover monocultures. On average, N fertilization of mixtures resulted in almost 9% higher total yield (P < 0AE01; mean response = 18AE1 kg of total DM per kg of N) but decreased the clover proportion (0AE250 vs. 0AE312). Wider grass-row spacing increased clover proportion (0AE327 vs. 0AE234; P < 0AE01) with no reduction of total DM yield. N fertilization · grass-row spacing interaction occurred only for clover content (P < 0AE01). Without N fertilization, mixtures out-yielded clover and grass pure stands. With N fertilization, at double rate to pure grass, yields from mixtures were greater than from clover and comparable to Italian ryegrass.

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“…Only a limited number of results from long‐term experiments have been published (e.g. Williams et al. , 2003), but in most cases their relevance has been restricted to a specific management system.…”

Section: Introductionmentioning

confidence: 99%

A simple statistical model for predicting herbage production from permanent grassland

Trnka¹,

Eitzinger²,

Gruszczynski³

et al. 2006

Grass and Forage Science

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The considerable year-to-year and seasonal variation in grassland production is of major importance to dairy farmers in Europe, as production systems must allow for the risk of unfavourable weather conditions. A large portion of the variability is caused by weather and its interaction with soil conditions and grassland management. The present study takes advantage of the interactions between weather, soil conditions and grassland management to derive a reliable grassland statistical model (GRAM) for grasslands under various management regimes using polynomial regressions (GRAM-R) and neural networks (GRAM-N). The model performance was tested with a focus on predicting its capability during unusually dry or wet years using long-term experimental data from Austrian sites. The GRAM model was then coupled with the Met&Roll stochastic weather generator to provide estimates of harvestable herbage dry matter (DM) production early in the season. It was found that, with the GRAM-N or GRAM-R methodology, up to 0AE78 of the variability in harvested herbage DM production could be explained with a systematic bias of 1AE1-2AE3%. The models showed stable performance over subsets of dry and wet years. Generalized GRAM models were also successfully used to estimate daily herbage growth during the season, explaining between 0AE63 and 0AE91 of variability in individual cases. It was possible to issue a probabilistic forecast of the harvestable herbage DM production early in the season with reasonable accuracy. The overall results showed that the GRAM model could be used instead of (or in parallel with) more sophisticated grassland models in areas or sites where complete data sets are not yet available. As the model was tested under various climatic and soil conditions, it is suggested that the proposed approach could be used for comparable temperate grassland sites throughout Europe.

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Long-term performance of white clover varieties grown with perennial ryegrass under rotational grazing by sheep with different nitrogen applications

Cited by 19 publications

References 11 publications

A Novel Approach to Grass–Legume Management

A Novel Approach to Grass–Legume Management

Optimizing legume content and forage yield of mown white clover–Italian ryegrass mixtures through nitrogen fertilization and grass row spacing

A simple statistical model for predicting herbage production from permanent grassland

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