Dry Matter Production and Light Interception of Crop Surfaces

Alberda, Th.; Sibma, L.

doi:10.1111/j.1365-2494.1968.tb00576.x

Cited by 45 publications

(28 citation statements)

References 6 publications

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“…Whether this actually influences response depends on the degree of stimulation of growth by N application required to increase yield in either physiological state to a ceiling yield. The DM yields observed in the present experiment were still increasing at each harvest and did not approach the 600-1400 g m* levels of ceiling yield quoted by Alberda and Sibma (1968) and Leafe et al (1974).…”

Section: Methodscontrasting

confidence: 36%

The influence of vernalization on response to nitrogen of perennial ryegrass

Bartholomew¹,

Chestnutt²

1978

Grass and Forage Science

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Vernalized and unvernalized perennial ryegrass (Lolium perenne cv. Gremie) tillers planted in microplots in a glasshouse in April 1974 and 1975 were exposed to natural daylength thus inducing vernalized plants to produce reproductive, and unvernalized plants vegetative growth. Nitrogen was applied at 0-30 g m"^ (to 24 g m-' in 1975) to both types of herbage. At the first defoliation in each year yields from vernalized grass were greater than those from unvernalized grass; subsequently differences were minimal or reversed. Vernalization had no significant effect (P>0 05) on total yields over four defoliations in either year.Apart from the first cut in 1974 nitrogen application increased dry matter yields of both types of herbage. Tiller numbers were usually increased by the lowest level of nitrogen application but at higher levels the effect was variable.There was no evidence of an interaction effect of level of nitrogen application and vernalization on dry matter yields.

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Section: Methodscontrasting

confidence: 36%

The influence of vernalization on response to nitrogen of perennial ryegrass

Bartholomew¹,

Chestnutt²

1978

Grass and Forage Science

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“…The thermal time is measured as the product of daily mean air temperature (°C) and time in days. Perennial ryegrass (Loliumperenne l.), the focus of this research, generally has a maximum of three live leaves per tiller, with the oldest leaf (first to emerge) beginning to senesce as the fourth leaf emerges (Alberda & Sibma 1968).…”

Section: New Senescence Functionmentioning

confidence: 99%

Improving the McCall herbage growth model

Romera

McCall

Lee

et al. 2009

New Zealand Journal of Agricultural Research

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The objective of this study was to improve the McCall herbage growth model. A more mechanistic senescence function was incorporated, replacing an empirical senescence function. The new function is based on leaf lifespan (LLS), measured in thermal time, which is characteristic of a given grass species, and can be measured independently or sourced from the literature. Other complementary changes were also incorporated, the major ones being to incorporate soil water infiltration constraints and to improve seasonal predictions in winter based on greater photosynthetic efficiency of leaves at low light intensity. The existing and new versions of the model were each calibrated against five time series of herbage growth data using the first half of each time series. The second half of each time series was used for validation, along with an independent dataset. respectively). Most goodness-of-fit indicators also improved for the independent dataset (e.g. ρ c = 0.708 versus 0.787, for existing and new versions, respectively). It is concluded that the new improved version of the model can be confidently used as a replacement for the existing version.

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“…In some cases that objective has been attained consistently and well, in others, accuracy is poor. The estimates of gross photosynthesis provided by ecosystem-level models, when corrected for respiration, provide good predictions of primary productivity (1,24). Economic yields can be derived from that using generalized partitioning factors, and our best current estimates of global food production under various agricultural strategies have been obtained in that way (13).…”

Section: Productivity and Bioclimatologymentioning

confidence: 99%