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Soil Science

IGC Proceedings (1997-2023)

2022

Model

Articles 1 - 5 of 5

Full-Text Articles in Physical Sciences and Mathematics

Estimating Nitrogen Fixation By Pastures On A Regional Or Continental Scale, Murray Unkovich Nov 2022

Estimating Nitrogen Fixation By Pastures On A Regional Or Continental Scale, Murray Unkovich

IGC Proceedings (1997-2023)

With fertiliser N inputs dramatically increasing in Australia in recent years (Angus, 2001), regional and continental scale estimates of biological nitrogen fixation (BNF) are now required for assessing the risks of terrestrial and surface water eutrophication, groundwater contamination, and gaseous N emissions.


Predicting Forage Intake By Sheep Through The Pampa Corte Model Or Nrc, C. A. Pozo, Gilberto V. Kozloski, H. M. N. Ribeiro Filho, J. F. Tourrand, Vicente Celestino Pires Silveira Feb 2022

Predicting Forage Intake By Sheep Through The Pampa Corte Model Or Nrc, C. A. Pozo, Gilberto V. Kozloski, H. M. N. Ribeiro Filho, J. F. Tourrand, Vicente Celestino Pires Silveira

IGC Proceedings (1997-2023)

The aim of the present study was to evaluate the precision and accuracy of the Pampa Corte and National Research Council (2007; NRC) models for predicting forage intake (FI) by sheep. Individual data (n = 213) of observed FI, body weight and chemical composition of consumed diet were taken from fifteen indoor digestibility trials conducted with male sheep housed in metabolic cages and fed only forage ad libitum. The diets were composed of tropical grasses, temperate grasses and legumes. Individual observations of FI were averaged by treatment (n = 32) into each experiment which were then compared to FI …


Digestibility Estimates Based On A Grass Growth Model Are Distributed Via Internet To Finnish Farmers, Marketta Rinne, J. Nousiainen, I. Mattila, H. Nikander, P. Huhtanen Jan 2022

Digestibility Estimates Based On A Grass Growth Model Are Distributed Via Internet To Finnish Farmers, Marketta Rinne, J. Nousiainen, I. Mattila, H. Nikander, P. Huhtanen

IGC Proceedings (1997-2023)

Optimising the harvesting time of grass in primary growth is difficult under Finnish climatic conditions, because the digestibility of grass decreases on average by 0.5 percentage units daily. We constructed a model based on cumulative temperature and geographical location which estimates the digestibility of grass. This model is used to produce estimates utilising real time weather information. The estimates are presented as a map, which is revised daily. Farmers have free access to the maps via Internet.


Modelling Grassland Ecosystems, J. H. M. Thornley Jan 2022

Modelling Grassland Ecosystems, J. H. M. Thornley

IGC Proceedings (1997-2023)

In this contribution a view of the promise and difficulties of modelling grassland is given. This is largely centred around work with a grassland ecosystem simulator known as the Hurley Pasture Model.

A brief introduction sets forth possible reasons for building a large ecosystem model, and stresses the importance of modelling objectives. It is suggested that a model is de rigeur for any research programme which aims to take a firm grasp of the complex responses of grassland. Mechanistic models are required to provide the understanding needed for intelligent and flexible management of grassland, whatever the prevailing environmental or economic …


Length And Width To Estimate Dry Mass Of Panicum Maximum Cv. Tanzânia Leaves, L. G. Barioni, P. M. Santos, A. Coldebella, M. Corsi Jan 2022

Length And Width To Estimate Dry Mass Of Panicum Maximum Cv. Tanzânia Leaves, L. G. Barioni, P. M. Santos, A. Coldebella, M. Corsi

IGC Proceedings (1997-2023)

An analysis of the relationship of leaf length (LL) and leaf width (LW) with leaf dry weight (LDW) in Panicum maximum was carried out with the objective of improving estimations of tissue flow in that plant. Data was collected in a mob grazing experiment with 28 days grazing interval sampled the day before grazing in 9 grazing cycles. Regression analysis revealed highly significant effect (P < 0.001) of both LL and LW on LDW. A lack of fit test gave strong evidence of non-linear relationship of LDW with LL (p < 0.05), fitting the model 1 0 LDW = β0LLβ1 , while LW presented a linear relation with LDW. LL was a better predictor of LDW than LW. LL solely or in combination with LW produced equations with …