An on-farm evaluation of the capability of saline land for livestock production in southern Australia
Bibliographic record
Abstract
Grazing livestock on revegetated saline land is one of few profitable options to continue using this class of agricultural land. However, there has been little research conducted to assess the capability of saline land to support livestock production based on the soil and water characteristics at a particular site. In this study, data from 11 grazing studies collected from eight commercial farms across southern Australia were used to estimate metabolisable energy (ME) utilised/ha, as well as total ME produced/ha. All data were from the autumn (March–May) period, when feed is normally in short supply and of limited quality. Site characteristics indicative of the severity of salinisation varied across the sites. Topsoil electrical conductivity (ECe) ranged from 1 to 33 dS/m and groundwater EC from 14 to 60 dS/m (equivalent to sea water). Feed on offer before grazing varied from 700 kg dry matter/ha to 9000 kg dry matter/ha between sites. Thinopyrum ponticum and Puccinellia ciliata featured prominently in the less saline revegetated sites, with Atriplex spp. present on the more saline sites and some lucerne and rhodes grass on the less saline, well drained sites. Grazing days per ha for sheep (ME-adjusted dry sheep equivalent) on autumn pastures across the sites ranged from 41 to 3600, and liveweight gains ranged from –95 to 314 g/sheep.day. The grazing value of the highest producing saltland was at least as high as that expected on adjacent areas that were not salt affected. The major advantage of establishing saltland pastures included an out-of-season feed supply high in crude protein and micronutrients that possessed the ability to capture summer and autumn rain. This should represent a substantial reduction in supplementary feed costs and increases the flexibility of methods for feeding livestock through periods of low annual pasture availability. The value of the ME produced on the highest yielding saltland pasture was estimated to be $360/ha based on substituting the best alternative strategy of purchasing lupin grain as a supplement. A quadratic relationship (R2 = 0.62, P = 0.024) was found between soil ECe and ME produced across the sites. Significant relationships were not found between other saline site characteristics and ME production, which partly reflects the complexity of these systems as well as limitations with site characterisation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".