Regrouping unfamiliar animals in the weeks prior to slaughter has few effects on physiology and meat quality in Bos taurus feedlot steers

The response of cattle to alterations in social groupings can lead to physiological changes that affect meat quality. Feedlot practices frequently lead to a proportion of cattle in a pen being drafted for slaughter with the balance retained for a further period until they meet market specifications. An ability to regroup such retained cattle for short periods without consequences for meat quality would facilitate efficient use of feedlot pen space. The current experiment examined the impact on physiological variables and meat quality of regrouped British breed steers 4, 2 or 1 week before dispatch for slaughter. There was little effect of regrouping cattle on physiological variables associated with stress responses. Physical assessment of meat quality indicated that regrouping steers 1 week before slaughter led to higher compression and a tendency for higher peak force values in animals from one genotype than in their respective controls (1.89 v. 1.71 ± 0.05 kg, P = 0.017); however, these assessments were not matched by changes in sensory perception of meat quality. Average daily gain during feedlot finishing was negatively related to the temperament measure and flight time. It was also associated with breed, white cell count, plasma cortisol and haemoglobin at the midpoint of the 70-day finishing period. The results confirm the impact of flight time on growth rate during feedlot finishing and that regrouping cattle less than 2 weeks before slaughter may reduce meat quality.

Simulating the effects of saline and sodic subsoils on wheat crops growing on Vertosols

Soils with high levels of chloride and/or sodium in their subsurface layers are often referred to as having subsoil constraints (SSCs). There is growing evidence that SSCs affect wheat yields by increasing the lower limit of a crop's available soil water (CLL) and thus reducing the soil's plant-available water capacity (PAWC). This proposal was tested by simulation of 33 farmers' paddocks in south-western Queensland and north-western New South Wales. The simulated results accounted for 79% of observed variation in grain yield, with a root mean squared deviation (RMSD) of 0.50 t/ha. This result was as close as any achieved from sites without SSCs, thus providing strong support for the proposed mechanism that SSCs affect wheat yields by increasing the CLL and thus reducing the soil's PAWC. In order to reduce the need to measure CLL of every paddock or management zone, two additional approaches to simulating the effects of SSCs were tested. In the first approach the CLL of soils was predicted from the 0.3-0.5 m soil layer, which was taken as the reference CLL of a soil regardless of its level of SSCs, while the CLL values of soil layers below 0.5 m depth were calculated as a function of these soils' 0.3-0.5 m CLL values as well as of soil depth plus one of the SSC indices EC, Cl, ESP, or Na. The best estimates of subsoil CLL values were obtained when the effects of SSCs were described by an ESP-dependent function. In the second approach, depth-dependent CLL values were also derived from the CLL values of the 0.3-0.5 m soil layer. However, instead of using SSC indices to further modify CLL, the default values of the water-extraction coefficient (kl) of each depth layer were modified as a function of the SSC indices. The strength of this approach was evaluated on the basis of correlation of observed and simulated grain yields. In this approach the best estimates were obtained when the default kl values were multiplied by a Cl-determined function. The kl approach was also evaluated with respect to simulated soil moisture at anthesis and at grain maturity. Results using this approach were highly correlated with soil moisture results obtained from simulations based on the measured CLL values. This research provides strong evidence that the effects of SSCs on wheat yields are accounted for by the effects of these constraints on wheat CLL values. The study also produced two satisfactory methods for simulating the effects of SSCs on CLL and on grain yield. While Cl and ESP proved to be effective indices of SSCs, EC was not effective due to the confounding effect of the presence of gypsum in some of these soils. This study provides the tools necessary for investigating the effects of SSCs on wheat crop yields and natural resource management (NRM) issues such as runoff, recharge, and nutrient loss through simulation studies. It also facilitates investigation of suggested agronomic adaptations to SSCs.

Effects of hooking damage and hook type on post-release survival of sand flathead (Platycephalus bassensis)

This study examined post-release survival in sand flathead (Platycephalus bassensis) and whether there were survival benefits from the use of circle hooks over conventional hook patterns. Anatomical hooking location was the major factor contributing to mortality, with an almost 100% survival rate for fish hooked in the lip, mouth or eye (shallow-hooked) compared with around 64% for fish hooked in the throat or gut (deep-hooked). Mortality in deep-hooked fish was generally associated with injuries to vital organs (gills, heart, liver) and survival was significantly lower if bleeding was associated with injury (54% compared with 85% for non-bleeders). Circle hooks resulted in significantly lower deep-hooking rates (1%) compared with conventional hook types (4-9%) and, based on catch rates, were at least as effective as conventional hook patterns. Estimated survival rates for line-caught sand flathead were high, over 99% for circle hooks and between 94 and 97% for conventional hooks. These findings support the efficacy of management strategies based on size and bag limits and the practice of catch-and-release fishing for sand flathead, as well as a potential conservation benefit from the use of circle hooks.

The effects of high stocking rates on milk production from dryland and irrigated Mediterranean pastures

An experiment using herds of similar to 20 cows (farmlets) assessed the effects of high stocking rates on production and profitability of feeding systems based on dryland and irrigated perennial ryegrass-based pastures in a Mediterranean environment in South Australia over 4 years. A target level of milk production of 7000 L/cow.year was set, based on predicted intakes of 2.7 t DM/cow.year as concentrates, pasture intakes from 1.5 to 2.7 t/cow.year and purchased fodder. In years 1 and 2, up to 1.5 t DM/cow.year of purchased fodder was used and in years 3 and 4 the amounts were increased if necessary to enable levels of milk production per cow to be maintained at target levels. Cows in dryland farmlets calved in March to May inclusive and were stocked at 2.5, 2.9, 3.3, 3.6 and 4.1 cows/ha, while those in irrigated farmlets calved in August to October inclusive and were stocked at 4.1, 5.2, 6.3 and 7.4 cows/ha. In the first 2 years, when inputs of purchased fodder were limited, milk production per cow was reduced with higher stocking rates (P < 0.01), but in years 3 and 4 there were no differences. Mean production was 7149 kg/cow.year in years 1 and 2, and 8162 kg/cow.year in years 3 and 4. Production per hectare was very closely related to stocking rate in all years (P < 0.01), increasing from 18 to 34 t milk/ha.year for dryland farmlets (1300 to 2200 kg milk solids/ha) and from 30 to 60 t milk/ha.year for irrigated farmlets (2200 to 4100 kg milk solids/ha). Almost all of these increases were attributed to the increases in grain and purchased fodder inputs associated with the increases in stocking rate. Net pasture accumulation rates and pasture harvest were generally not altered with stocking rate, though as stocking rate increased there was a change to more of the pasture being grazed and less conserved in both dryland and irrigated farmlets. Total pasture harvest averaged similar to 8 and 14 t DM/ha.year for dryland and irrigated pastures, respectively. An exception was at the highest stocking rate under irrigation, where pugging during winter was associated with a 14% reduction in annual pasture growth. There were several indications that these high stocking rates may not be sustainable without substantial changes in management practice. There were large and positive nutrient balances and associated increases in soil mineral content (P < 0.01), especially for phosphorus and nitrate nitrogen, with both stocking rate and succeeding years. Levels under irrigation were considerably higher (up to 90 and 240 mg/kg of soil for nitrate nitrogen and phosphorus, respectively) than under dryland pastures (60 and 140 mg/kg, respectively). Soil organic carbon levels did not change with stocking rate, indicating a high level of utilisation of forage grown. Weed ingress was also high (to 22% DM) in all treatments and especially in heavily stocked irrigated pastures during winter. It was concluded the higher stocking rates used exceeded those that are feasible for Mediterranean pastures in this environment and upper levels of stocking are suggested to be 2.5 cows/ha for dryland pastures and 5.2 cows/ha for irrigated pastures. To sustain these suggested stocking rates will require further development of management practices to avoid large increases in soil minerals and weed invasion of pastures.

Climate change impacts on northern Australian rangeland livestock carrying capacity: a review of issues

Grazing is a major land use in Australia's rangelands. The 'safe' livestock carrying capacity (LCC) required to maintain resource condition is strongly dependent on climate. We reviewed: the approaches for quantifying LCC; current trends in climate and their effect on components of the grazing system; implications of the 'best estimates' of climate change projections for LCC; the agreement and disagreement between the current trends and projections; and the adequacy of current models of forage production in simulating the impact of climate change. We report the results of a sensitivity study of climate change impacts on forage production across the rangelands, and we discuss the more general issues facing grazing enterprises associated with climate change, such as 'known uncertainties' and adaptation responses (e.g. use of climate risk assessment). We found that the method of quantifying LCC from a combination of estimates (simulations) of long-term (>30 years) forage production and successful grazier experience has been well tested across northern Australian rangelands with different climatic regions. This methodology provides a sound base for the assessment of climate change impacts, even though there are many identified gaps in knowledge. The evaluation of current trends indicated substantial differences in the trends of annual rainfall (and simulated forage production) across Australian rangelands with general increases in most of western Australian rangelands ( including northern regions of the Northern Territory) and decreases in eastern Australian rangelands and south-western Western Australia. Some of the projected changes in rainfall and temperature appear small compared with year-to-year variability. Nevertheless, the impacts on rangeland production systems are expected to be important in terms of required managerial and enterprise adaptations. Some important aspects of climate systems science remain unresolved, and we suggest that a risk-averse approach to rangeland management, based on the 'best estimate' projections, in combination with appropriate responses to short-term (1-5 years) climate variability, would reduce the risk of resource degradation. Climate change projections - including changes in rainfall, temperature, carbon dioxide and other climatic variables - if realised, are likely to affect forage and animal production, and ecosystem functioning. The major known uncertainties in quantifying climate change impacts are: (i) carbon dioxide effects on forage production, quality, nutrient cycling and competition between life forms (e.g. grass, shrubs and trees); and (ii) the future role of woody plants including effects of. re, climatic extremes and management for carbon storage. In a simple example of simulating climate change impacts on forage production, we found that increased temperature (3 degrees C) was likely to result in a decrease in forage production for most rangeland locations (e. g. -21% calculated as an unweighted average across 90 locations). The increase in temperature exacerbated or reduced the effects of a 10% decrease/increase in rainfall respectively (-33% or -9%). Estimates of the beneficial effects of increased CO2 (from 350 to 650 ppm) on forage production and water use efficiency indicated enhanced forage production (+26%). The increase was approximately equivalent to the decline in forage production associated with a 3 degrees C temperature increase. The large magnitude of these opposing effects emphasised the importance of the uncertainties in quantifying the impacts of these components of climate change. We anticipate decreases in LCC given that the 'best estimate' of climate change across the rangelands is for a decline (or little change) in rainfall and an increase in temperature. As a consequence, we suggest that public policy have regard for: the implications for livestock enterprises, regional communities, potential resource damage, animal welfare and human distress. However, the capability to quantify these warnings is yet to be developed and this important task remains as a challenge for rangeland and climate systems science.

Row spacing and planting density effects on the growth and yield of sugarcane. 1. Responses in fumigated and non-fumigated soil.

It has been reported that high-density planting of sugarcane can improve cane and sugar yield through promoting rapid canopy closure and increasing radiation interception earlier in crop growth. It is widely known that the control of adverse soil biota through fumigation (removes soil biological constraints and improves soil health) can improve cane and sugar yield. Whether the responses to high-density planting and improved soil health are additive or interactive has important implications for the sugarcane production system. Field experiments established at Bundaberg and Mackay, Queensland, Australia, involved all combinations of 2-row spacings (0.5 and 1.5 m), two planting densities (27 000 and 81 000 two-eyed setts/ha), and two soil fumigation treatments (fumigated and non-fumigated). The Bundaberg experiment had two cultivars (Q124, Q155), was fully irrigated, and harvested 15 months after planting. The Mackay experiment had one cultivar (Q117), was grown under rainfed conditions, and harvested 10 months after planting. High-density planting (81 000 setts/ha in 0.5-m rows) did not produce any more cane or sugar yield at harvest than low-density planting (27 000 setts/ha in 1.5-m rows) regardless of location, crop duration (15 v. 10 months), water supply (irrigated v. rainfed), or soil health (fumigated v. non-fumigated). Conversely, soil fumigation generally increased cane and sugar yields regardless of site, row spacing, and planting density. In the Bundaberg experiment there was a large fumigation x cultivar x density interaction (P<0.01). Cultivar Q155 responded positively to higher planting density in non-fumigated soil but not in fumigated soil, while Q124 showed a negative response to higher planting density in non-fumigated soil but no response in fumigated soil. In the Mackay experiment, Q117 showed a non-significant trend of increasing yield in response to increasing planting density in non-fumigated soil, similar to the Q155 response in non-fumigated soil at Bundaberg. The similarity in yield across the range of row spacings and planting densities within experiments was largely due to compensation between stalk number and stalk weight, particularly when fumigation was used to address soil health. Further, the different cultivars (Q124 and Q155 at Bundaberg and Q117 at Mackay) exhibited differing physiological responses to the fumigation, row spacing, and planting density treatments. These included the rate of tiller initiation and subsequent loss, changes in stalk weight, and propensity to lodging. These responses suggest that there may be potential for selecting cultivars suited to different planting configurations.

Row spacing and planting density effects on the growth and yield of sugarcane. 3. Responses with different cultivars.

The promotion of controlled traffic (matching wheel and row spacing) in the Australian sugar industry is necessitating a widening of row spacing beyond the standard 1.5 m. As all cultivars grown in the Australian industry have been selected under the standard row spacing there are concerns that at least some cultivars may not be suitable for wider rows. To address this issue, experiments were established in northern and southern Queensland in which cultivars, with different growth characteristics, recommended for each region, were grown under a range of different row configurations. In the northern Queensland experiment at Gordonvale, cultivars Q187((sic)), Q200((sic)), Q201((sic)), and Q218((sic)) were grown in 1.5-m single rows, 1.8-m single rows, 1.8-m dual rows (50 cm between duals), and 2.3-m dual rows (80 cm between duals). In the southern Queensland experiment at Farnsfield, cvv. Q138, Q205((sic)), Q222((sic)) and Q188((sic)) were also grown in 1.5-m single rows, 1.8-m single rows, 1.8-m dual rows (50 cm between duals), while 1.8-m-wide throat planted single row and 2.0-m dual row (80 cm between duals) configurations were also included. There was no difference in yield between the different row configurations at Farnsfield but there was a significant row configuration x cultivar interaction at Gordonvale due to good yields in 1.8-m single and dual rows with Q201((sic)) and poor yields with Q200((sic)) at the same row spacings. There was no significant difference between the two cultivars in 1.5-m single and 2.3-m dual rows. The experiments once again demonstrated the compensatory capacity that exists in sugarcane to manipulate stalk number and individual stalk weight as a means of producing similar yields across a range of row configurations and planting densities. There was evidence of different growth patterns between cultivars in response to different row configurations (viz. propensity to tiller, susceptibility to lodging, ability to compensate between stalk number and stalk weight), suggesting that there may be genetic differences in response to row configuration. It is argued that there is a need to evaluate potential cultivars under a wider range of row configurations than the standard 1.5-m single rows. Cultivars that perform well in row configurations ranging from 1.8 to 2.0 m are essential if the adverse effects of soil compaction are to be managed through the adoption of controlled traffic.

Row spacing and planting density effects on the growth and yield of sugarcane. 2. Strategies for the adoption of controlled traffic.

Controlled traffic (matching wheel and row spacing) is being promoted as a means to manage soil compaction in the Australian sugar industry. However, machinery limitations dictate that wider row spacings than the standard 1.5-m single row will need to be adopted to incorporate controlled traffic and many growers are reluctant to widen row spacing for fear of yield penalties. To address these concerns, contrasting row configuration and planting density combinations were investigated for their effect on cane and sugar yield in large-scale experiments in the Gordonvale, Tully, Ingham, Mackay, and Bingera (near Bundaberg) sugarcane-growing regions of Queensland, Australia. The results showed that sugarcane possesses a capacity to compensate for different row configurations and planting densities through variation in stalk number and individual stalk weight. Row configurations ranging from 1.5-m single rows (the current industry standard) to 1.8-m dual rows (50 cm between duals), 2.1-m dual (80 cm between duals) and triple ( 65 cm between triples) rows, and 2.3-m triple rows (65 cm between triples) produced similar yields. Four rows (50 cm apart) on a 2.1-m configuration (quad rows) produced lower yields largely due to crop lodging, while a 1.8-m single row configuration produced lower yields in the plant crop, probably due to inadequate resource availability (water stress/limited radiation interception). The results suggest that controlled traffic can be adopted in the Australian sugar industry by changing from a 1.5-m single row to 1.8-m dual row configuration without yield penalty. Further, the similar yields obtained with wider row configurations (2 m or greater with multiple rows) in these experiments emphasise the physiological and environmental plasticity that exists in sugarcane. Controlled traffic can be implemented with these wider row configurations (>2 m), although it will be necessary to carry out expensive modifications to the current harvester and haul-out equipment. There were indications from this research that not all cultivars were suited to configurations involving multiple rows. The results suggest that consideration be given to assessing clones with different growth habits under a range of row configurations to find the most suitable plant types for controlled traffic cropping systems.