ArticleAsian-Australasian journal of animal sciences2015
Modelling Pasture-based Automatic Milking System Herds: The Impact of Large Herd on Milk Yield and Economics.
Article in Asian-Australasian journal of animal sciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this modelling study was to investigate the effect of large herd size (and land areas) on walking distances and milking interval (MI), and their impact on milk yield and economic penalties when 50% of the total diets were provided from home grown feed either as pasture or grazeable complementary forage rotation (CFR) in an automatic milking system (AMS). Twelve scenarios consisting of 3 AMS herds (400, 600, 800 cows), 2 levels of pasture utilisation (current AMS utilisation of 15.0 t dry matter [DM]/ha, termed as 'moderate'; optimum pasture utilisation of 19.7 t DM/ha, termed as 'high') and 2 rates of incorporation of grazeable complementary forage system (CFS: 0, 30%; CFS = 65% farm is CFR and 35% of farm is pasture) were investigated. Walking distances, energy loss due to walking, MI, reduction in milk yield and income loss were calculated for each treatment based on information available in the literature. With moderate pasture utilisation and 0% CFR, increasing the herd size from 400 to 800 cows resulted in an increase in total walking distances between the parlour and the paddock from 3.5 to 6.3 km. Consequently, MI increased from 15.2 to 16.4 h with increased herd size from 400 to 800 cows. High pasture utilisation (allowing for an increased stocking density) reduced the total walking distances up to 1 km, thus reduced the MI by up to 0.5 h compared to the moderate pasture, 800 cow herd combination. The high pasture utilisation combined with 30% of the farm in CFR in the farm reduced the total walking distances by up to 1.7 km and MI by up to 0.8 h compared to the moderate pasture and 800 cow herd combination. For moderate pasture utilisation, increasing the herd size from 400 to 800 cows resulted in more dramatic milk yield penalty as yield increasing from c.f. 2.6 and 5.1 kg/cow/d respectively, which incurred a loss of up to $AU 1.9/cow/d. Milk yield losses of 0.61 kg and 0.25 kg for every km increase in total walking distance (voluntary return trip from parlour to paddock) and every one hour increase in MI, respectively. The high pasture utilisation combined with 30% of the farm in CFR in the farm increased milk yield by up to 1.5 kg/cow/d, thereby reducing loss by up to $0.5/cow/d (c.f. the moderate pasture and 800 cow herd scenario). Thus, it was concluded that the successful integration of grazeable CFS with pasture has the potential to improve financial performance compared to the pasture only, large herd, AMS.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.