A large body of published research now exists on economic, social, technical and policy related aspects of organic production. The dramatic increase in published research over the last 20 years reflects not only the existence of policy support for organic farming in some countries but also the availability of government funding for research on organic farming. This has resulted in a broadening out of organic research from privately funded, specifically organic research organizations, into universities and mainstream research institutes. In parallel, publication of research results from organic farming has increasingly appeared in refereed literature in addition to literature sources more available to farmers and advisors. Research scientists from Europe, North America and Australasia have all made important contributions to the peer-reviewed literature. The literature is dominated by comparisons of organic and other forms of agriculture, although in many cases these comparisons are not fully valid. Research directed specifically at organic systems is often much more valuable in developing improved production systems than comparative research. Research on organic farming embodies both holistic and reductionist research approaches. Trans-disciplinary research also has an important role to play in understanding the complexities of the ecological approach to agriculture typified by organic farming. Working within the principles and standards of organic agriculture will mean that some research will always be specific to organic production systems. However, in future an increased transfer of knowledge from organic to conventional agriculture and vice versa is envisaged.

Farming systems research is a multi-disciplinary holistic approach to solve the problems of small farms. Small and marginal farmers are the core of the Indian rural economy constituting 0·80 of the total farming community but possessing only 0·36 of the total operational land. The declining trend of per capita land availability poses a serious challenge to the sustainability and profitability of farming. Under such conditions, it is appropriate to integrate land-based enterprises such as dairy, fishery, poultry, duckery, apiary, field and horticultural cropping within the farm, with the objective of generating adequate income and employment for these small and marginal farmers under a set of farm constraints and varying levels of resource availability and opportunity. The integration of different farm enterprises can be achieved with the help of a linear programming model. For the current review, integrated farming systems models were developed, by way of illustration, for the marginal, small, medium and large farms of eastern India using linear programming. Risk analyses were carried out for different levels of income and enterprise combinations. The fishery enterprise was shown to be less risk-prone whereas the crop enterprise involved greater risk. In general, the degree of risk increased with the increasing level of income. With increase in farm income and risk level, the resource use efficiency increased. Medium and large farms proved to be more profitable than small and marginal farms with higher level of resource use efficiency and return per Indian rupee (Rs) invested. Among the different enterprises of integrated farming systems, a chain of interaction and resource flow was observed. In order to make farming profitable and improve resource use efficiency at the farm level, the synergy among interacting components of farming systems should be exploited. In the process of technology generation, transfer and other developmental efforts at the farm level (contrary to the discipline and commodity-based approaches which have a tendency to be piecemeal and in isolation), it is desirable to place a whole-farm scenario before the farmers to enhance their farm income, thereby motivating them towards more efficient and sustainable farming.

Currently, the diversity of sow herd management strategies has been described but there are no tools that explore how it promotes sow herd performance nor how it or performance are linked to work organization problems. The goal of the current study was to build a herd dynamic, stochastic object-oriented model capable of representing the herd dynamics and performance, and to predict the number of events workers will have to deal with. Each sow is individually represented in the model and the model works as a discrete event simulator with a predefined time step of 1 h. At each time step of simulation, the model searches for an event to be processed. An event may imply change of sow physiological state (e.g. oestrus, farrowing and insemination) and/or request an action from a worker (e.g. oestrous detection and farrowing supervision). This action may result in the planning of a new event (e.g. farrowing after mating) and/or modification of sow state (e.g. from oestrus to pregnant). The occurrences of some technical activities such as weaning are defined in time and frequency according to the management strategy of the farmer. The model is stochastic as sow biology is represented by several normal univariate distributions according to parity or by a threshold (fertility, abortion and mortality rates). When sows return into oestrus after mating they can be moved to another batch or culled depending on batch management strategy and culling policy. Outputs of this model focus on productivity of sows and distribution of tasks over the week. Definitions of the duration of simulation and number of replications to obtain the steady state and the variability of results are presented. The model is able to simulate several batch farrowing systems (BFS) and results of 1-, 3- and 4-week BFS are presented. Several simulations with modified management (no oestrous detection during the weekend and change of the weaning day) or with modified sow biology (increased variability of the weaning-to-oestrus interval and lower fertility rate) are performed. Results indicate that these modifications have specific consequences on performance and task distribution according to the BFS. The model provides useful information concerning the effects of herd management strategies on productivity and distribution of events over time and their sensitivity to biological criteria.

In beef suckler herds, reproductive failure is a major cause of financial loss during a bovine viral diarrhoea (BVD) outbreak due to reduction in the numbers of calves, increased calving spread and the financial implications of dealing with infertile cows. These losses may be hidden and/or not fully attributed to BVD. A model of herd dynamics was built and combined with an epidemiological model to encapsulate the disruptions to reproduction that BVD may cause in beef suckler herds and to estimate the associated financial consequences of such disruptions.

Results from the model suggest that the average losses associated with BVD in Scottish beef suckler herds via impaired reproduction alone may vary between £43 and £22/cow/year during the course of a BVD epidemic. These results indicate that an outbreak can be costly and these losses may be hidden by the use of low risk management practices such as a long breeding season, not only in herds with no evidence of antibodies but also in herds where there are some antibody positive (immune) animals.

Brody (1945) concluded that the inflection point of the growth curve of domestic animals coincides with the onset of puberty and is coupled with an increase in proportion of fat gain at that time. This purported coincidence of growth inflection and onset of puberty has been termed the ‘Brody Law’. Recent findings suggesting a pivotal role of body energy reserves, communicated by the metabolic hormone leptin, on the onset of puberty led to the hypothesis that sheep must reach the inflection point of growth (AIP) considerably before the onset of puberty (AOP). In order to test this hypothesis, growth curves were fitted for ewe lambs on different growth trajectories from two experiments. Both experiments examined the effect of growth trajectory on AOP in ewe lambs. One data set was developed in France with Merino sheep; the other came from two distinct genetic lines of Targhee sheep in the USA. The French experiment subjected ewe lambs to two different feeding levels, while the USA experiment compared two nutritional regimens differing in both energy and protein concentration.

Several non-linear models described in the literature as potentially useful for modelling weight–age relationships were fitted. The Logistic function was identified as the superior model for all datasets. All animals in both experiments reached AIP considerably before AOP. AOP was defined using two criteria threshold levels of progesterone as AOP1 ⩾0·5 ng/ml and AOP2 ⩾1 ng/ml progesterone. For the USA data, multivariate analysis of AIP, AOP1 and AOP2 demonstrated that nutritional treatment was highly significant; this was also the case for the multivariate analysis of AIP, degree of maturity at AOP1 (DOM1) and DOM2. The correlation between AIP and DOM was highly negative. In contrast, the feeding treatment in the French experiments had no effect on any of the response variables except estimated mature weight. However, AIP was negatively correlated with DOM1 and DOM2. AOP was highly positively correlated with DOM. Most notably, AIP was not correlated with AOP1 or AOP2 in either experiment, and all animals reached AIP considerably before AOP1. These findings are consistent with the hypothesis that growing female sheep must reach a certain minimum level of body fatness before the onset of puberty. Genetic group and nutritional treatment significantly affect growth curve parameters; hence, the age at which this (currently unknown) level is reached must strongly depend on nutritional regimen. It is concluded that growth modelling per se cannot be used to infer onset of puberty, and that endocrine thresholds do not necessarily demarcate distinct phases of the growth curve.

This paper provides information on the extent and containment of intraclass correlation (ICC) concerning group-feeding trials on suckler cows. The research comprised the re-analysis of six previously reported experiments and a parallel simulation study. ICC coefficients were estimated for eight variables. They were seen to be higher in experiments on bulls compared with those on cows and more notable in the measurements of live weight gain compared with final weight. Moreover, the ICC coefficients were generally high for all variables measuring behavioural patterns. The simulation study showed that using a single animal as an experimental unit could be valid in certain situations, but it could not be extended to cover all the cases. The simulation study also showed that the common mixed model approach had significant problems when the ICC was slight. In general, the research strengthened the arguments that much more effort should be placed on the planning and statistical analysis of group-feeding experiments, especially in behavioural studies.

Cull cows account for a large part of beef consumption in France and are a significant proportion of farm income for dairy (0·10) and beef systems (up to 0·30). On-farm observations highlight considerable variations in cull cow phenotypes in terms of age, frame size, health, physiological status and body condition. Consequently, an important issue for producers of cull cows is the management of feed supply during the finishing period to obtain a satisfactory condition score and conformation prior to slaughter.

New feeding recommendations for cull cows should consider live weight and live weight gain, age, frame size and body condition score (BCS) to estimate the energy requirements. A predictive model, called CompoCow, was developed for this purpose. The present paper describes the CompoCow model by summarizing developments from previous modelling approaches and outlining the assumptions and equations used in the model. CompoCow combines a growth model for the cow during its productive period (3–8 years old) and a model for the finishing period (in days) and was parameterized for Charolais, Limousine and Holstein breeds. Sensitivity analysis highlighted that the outputs of the model were mainly sensitive to initial body weight and expected body weight gain of the animal. The proportion of lipid in live weight gain was related to body weight, BCS and frame size of the animal. The model also accounts for the higher proportion of lipid in live weight gain in Holstein than in Charolais cows. The model was applied to data from Charolais cows. It showed that the proportion of variability explained by CompoCow for energy requirements was higher than the proportion obtained with previous INRA recommendations, 0·78 and 0·67, respectively. CompoCow does not rely on mechanistic relationships, but it appears robust as it accounts correctly for the effects of age and BCS on the requirements.

Descriptions of entire lactations were investigated using six mathematical equations, comprising the differentials of four growth functions (logistic, Gompertz, Schumacher and Morgan) and two other equations (Wood and Dijkstra). The data contained monthly milk yield records from 70 first, 70 second and 75 third parity Iranian Holstein cows. Indicators of fit were model behaviour, statistical evaluation and biologically meaningful parameter estimates and lactation features. Analysis of variance with equation, parity and their interaction as factors and with cows as replicates was performed to compare goodness of fit of the equations. The interaction of equation and parity was not significant for any statistics, which showed that there was no tendency for one equation to fit a given parity better than other equations. Although model behaviour analysis showed better performance of growth functions than the Wood and Dijkstra equations in fitting the individual lactation curves, statistical evaluation revealed that there was no significant difference between the goodness of fit of the different equations. Evaluation of lactation features showed that the Dijkstra equation was able to estimate the initial milk yield and peak yield more accurately than the other equations. Overall evaluation of the different equations demonstrated the potential of the differentials of simple empirical growth functions used in the current study as equations for fitting monthly milk records of Holstein dairy cattle.

A centenary review presents an opportunity to ponder over the processes of concept development and give thought to future directions. The current review aims to ascertain the ontogeny of current concepts, underline the connection between ideas and people and pay tribute to those pioneers who have contributed significantly to modelling in animal nutrition. Firstly, the paper draws a brief portrait of the use of mathematics in agriculture and animal nutrition prior to 1925. Thereafter, attention turns towards the historical development of growth modelling, feed evaluation systems and animal response models. Introduction of the factorial and compartmental approaches into animal nutrition is noted along with the particular branches of mathematics encountered in various models. Furthermore, certain concepts, especially bioenergetics or the heat doctrine, are challenged and alternatives are reviewed. The current state of knowledge of animal nutrition modelling results mostly from the discernment and unceasing efforts of our predecessors rather than serendipitous discoveries. The current review may stimulate those who wish for greater understanding and appreciation.

Nine spring wheat cultivars, selected on the basis of height, tillering capacity and maturity, were grown in differing levels of natural weed presence at three locations in Edmonton and New Norway, Alberta between 2003 and 2004. The objectives of the study were to (1) identify competitive traits in wheat cultivars, (2) determine whether traits associated with competitive ability differ under increasing weed pressure and (3) assess cultivar stability in and adaptation to environments differing in yield potential and weed competition. Eight experimental environments (including conventionally and organically managed fields with and without common oats sown as a weed analogue) were grouped into low, medium and high weed pressure levels, based on mean total weed biomass. Tallness and early heading and maturity were related to increased grain yield at the highest weed level. Greater spikes/m2, tallness and early heading were associated with reduced weed biomass, depending on weed level. Principal component analysis (PCA) revealed that height accounted for a small amount of variation in low weed environments, yet was more important as weed pressure increased. Finlay–Wilkinson (Finlay & Wilkinson 1963) stability analysis demonstrated that cultivars responded differently in environments differing in yield potential and in weed pressure. Older wheat cultivars were generally more yield-stable across environments, while modern semidwarf cultivars were more sensitive to changes in weed level. The cultivar Park (released in 1963) was the most yield- and weed-stable cultivar, coupled with relatively high yields and average weed biomass accumulation, and may therefore be well adapted to low yielding or high weed environments.

Many of the most pervasive disease challenges to livestock are transmitted via oral contact with faeces (or by faecal–aerosol) and the current paper focuses on how disease risk may depend on: spatial heterogeneity, animal searching behaviour, different grazing systems and faecal deposition patterns including those representative of livestock and a range of wildlife. A spatially explicit agent-based model was developed to describe the impact of empirically observed foraging and avoidance behaviours on the risk of disease presented by investigative and grazing contact with both livestock and wildlife faeces. To highlight the role of spatial heterogeneity on disease risks an analogous deterministic model, which ignores spatial heterogeneity and searching behaviour, was compared with the spatially explicit agent-based model. The models were applied to assess disease risks in temperate grazing systems. The results suggest that spatial heterogeneity is crucial in defining the disease risks to which individuals are exposed even at relatively small scales. Interestingly, however, although sensitive to other aspects of behaviour such as faecal avoidance, it was observed that disease risk is insensitive to search distance for typical domestic livestock restricted to small field plots. In contrast disease risk is highly sensitive to distributions of faecal contamination, in that contacts with highly clumped distributions of wildlife contamination are rare in comparison to those with more dispersed contamination. Finally it is argued that the model is a suitable framework to study the relative inter- and intra-specific disease risks posed to livestock under different realistic management regimes.

Increased harvest index (HI) has been one of the principal factors contributing to genetic yield improvements in spring barley (Hordeum vulgare L.), oat (Avena sativa L.) and wheat (Triticum aestivum L.) cultivars. Although high HI demonstrates high-yielding ability when cultivars are compared, it can also indicate challenges to yield formation when comparisons are made across differing growing conditions. The present study was designed to investigate variation in HI among modern cereal cultivars relative to that brought about by a northern environment, to assess whether HI still explains the majority of the differences in grain yield when only modern cereal cultivars are compared, and to monitor key traits contributing to HI. Stability of HI was also investigated with reference to the role of tillers. Twelve experiments (3 years, two locations, two nitrogen fertilizer regimes) were carried out in southern Finland to evaluate 12 two-row spring barley, 10 six-row barley, 10 oat and 11 wheat cultivars. In addition to HI, days to heading and maturity, length of grain filling period, grain yield, test weight and 13 traits characterizing plant stand structure were measured and analysed with principal component analysis (PCA) to detect traits associated with HI and those contributing to stability of HI. Although only modern cereals were studied, differences among cultivars were significant both in mean HI and stability of HI, and HI was associated with short plant stature in all modern cereal species. Also, single grain weight was associated with HI in all species. Differences between, but not within, species in HI were partly attributable to differences in tiller performance. Grain yield was associated closely with HI except in two-row barley. It may be possible to further increase HI of wheat, as it still was relatively low. High HI did, however, not indicate the degree of success in yield determination when environments are compared.

Sensitivity analysis is routinely carried out in the evaluation of simulation models to identify the degree to which parameters influence model outputs. This type of sensitivity analysis is much less frequently applied to real systems, but a technique called metabolic control analysis (MCA) was developed in the 1970s for the purpose of experimentally identifying the degree to which individual enzymes in a metabolic pathway influence flux through the pathway. MCA is applied to the results of inhibition, activation or genetic manipulation of enzymatic steps in a biochemical pathway. Flux control coefficients for each enzyme are defined as the fractional change in steady-state flux through the entire pathway for an infinitesimal change in the activity of that one enzyme. The sum of control coefficients in a linear, non-branching pathway is equal to one. It is a common finding in MCA that the control, or sensitivity, is distributed over multiple enzymes and not in a single rate-limiting enzyme. The fundamental principles of MCA are reviewed and an overview of experimental methods to measure control coefficients is provided, with the objective of introducing this approach to the fields of agricultural biochemistry and modelling, where it is little known. The application of MCA to the study of glucose metabolism and fatty acid synthesis in bovine mammary tissue are reviewed. The analyses indicated that mammary hexokinase activity exerts more control than transmembrane transport of glucose over lactose synthesis, and that control of cytosolic fatty acid synthesis is shared between acetyl-CoA carboxylase and fatty acid synthase, contrary to the widely held view that acetyl CoA carboxylase is the rate-limiting enzyme. It is suggested that MCA could be a valuable aid in the integration of proteomic and metabolomic data with metabolic flux measurements to engineer desired changes in the composition of milk from dairy animals.

In France, many dairy farms plan the allocation of animal wastes to the fields of the farm at the beginning of every year. This decision is complex, because many factors must be taken into account at the field and farm scales, including increasingly constraining environmental regulations. To evaluate the environmental impact of waste allocation strategies, these strategies have to be translated into consistent decisions. The objective of the current study was to reproduce the decisions made by farmers, in a wide range of contexts. For this purpose, a linear programming model that could help in generating yearly waste allocations was developed. The model, called Fumigene, takes into account the farmer's preferences and environmental, agronomic and feasibility constraints. It was applied on two case farms and the simulated waste allocations were compared to those chosen by the farmers over periods of 3 and 4 years, respectively. The evaluation showed that the waste allocations generated by the model were consistent with the strategies of the farmers. Fumigene was then used in investigating the impact of taking into account the phosphorus (P) fertilization constraints instead of only the nitrogen constraints. In the case studied, balancing P fertilization over 5 years led to small changes in waste allocation. Balancing P fertilization every year caused bigger changes and led to export of a part of the wastes. In a general way, Fumigene can be coupled with environmental evaluation tools to compare the impacts of different waste allocation strategies.

Obtaining accurate estimates of the metabolizable energy (ME) intake (MEI; MJ/day) of individual grazing ruminants is an important requirement for effective nutritional management and genetic selection of energy efficient ruminants. Diet digestibility and the daily methane production rate (MPR; MJ/day) of ruminants can be closely linked with their MEI, so published data were examined to determine whether MEI could be accurately estimated from digestibility, MPR and other parameters able to be measured on grazing animals. Four modelling approaches were assessed or developed to estimate MEI: (i) a published fixed proportional relationship between the non-metabolizable losses of MPR and urinary energy (UE; MJ/day); (ii) the proportion of energy digestibility (EngDig); (iii) MPR and the ruminal factors that influence the stoichiometric relationships between MPR and MEI; and (iv) the calculated ME arising from rumen fermentation (MEf; MJ/day). Data to develop the models (n=61) were collected across three publications (Paper) where the Paper effect was treated as a random-effect variable. Each of the models (1–4) was challenged with an independent data set (n=19). The inclusion of MEf (P=0·01) to predict MEI [MEI=0·18 (2·03)+3·42 (0·36)×sqrt(MEf) (d.f.=57; residual log likelihood=173·6)] had the lowest mean square error of prediction (MSEP) when challenged with the independent data set; mean bias of −0·42 MJ/day (P<0·05), MSEP=0·68 MJ/day and the bias, slope and random components of the MSEP were, as a proportion, 0·26, 0·13 and 0·61, respectively. None of the models estimated MEI with sufficient accuracy to be useful for identifying individual animals with above average energetic efficiency. A critical limit to any model seeking to estimate MEI from MPR and fermentation traits appears to be the variation between animals and between diets, in the proportion of digested energy which is fermented relative to that which is made available by mammalian digestion, and this is evaluated.

In the context of market liberalization and in order to avoid trade distortions, European farmers risk experiencing a restriction of subsidies for market products. Moreover, policy makers cannot underestimate the public concerns about the non-productive functions of agriculture, such as environmental management. The current study illustrates different ways of modelling the trade-offs between environmental sustainability and economic viability for dairy farming systems in Reunion Island. Nitrogen (N) balance at the farm level is the result of complex interactions between pasture and animal management and between bio-technical and socio-economic management. Therefore, different multi-criteria models were tested using a common dynamic bio-economical model that integrated the different sub-systems of the farm and their interactions. Nitrogen excess mitigation in Reunion Island dairy farming systems was used as an illustration of a non-productive objective taken into account in the decision process modelling.

The simulations highlighted the necessity to adapt the nitrogen mitigation objective to the technical level of local territories in order to adopt environmentally friendly practices, without jeopardizing the local dairy sector. Moreover, the models generated a different set of solutions that varied according to how non-production functions are integrated in farmers' decision-making processes. This constitutes a relevant basis for discussions between farmers and decision makers.

A model of reproductive performance was developed to study the influences of breeding management decisions and animal characteristics on the reproductive performance and the calving distribution in a beef herd. In the model, reproductive performance is formalized as a sequence of events (parturition, ovulation, conception), each of which modifies the reproductive status of the simulated cow. With respect to reproduction, a cow can be in one of three possible states: open-not-cycling, open-cycling or pregnant. The length of the different intervals that are included between two successive reproductive events (calving to first cycle interval, length of oestrous cycles, calving–conception and calving intervals) is formalized using stochastic or empirical laws that may be influenced by numerous animal or environmental factors or by management decisions (feeding strategy, breeding season and length of the breeding period). Within the herd, cows are considered to differ from each other by their parity, calving date, body condition at calving and their bull exposure.

Calving to first oestrous interval (postpartum anoestrous interval (PPAI)) is expressed as the sum of three equations which formalize the respective effects of calving date, body condition score at calving (BCScalving) and the response to early bull exposure in interaction with BCScalving. The influences of these variables on reproductive performance were quantified by analysing data sets (three bibliographical and two experimental) or by expertise. Special attention was paid to the influence of calving date on PPAI and a biological interpretation of this effect is proposed. Probabilities of natural insemination success were estimated according to the number of oestrus and the number of matings.

The model was fitted to data from primiparous Charolais cows (n=139) bred at the experimental station Laqueuille (French National Institute for Agricultural Research (INRA)). Its ability to simulate PPAI was tested using an independent data set of primiparous Charolais cows (n=188) from the experimental farm Le Pin. The model only accounts for 39% of the observed inter-individual variability. However, the analysis of the mean square deviation components led to validation of the structure of the model. In particular, the assumption that the influence of calving date on PPAI can be attributed to a sensitivity of the reproductive function to the variation of the photoperiod during the month preceding parturition was confirmed. Simulations also revealed that fat cows could have similar anoestrus to thin cows when they are exposed early to a bull. Such a result emphasized the necessity to investigate further and better calibrate the combined effects of BCS at calving and bull exposure on PPAI.

The present investigation was designed to assess the range of growth-promoting activities of various rhizosphere bacteria on wheat and oat growing in Lanzhou, China. Detection of the N-fixing bacteria by the acetylene reduction assay-based most probable number (ARA-based MPN) method indicated the presence of significant numbers of N-fixing rhizobacteria, i.e. 5·8×106 bacteria/g dry weight of root in association with Chinese wheat variety V4. A total of 24 rhizobacteria was isolated from wheat and oat grown in Lanzhou, China. These bacterial isolates were studied for growth characteristics, nitrogen fixation, phosphate solubilization and indole acetic acid (IAA) production. All the isolates were motile and gram negative. Acetylene reduction activity was detected in all isolates ranging from 124·6 to 651·6 nmol C2H2 reduced/h/vial while almost all isolates produced IAA ranging from 0·2 to 5·1 μg/ml. Only two isolates, ChW1 and ChW6, formed clear zones on Pikovskaia's medium, showing the ability to solubilize phosphates. ChW1 and ChW6 were used to develop fluorescent antibodies to check the cross reactivity of the isolates. Inoculation of these bacterial isolates resulted in higher plant biomass, root area and total N content on Chinese wheat variety Ningchun 2 and Pakistani oat variety Swan under controlled conditions. Among the wheat isolates, ChW5 was the best in promoting wheat growth by increasing its root length, root area, shoot dry weight and total N content. Among oat isolates, ChO3, ChO5 and ChO6 showed significant effects on different growth parameters of their host plants. Using the 15N isotope dilution method, the highest N fixation contribution (0·73 of total plant N) was observed in the wheat plants inoculated with isolate ChW5. Random amplified polymorphic DNA (RAPD) analysis of seven selected isolates showed that the variation within the isolates from different host crops grown in the same soil was quite large and helpful not only in defining the bacterial strains associated with different host crops but also in defining the distances of isolates from standard strains of rhizobacteria used. In conclusion, the present results indicate that the selected bacterial isolates did promote the growth of wheat and oat in ways that could be harnessed to practical benefit for the farmer and consistent with sustainable agricultural practices in China.

Manure production in the most livestock-intensive areas exceeds the crop demand for nutrients and legislative restrictions on application rate cause a shortage of land for manure application. Export of nutrients in the fibrous fraction of separated animal slurry has become an option for sustaining or increasing livestock production in livestock-intensive areas. The nitrogen (N) and carbon (C) losses during on-farm storage of the fibrous fraction, originating from separation of anaerobically digested pig slurry using the non-volatile elements phosphorus (P), copper (Cu) and zinc (Zn) as internal references, were calculated. In addition, the plant availability of N in fresh and stored fibrous fractions was evaluated in an incubation experiment. The losses of N and C were greater from the heap surface than from the centre, and turning the heap by reloading for transport increased the losses. The proportion of ammonium N, total N and C lost during storage of the fibrous fraction was 0·30–0·90, 0·10–0·55 and 0·35–0·70 of the initial amount, respectively. Storage reduced the plant-available N and the amount of residual organic N, thereby having long-term influence on soil fertility. The plant-available N in fresh fibrous fractions was 0·22–0·52 of total N, but decreased to 0·15–0·38 after storage due to a decrease of the Nammonium:Ntotal ratio during storage. The net mineralization of manure N was negatively related to the Ctotal:Norganic ratio. The fibrous fraction of separated pig slurry may be characterized as a manure with a high potential for loss and a variable value as fertilizer.