A total of 34 tomato genotypes (24 F1+10 parents) were tested for resistance to tomato leaf curl virus (ToLCV) disease by various whitefly inoculation techniques under field and insect-proof glasshouse (mass and cage) conditions. Of the ten tomato parental lines, two accessions [EC-520061 (Solanum habrochaites) and EC-521080 (Solanum pimpinellifolium)] were identified as highly resistant while four accessions (EC-520049, EC-528372, WIR-5032 and WIR-3957) of wild species were resistant to ToLCV. Out of the 24 F1 crosses, PBC×EC-520061, H-86×EC-520061, H-24×EC-520061 and DVRT-2×EC-520061 were found to be highly resistant against ToLCV disease. Biochemical (total phenol and total sugar concentration) and physiological (chlorophyll content and leaf area index) parameters were also used in healthy and disease-inoculated leaves of ten parents and six F1 hybrids to test the conformity of ToLCV-resistant and susceptible disease reactions. The results showed that among the 16 genotypes (10 parents+6 F1), EC-520061, EC-520049, PBC×EC-520061 and H-86×EC-520061 were stable for both biochemical and physiological markers while EC-521080 showed higher accumulations of total phenol and sugar concentrations and reduced leaf size between healthy and disease-inoculated leaves. The present study demonstrates the importance of the whitefly inoculation technique and biochemical and physiological markers in virus resistance screening programmes, and identifies a potential source of resistance to the ToLCV in Solanum species.

Although the grey forecasting model has been successfully employed in various fields and demonstrates promising results, the literature shows that its performance could still be improved. Therefore, the aim of the present study was to continue the investigation and derive three hybrid models to predict grain production in China by combining particle swarm optimization (PSO) with the grey linear power index model, the grey logarithm power model and the grey parabola power model. In grey modelling, the use of PSO had the ability to search optimum grey parameters to construct three improved derivative grey models. The results concluded that the improved optimization models with high precision were superior to the traditional models, and PSO contributed more to precision improvement of the three grey models. Furthermore, results from the experiments demonstrated that the optimized models were reliable and valid.

The present paper provides an approach for the design and analysis of variety trials that are used to obtain quality trait data. These trials are multi-phase in nature, comprising a field phase followed by one or more laboratory phases. Typically the laboratory phases are costly relative to the field phase and this imposes a limit on the number of samples that can be tested. Historically, this has been achieved by sacrificing field replication, either by testing a single replicate plot for each variety or a single composite sample, obtained by combining material from several field replicates. An efficient statistical analysis cannot be applied to such data so that valid inference and accurate prediction of genetic effects may be precluded. A solution that has appeared recently in the literature is the use of partial replication, in which some varieties are tested using multiple field replicates and the remainder as single replicates only. In the present paper, an approach is proposed in which some varieties are tested using individual field replicate samples and others as composite samples. Replication in the laboratory is achieved by splitting a relatively small number of field samples into sub-samples for separate processing. It is shown that, if necessary, some of the composite samples may be split for this purpose. It is also shown that, given a choice of field compositing and laboratory replication strategy, an efficient design for a laboratory phase may be obtained using model-based techniques. The methods are illustrated using two examples. It is demonstrated that the approach provides more accurate variety predictions compared with the partial replication approach and that the gains can be substantial if the field variation is large relative to the laboratory variation.

A study was carried out in the rainy seasons of 2008 and 2009 in Niger to investigate the effects of fertilizer micro-dosing on root development, yield and soil nutrient exploitation of pearl millet. Different rates of diammonium phosphate (DAP) were applied to the soil at different depths and it was found that although micro-dosing with DAP increased grain yield over the unfertilized control to a similar level as broadcast DAP, doubling the micro-dosage did not increase it further. Increasing the depth of fertilizer application from 5 to 10 cm resulted in significant increases in root length density, and deep application of fertilizer resulted in higher yields, although the increases were generally not significant. It was postulated that the positive effect of micro-dosing resulted from better exploitation of soil nutrients because of the higher root volume. Levels of nutrients exported from the soil were at least as high in plants receiving micro-dosing as the unfertilized control, and plants receiving micro-dosing exported 5–10 times more phosphorus from the soil than the amount added through fertilization.

Improvement of nitrogen (N) use efficiency is urgently needed since excessive application of N fertilizer has been widespread in small-scale fields in China, causing great losses of N fertilizer and environmental pollution. In the present study, a simple technology, termed the Green Window Approach (GWA), to optimize N strategies for cereal crops is presented. The GWA represents an on-field demonstration site visualizing the effects of incremental N levels and enables farmers to conduct such a trial within their own fields. The lowest N rate that achieves no visible change in plant growth or biomass shows the optimal N requirement of crops. Therefore the objective was to develop the key procedures of GWA and to evaluate the effects of its application in cereal crops on grain yield, N use efficiency and economic benefit. A total of seven GWA trials were performed from 2009 to 2011 on farmers’ irrigated wheat fields in the North China Plain. The GWA consisted of eight small plots placed in a compact layout on a well-accessible part of the field. Plot size varied from 2·5×2·5 to 4×4 m2, depending on the size and shape of each field. All GWA plots received basal nitrogen (N), phosphorus (P) and potassium (K) rates of 30 kg N/ha (except for the nil-N plot), 80 kg P2O5/ha and 100 kg K2O/ha. Nitrogen supplies, including residual soil nitrate in 0–90 cm determined at Zadoks growth stages (GS) 21–23 in early spring and the split-topdressing N at GS 21–23 and GS 41–52, were incrementally increased from 0 to 420 kg N/ha. The remaining part of the field still received farmers’ customary fertilization (FCF). Optimal N rate could be estimated as the lowest N rate that achieved no visible change in plant growth at GS 60–73. Compared with FCF area, grain yield was increased by 13% to a maximum or near maximum value of 5·8 t/ha, optimal N rate was sharply decreased by 69% to 116 kg N/ha, apparent N recovery was greatly increased from 11 to 46%, whereas the cost of fertilizer input was decreased by 57% to 1045 Chinese Renminbi (RMB)/ha (162 US$/ha), the profit of grain yield was increased by 13% to 12 211 RMB/ha (1891 US$/ha) and the net economic benefits were increased by 60% to 7473 RMB/ha (1157 US$/ha). Most importantly, the GWA does not need laboratory facilities, complicated procedures or professional knowledge of N balances, and farmers can easily understand and use GWA by themselves.

According to the EU 28/2009 directive, member states are mandated to substitute 10% of fossil fuels used in transportation with biofuels by the year 2020. Bioethanol production is expected to contribute significantly towards fulfilling Greece's obligations. First-generation bioethanol, produced from amylaceous and sugar crops, is the most important biofuel globally. Maize (Zea mays L.) is the main feedstock for production worldwide, while sweet sorghum (Sorghum bicolor L. Moench), although a promising raw material source, has not yet enjoyed substantial commercial exploitation due to the high seasonality of the crop. Sustainability criteria set by the EU constitute a key factor in the characterization and future use of biofuels. A 3-year study including 20 maize and 4 sweet sorghum varieties was conducted in order to compare these two crops in terms of emitted greenhouse gases (GHG) during the cultivation phase as well as regarding emission savings by substituting bioethanol for petrol/gasoline. Both crops demonstrated promising bioethanol yields reaching 5235·7 and 6443·7 l/ha/yr for maize and sweet sorghum, respectively, and showed that they could be employed towards first-generation bioethanol production in Greece. Sweet sorghum varieties produced higher bioethanol yields per hectare coupled with lower emissions during the cultivation phase and better overall GHG savings compared to maize.

Most crop models make use of a nutrient-balance approach for modelling crop response to soil fertility. To counter the vast input data requirements that are typical of these models, the crop water productivity model AquaCrop adopts a semi-quantitative approach. Instead of providing nutrient levels, users of the model provide the soil fertility level as a model input. This level is expressed in terms of the expected impact on crop biomass production, which can be observed in the field or obtained from statistics of agricultural production. The present study is the first to describe extensively, and to calibrate and evaluate, the semi-quantitative approach of the AquaCrop model, which simulates the effect of soil fertility stress on crop production as a combination of slower canopy expansion, reduced maximum canopy cover, early decline in canopy cover and lower biomass water productivity. AquaCrop's fertility response algorithms are evaluated here against field experiments with tef (Eragrostis tef (Zucc.) Trotter) in Ethiopia, with maize (Zea mays L.) and wheat (Triticum aestivum L.) in Nepal, and with quinoa (Chenopodium quinoa Willd.) in Bolivia. It is demonstrated that AquaCrop is able to simulate the soil water content in the root zone, and the crop's canopy development, dry above-ground biomass development, final biomass and grain yield, under different soil fertility levels, for all four crops. Under combined soil water stress and soil fertility stress, the model predicts final grain yield with a relative root-mean-square error of only 11–13% for maize, wheat and quinoa, and 34% for tef. The present study shows that the semi-quantitative soil fertility approach of the AquaCrop model performs well and that the model can be applied, after case-specific calibration, to the simulation of crop production under different levels of soil fertility stress for various environmental conditions, without requiring detailed field observations on soil nutrient content.

The extent to which markers have been used in chickpea breeding programmes has not been clearly determined. In the current study, phenotypic and marker-assisted selection (MAS) were employed to select blight resistant genotypes, comparing the effectiveness of both methods. The phenotypic evaluation showed that the resistance could be recessive in the material employed. However, the high distorted segregation towards the susceptible parent detected on linkage group four (LG4) could also explain the phenotype distribution of resistance. Phenotypic selection in F2:4 and F2:5 generations lead to an increase in the frequency of the allele associated with the resistance of the markers CaETR and GAA47, indicating the usefulness of these markers for MAS. The markers TA72 and SCY17 could be also useful for MAS but the high distorted segregation towards the susceptible parent in the region where these markers are located could explain their low effectiveness. The costs associated with phenotypic selection and MAS for ascochyta blight resistance during three cycles of selection are presented in the current study, showing that MAS was more expensive than phenotypic selection. Nevertheless, the use of markers reduced the time taken to select resistant lines. The markers analysed in the current study were useful to select genotypes resistant to ascochyta blight in chickpea breeding programmes, allowing pyramiding genes or quantitative trait loci (QTL) related to different pathotypes. It is recommended that MAS should be employed in early generations of chickpea breeding programmes for the four QTL analysed because this makes it possible to develop populations with a high frequency of the favourable alleles conferring resistance to blight.

Selenium (Se) is an essential micronutrient for human and animal health. Globally, more than one billion people are Se deficient due to low dietary Se. Low dietary intake of Se can be improved by Se supplementation, food fortification and biofortification of crops. Lentil (Lens culinaris Medikus subsp. culinaris) is a popular cool-season food legume in many parts of the world; it is naturally rich in Se and therefore has potential for Se biofortification. An Se foliar application experiment at two locations and a multi-location trial of 12 genotypes at seven locations were conducted from April to December 2011 in South Australia and Victoria, Australia. Foliar application of a total of 40 g/ha of Se as potassium selenate (K2SeO4) – 10 g/ha during full bloom and 30 g/ha during the flat pod stage – increased seed Se concentration from 201 to 2772 μg/kg, but had no effect on seed size or seed yield. Consumption of 20 g of biofortified lentil can supply all of the recommended daily allowance of Se. After Se foliar application, cultivars PBA Herald XT (3327 μg/kg), PBA bolt (3212) and PBA Ace (2957 μg/kg) had high seed Se concentrations. These cultivars may be used in lentil biofortification. In the genotypic evaluation trial, significant genotype and location variation was observed for seed Se concentration, but the interaction was not significant. In conclusion, foliar application of Se as K2SeO4 is an efficient agronomic approach to improve seed Se concentration for lentil consumers and there is also scope for genetic biofortification in lentil.

The present work built on a previous study of tillage trials, which found the effectiveness of least limiting water range (LLWR) as an indicator of soil organic carbon (SOC) mineralization under different tillage practices in a black soil of Northeast China in 2009. To improve the understanding of soil structure controls over SOC dynamics, a study was conducted to explore the relationship between LLWR, which was calculated based on soil bulk density and soil pore-size distribution, and the effects of LLWR, which was calculated based on soil bulk density and soil pore-size distribution on SOC mineralization following no tillage (NT) and mouldboard ploughing (MP). In contrast to MP, NT had a significantly greater volume of large macropores (>100 μm) at depths of 0–0·05 and 0·2–0·3 m, but a significantly lower volume of small macropores (30–100 μm) at depths of 0–0·05, 0·05–0·1, 0·1–0·2 and 0·2–0·3 m. The volume of meso- (0·2–30 μm) and micro-pores (<0·2 μm) at different depths under the two tillage practices were similar. Tillage-induced changes in soil bulk density and pore-size volumes affected the ability of soil to fulfil essential soil functions in relation to organic matter turnover. Soil pore-size distribution, especially small macropores greatly affected LLWR and there was a significant correlation between LLWR, which was calculated based on soil bulk density, and the proportion of small macropores. The proportion of small macropores were used to calculate LLWR instead of soil bulk density and the values for NT and MP soils ranged from 0·073 to 0·148 m3 water/m3 soil. Using the proportion of small macropores rather than bulk density in the calculation of LLWR resulted in more sensitive indications of SOC mineralization. Variation in the proportion of small macropores can help characterize the impacts of tillage practices on dynamics of LLWR and SOC sequestration.

A worldwide innovative method to discriminate grapevine clones is presented. It is an alternative to ampelography, isozyme and DNA analysis. The spectra and their first and second derivatives of 201 bands in the visible and near-infrared wavelength range between 634 and 759 nm were used as inputs to a classifier created using partial least squares. The spectra were acquired in the laboratory for the adaxial side of the apical part of the main lobe of fully hydrated grapevine leaves. The classifier created allowed the separation of 100 leaves of the Cabernet Sauvignon (Vitis vinifera L.) variety into four clones, namely CS 15, CS 169, CS 685 and CS R5, comprising 25 leaves each. The percentages of leaves correctly classified for these clones were 98·2, 99·2, 100 and 97·8%, respectively, when the classifier input was the second derivative of the normalized spectra. These percentages were determined by Monte-Carlo cross-validation. With the new method proposed, each leaf of a given variety can be classified in a few seconds according to its clone in an environmentally friendly way.

Modern agriculture is based on the control of in-field variability, which is determined by the interactions of numerous factors such as soil, climate and crop. For this reason, the use of remote sensing is becoming increasingly important, thanks to the technological development of satellites able to supply information with high spatial resolution and revisit frequency. Despite the large number of studies on the use of remote sensing for crop monitoring, very few have addressed the problem of spatial variability at field scale or the early prediction of crop yield and grain quality. The aim of the current research was to assess the potential use of high resolution satellite imagery for monitoring durum wheat growth and development, addressing forecast grain yield and protein content, through vegetation indices at two stages of crop development. To best represent the natural variability of agricultural production, the study was conducted in wheat fields managed by local farmers. As regards dry weight, leaf area index and nitrogen (N) content, the possibility of describing the crop state is evident at stem elongation, while at anthesis this potential is completely lost. However, satellites seem to be unable to estimate the N concentration. Aboveground biomass accumulated from emergence to stem elongation is strictly related to the final yield, while it has been confirmed that the crop parameters observed at anthesis are less informative, despite approaching harvesting time.

Field experiments were conducted between 2009 and 2011 in Ireland to compare the effects of soil tillage systems on the grain yield, nitrogen use efficiency (NUE) and nitrogen (N) uptake patterns of spring barley (Hordeum vulgare) in a cool Atlantic climate. The four tillage treatments comprised conventional tillage in spring (CT), reduced tillage in autumn (RT A), reduced tillage in spring (RT S) and reduced tillage in autumn and spring (RT A+S). Each tillage system was evaluated with five levels of fertilizer N (0, 75, 105, 135 and 165 kg N/ha). Grain yield varied between years but CT had a significantly higher mean yield over the three years than the RT systems. There was no significant difference between the three RT systems. Tillage system had no significant effect on the grain yield response to fertilizer N. As a result of the higher yields achieved, the CT system had a higher NUE than the RT systems at all N rates. There was no significant difference in NUE between the three RT systems. Conventional tillage had significantly higher nitrogen uptake efficiency (NUpE) than RT A and a significantly higher nitrogen utilization efficiency (NUtE) than all three RT systems. Crop N uptake followed a similar pattern each year. Large amounts of N were accumulated during the vegetative growth stages while N was lost after anthesis. Increased N rates had a positive effect on N uptake in the early growth stages but tended to promote N loss later in the season. The CT system had the highest N uptake in the initial growth stages but its rate of uptake diminished at a faster rate than the RT systems as the season progressed. Tillage system had an inconsistent effect on crop N content during the later growth stages. On the basis of these results it is concluded that the use of non-inversion tillage systems for spring barley establishment in a cool oceanic climate remains challenging and in certain conditions may result in a reduction in NUE and lower and more variable grain yields than conventional plough-based systems.

New-type oilseed rape (Brassica napus, ArArCcCc) with introgressed exotic subgenomic components from Brassica rapa (ArAr) and Brassica carinata (BcBcCcCc) showed strong heterosis in both vegetative and reproductive growth. The aim of the current study was to analyse the tolerance of the new-type B. napus with different exotic subgenomic contents to low nitrogen (N) stress. Under hydroponic culture and pot experiments, root system parameters, photosynthetic parameters, relative chlorophyll concentration (SPAD values), biomass, seed yield, seed yield components, N concentration and expressions of genes involved in N transport and assimilation were determined with two new-type B. napus genotypes (N-efficient genotype D4-15 and N-inefficient genotype D1-1) under high-N and low-N levels. Furthermore, N accumulation, N transfer efficiency and N use efficiency (NUE) were analysed in the two genotypes. The hydroponic and potted growth tests showed consistent characteristics in N uptake and utilization efficiency at the seedling stage, and N-efficient genotype (D4-15) showed better growth phenotypes across cultured conditions and N levels. Under the low-N condition, D4-15 produced a larger root system and accumulated more N, and had higher N transfer efficiency and NUE than D1-1. Moreover, D4-15 had significantly higher photosynthetic parameters, photosynthetic NUE and expression levels of the N transporter genes, BnNRT1·1, BnNRT2·5, BnNRT2·7 and BnAMT1·1, in roots or leaves, as well as higher seed yield than that of D1-1 under low-N supply. These results indicated that the N-efficient new-type B. napus D4-15 possessed excellent adaptability to low-N stress, which may be attributed to the highly introgressed exotic subgenomic components from B. rapa and B. carinata, suggesting the possibility of identifying high-nutrient-efficiency germplasm from inter-specific hybrids.

Delayed senescence, or stay-green, contributes to a longer grain-filling period and has been regarded as a desirable characteristic for the production of a number of crops including wheat. In the present study, in order to identify quantitative trait loci (QTLs) for traits related to the progression of wheat flag leaf senescence, green leaf area duration (GLAD) of a doubled haploid (DH) population, derived from two winter wheat varieties Hanxuan10 and Lumai14, was visually estimated under two water conditions and was recorded at 3-day intervals from 10 days after anthesis to physiological maturity using a 0–9 scale. According to GLAD, parameters related to the progression of senescence of DH lines and their parents were estimated by the Gompertz statistical model. Based on the model parameters, DH lines were categorized into three groups under drought stress and four groups under well-watered conditions. A total of 24 additive QTLs and 23 pairs of epistatic QTLs for parameters related to the progression of senescence were identified on 18 chromosomes, except for 3B, 1D and 6D. Of the QTLs detected, 14 and 10 additive QTLs were associated with the investigated traits under drought stress and well-watered conditions, respectively. Furthermore, 4, 7, 6, 2 and 2 additive QTLs for traits related to progression of senescence were clustered around the same or similar regions of chromosomes 1A, 1B, 5A, 5B and 7A, respectively. The present data provided the genetic basis for high phenotypic correlations among traits related to the progression of wheat flag leaf senescence. In addition, 17 loci were co-located or linked with previously reported QTLs regulating chlorophyll fluorescence, high-light-induced photo-oxidation, or heat stress and dark-induced senescence. The marker Xwmc336 on chromosome 1A, responsible for the onset and end times of leaf senescence, the time to maximum rate of senescence, the time to reach 75% senescence and chlorophyll content under drought stress may be helpful for marker-assisted selection breeding of wheat.

Improving resistance to water and osmotic stresses at the seedling stage is becoming a much more important target for wheat breeders due to an increase in the frequency and severity of drought occurrences at the crop establishment and tillering phases in many wheat growing areas of the world. Ninety-six diverse wheat genotypes were laboratory tested for germination and growth response under osmotic stress induced by polyethylene glycol (PEG). Germination percentage, mean germination time, coleoptile length, shoot length and shoot growth rate were compared under stress (−0·4 MPa) and control (0·0 MPa) conditions. The same genotypes were previously grown in field trials exposed to drought stress during the anthesis and/or grain filling growth stage along with control (optimum) conditions. Grain yield (GY) and 19 other traits of agronomic importance (earliness, stem-related traits, number of kernels, mass of 1000 grains, etc.) were recorded. All seedling traits under PEG-induced water stress showed the highest relationship with the stem and stem-related traits of adult plants. To study the correlation between stress tolerance in the seedling and reproductive stages, three stress indices (tolerance index (TOL), stress susceptibility index (SSI) and stress tolerance index (STI)) for the seedling traits and GY under pre- and post-anthesis drought stress were calculated, based on a mean trait value obtained under stress and the corresponding trait value under control conditions. The ranking of the genotypes based on TOL and STI from seedling traits was found in most cases to be significantly correlated with the ranking of genotypes based on TOL and STI from GY, respectively.

Compost use is increasingly proposed as a sustainable strategy to restore the fertility of degraded agricultural soils and to reduce landfill disposal or incineration of organic wastes. The effects of compost application on many soil physico-chemical and biological properties, as well as on soil contamination, have been investigated widely, but a model for the ecological interactions among them has never been developed. The aim of the present paper was to provide an integrated view of the causal processes induced by repeated compost amendments on agricultural soil properties. For this purpose, a confirmatory path analysis was performed to enable inferences to be drawn about the causal processes involving compost amendment, soil organic matter content, nutrient concentrations, microbial activity and soil contamination. The path analysis was performed on a dataset derived from a 3-year field trial carried out by the current authors in a Mediterranean intensive agricultural system, where 0, 15, 30 or 45 t/ha of certified compost from municipal solid wastes were annually applied. A script (‘cpa’) was developed using the R programming language and used to test 13 hypothetical models, expressed as directed acyclic graphs, against the observed data. Within the above-mentioned dataset, potassium and zinc available concentrations, microbial respiration and total polycyclic aromatic hydrocarbon (PAH) concentrations were selected as indicative of soil nutrient availability, microbial activity and organic contamination. The applied approach highlights that compost amendment directly influences all the other variables considered in the study and is the main determinant of the observed trends. Other important relationships are those among organic matter, nutrient availabilities, respiration and PAHs, as well as their temporal dynamics.

The widespread adoption by agronomists and researchers of handheld leaf chlorophyll meters stimulates enquiries on instrumental calibration issues, given the necessity, for some applications, of inferring actual chlorophyll concentrations from the readings provided. This is especially required for recently developed and more innovative devices such as the Dualex (Force-A, France), which unlike the more common SPAD-502 (Minolta, Japan) has not undergone extensive (published) calibration tests. Additionally, devices for spectral reflectance measurements are also becoming increasingly available. In the present paper, the calibration of SPAD on maize (Zea mays L.) and of Dualex on winter wheat (Triticum aestivum L.), durum wheat (Triticum durum Desf.), horse bean (Vicia faba L.) and maize, was compared to spectral reflectance indices and full spectral information (400–2500 nm) acquired by a spectroradiometer (ASD FieldSpec) equipped with a contact probe and leaf clip. Full spectral data were exploited using partial least squares regression (PLSR). The measurements were performed in the field at Maccarese (Central Italy) in 2012, gathering a specific experimental dataset. The calibration models obtained on experimental data for SPAD (on maize) and Dualex (on four crops) showed intermediate or high estimation accuracy with root-mean-square error (RMSE) values ranging between 7 and 11 μg/cm2 depending on the species. These results were slightly better than those achieved using spectral reflectance indices, which were inferior though to those provided by PLSR using full spectral resolution. A synthetic database, generated by the physically based PROSPECT model, simulating hemispherical leaf reflectance and transmittance, was used to compare the performances of the reflectance indices and the chlorophyll meters for a wider range of leaf properties. The results confirmed the substantial equivalence of reflectance-based and transmittance-based (i.e. simulated SPAD and Dualex) indices and the advantage of exploiting the full spectral information, e.g. through PLSR, if available.

Improvements in milk quality are important if the Irish dairy industry is to grow sustainably and retain a competitive advantage in a post-quota environment. In this regard, superior animal health has an important role to play. In order to reduce the costs of disease and to improve best practice it is important to demonstrate the economic gains achievable from improved dairy herd health. Elevated levels of somatic cell count (SCC) are an indicator of the prevalence of clinical and sub-clinical mastitis in dairy herds. Nationally representative farm-level data for Ireland (2008–2011) and panel data methods are used here to consider the independent effect of herd-level SCC (an annual weighted average figure based on monthly milk bulk tank readings) on both milk yield and gross margin per cow. Results indicate a 2% reduction in productivity for farms with SCC above 400 (‘000 cells/ml), while a reduction in bulk tank SCC from 400 to 300 (‘000 cells/ml) for the average herd (55 cows) results in an annual increase in gross margin of €1045. The impact of a range of herd management practices on SCC is also considered, with such practices shown to be important in influencing animal health.