The genetic effects, including genetic main effects and genotype×environment (G×E) interaction effects, for oleic acid content (OAC) and linoleic acid content (LAC) at five different developmental times/stages were studied using unconditional and conditional genetic models for seed quantitative traits in diploid plants. The unconditional analysis results revealed that both OAC and LAC were simultaneously controlled by diploid embryo nuclear genes, cytoplasmic genes and diploid maternal plant nuclear genes and their G×E interaction effects. Effects on the embryo and cytoplasm were found to be more important for OAC at different developmental times while maternal effects, in combination with cytoplasmic effects, were more important for LAC at most development times. The conditional analysis revealed that the net effect from expression of maternal genes was more important for both traits at most developmental stages. The total narrow-sense heritability was high for both OAC and LAC, with general heritabilities being more visible for OAC and G×E interaction heritability being more important for LAC at most development times. The predicted genetic effects indicated that while most parents (with the exception of Youcai 601, Zhongyou 821 and Eyouchangjia) could be used for improving OAC of offspring, Double 20-4 was the most appropriate for improving LAC due to its better stability and positive values across environments at most development times.

A new model is presented that relates the numbers of bolters in sugar-beet crops to an intensity of vernalization calculated as the accumulated number of hours between sowing and the end of June that temperatures were between 0 and 13°C, with each temperature within this range differentially weighted for its vernalizing effect. The model allows varieties to be characterized in terms of a threshold number of vernalizing hours needed to induce bolting (the vernalization requirement) and the increase in the proportion of bolted plants with each additional 10 vernalizing hours accumulated above this vernalizing threshold (the bolting sensitivity). When parameterized for variety, the model allows the level of bolting to be predicted for crops sown on specific dates in particular locations.

Data from variety-assessment trials done at a wide range of locations throughout the main UK sugar-beet growing areas between 1973 and 2006, and from early sown bolting trials done at a few sites between 2000 and 2008, were used to define specific aspects of the model. These included the range and weightings of vernalizing temperatures, the period during which vernalization occurs, and the temperatures likely to cause plants to become devernalized.

The vernalization-intensity bolting model was parameterized and validated using separate subsets of the UK variety-assessment trial data. It was shown to be more discriminating and robust than an existing ‘cool-day’ model, which relates bolting to the number of days from sowing in which the maximum air temperature was below 12°C. Examples are given of the use of the new model to assess the bolting risk associated with early sowing in different regions of the UK, to interpret recent patterns of bolting (especially the large numbers of bolters seen in some commercial crops in 2008), and its potential use as an advisory tool.

Increasingly serious shortages of water make it imperative to improve the efficiency of irrigation in agriculture, horticulture and in the maintenance of urban landscapes. The main aim of the current review is to identify ways of meeting this objective. After reviewing current irrigation practices, discussion is centred on the sensitivity of crops to water deficit, the finding that growth of many crops is unaffected by considerable lowering of soil water content and, on this basis, the creation of improved means of irrigation scheduling. Subsequently, attention is focused on irrigation problems associated with spatial variability in soil water and the often slow infiltration of water into soil, especially the subsoil. As monitoring of soil water is important for estimating irrigation requirements, the attributes of the two main types of soil water sensors and their most appropriate uses are described. Attention is also drawn to the contribution of wireless technology to the transmission of sensor outputs. Rapid progress is being made in transmitting sensor data, obtained from different depths down the soil profile across irrigated areas, to a PC that processes the data and on this basis automatically commands irrigation equipment to deliver amounts of water, according to need, across the field. To help interpret sensor outputs, and for many other reasons, principles of water processes in the soil–plant system are incorporated into simulation models that are calibrated and tested in field experiments. Finally, it is emphasized that the relative importance of the factors discussed in this review to any particular situation varies enormously.

Climate change is now unequivocal, particularly in terms of increasing temperature, increasing CO2 concentration, widespread melting of snow and ice and rising global average sea level, while the increase in the frequency of drought is very probable but not as certain.

However, climate changes are not new and some of them have had dramatic impacts, such as the appearance of leaves about 400 million years ago as a response to a drastic decrease in CO2 concentration, the birth of agriculture due to the end of the last ice age about 11 000 years ago and the collapse of civilizations due to the late Holocene droughts between 5000 and 1000 years ago.

The climate changes that are occurring at present will have – and are already having – an adverse effect on food production and food quality with the poorest farmers and the poorest countries most at risk. The adverse effect is a consequence of the expected or probable increased frequency of some abiotic stresses such as heat and drought, and of the increased frequency of biotic stresses (pests and diseases). In addition, climate change is also expected to cause losses of biodiversity, mainly in more marginal environments.

Plant breeding has addressed both abiotic and biotic stresses. Strategies of adaptation to climate changes may include a more accurate matching of phenology to moisture availability using photoperiod-temperature response, increased access to a suite of varieties with different duration to escape or avoid predictable occurrences of stress at critical periods in crop life cycles, improved water use efficiency and a re-emphasis on population breeding in the form of evolutionary participatory plant breeding to provide a buffer against increasing unpredictability. ICARDA, in collaboration with scientists in Iran, Algeria, Jordan, Eritrea and Morocco, has recently started evolutionary participatory programmes for barley and durum wheat. These measures will go hand in hand with breeding for resistance to biotic stresses and with an efficient system of variety delivery to farmers.

A mechanistic lactation model, based on a theory of mammary cell proliferation and cell death, was studied and compared to the equation of Wood (1967). Lactation curves of British Holstein Friesian cows (176 curves), Spanish Churra sheep (40 curves) and Spanish Murciano–Granadina goats (30 curves) were used for model evaluation. Both models were fitted in their original form using non-linear least squares estimation. The parameters were compared among species and among parity groups within species.

In general, both models provided highly significant fits to lactation data and described the data accurately. The mechanistic model performed well against Wood's 1967 equation (hereafter referred to as Wood's equation), resulting in smaller residual mean square values in more than two-thirds of the datasets investigated, and producing parameter estimates that allowed appropriate comparisons and noticeable trends attributed to shape. Using Akaike or Bayesian information criteria, goodness-of-fit with the mechanistic model was superior to that with Wood's equation for the cow lactation curves, with no significant differences between models when fitted to goat or sheep lactation curves. The rate parameters of the mechanistic model, representing specific proliferation rate of mammary secretory cells at parturition, decay associated with reduction in cell proliferation capacity with time and specific death rate of mammary secretory cells, were smaller for primiparous than for multiparous cows. Greater lactation persistency of cows compared to goats and sheep, and decrease in persistency with parity, were shown to be represented by different values of the specific secretory cell death rate parameter in the mechanistic model. The plausible biological interpretation and fitting properties of the mechanistic model enable it to be used in complex models of whole-cow digestion and metabolism and as a tool in selection programmes and by dairy producers for management decisions.

Sunflower oil, with more than 0·9 of tocopherols in the alpha-tocopherol form, supplies more vitamin E than any other vegetable oil. Thus far, no breeding to increase vitamin E levels in sunflower seeds has been conducted. The objective of the present research was to develop sunflower lines with high and low total seed tocopherol content through evaluation and subsequent selection of a large germplasm collection (952 sunflower entries). A range of variation from 119 to 491 mg/kg was found. Selection conducted from S1 to S4 plant generations allowed the isolation of line IAST-413, with an increased tocopherol content of 467 mg/kg compared to 251 mg/kg in the control line HA89, and line IAST-522, with a reduced tocopherol content of 73 mg/kg. Another accession with potentially high tocopherol content, but completely self-incompatible, was crossed to the line HA89 followed by plant-to-row selection up to the F5 plant generation; it averaged 463 mg/kg compared to 240 mg/kg in HA89. Two field experiments carried out at Córdoba in southern Spain in 2006 and 2007 with different sowing dates confirmed that the increased tocopherol content in the selected lines was consistently expressed across environments.

The majority of cotton produced in Australia is exported. The Australian cotton industry must maintain product quality in order to remain globally competitive. In addition, carbon-conscious consumers need reassurance that the system used to grow the product is environmentally sustainable. The aim of the present study was to estimate greenhouse gas (GHG) emissions due to various farm inputs in three common types of cotton farming systems on the Darling Downs region, southern Queensland. Analysis revealed that GHG emissions for dryland solid-plant and dryland double-skip cotton farming systems are similar, but emissions are much higher for irrigated solid-plant cotton farming (1367, 1274 and 4841 kg CO2e/ha, respectively). However, if comparisons of GHG emissions are based on yield (per tonne), the positions of dryland double-skip farming and dryland solid-plant farming are reversed, but the position of irrigated cotton farming still remains as the highest GHG emitter. If the cotton industry comes under the Australian Government Carbon Pollution Reduction Scheme (CPRS) without any subsidies and preconditions, and with a carbon price of A$25/t CO2e, the costs borne by each system would be A$66.8/t for the irrigated cotton industry, A$39.7/t for the dryland solid-plant cotton industry and A$43.6/t for the dryland double-skip cotton industry. This suggests that irrigated cotton would be more profitable in financial terms but with heavy environmental sustainability costs.

The main objective of the current study was to analyse how water application through a sprinkler irrigation system influences yield of onion (Allium cepa L.), taking into account water application heterogeneity and the effects on theoretical crop evapotranspiration (ETc). Field experiments were conducted on commercial onion plots, irrigated with a permanent sprinkler irrigation system, located in Albacete, Spain, over two irrigation seasons. Two experimental plots were selected each study year: plot A (PA), in which water was applied heterogeneously by using sprinklers with different nozzle combinations, and plot B (PB, used as the reference plot) in which the four sprinklers were maintained with the same nozzle combinations. Both experimental plots were divided into 25 subplots with the aim of studying the water distribution (measured as Christiansen uniformity coefficient (CU)), the impact on the actual evapotranspiration (ETa) and the yield obtained. Irrigation was scheduled using a daily simplified water balance method within the root area following the approach of the Food and Agriculture Organization. In the present study, sprinkler irrigation in PA resulted in lower CU (65–82% lower in 2002 and 59–79% lower in 2005) compared with PB (78–92% lower in 2002 and 79–93% lower in 2005). Between 30 May and 18 August 2002, the estimated crop water requirements in PA in the absence of water deficit was 22 mm over the accumulated value of ETc (491 v. 469 mm), while estimated crop water requirements under water deficit were 187 mm below ETc (282 v. 469 mm). In 2005, between 29 May and 25 August, ETa without water deficit was more similar to ETc (458 v. 444 mm) but Eta under water deficit was 242 mm. The greater uniformity of water distribution in PB was translated into a greater uniformity of yield distribution. A smaller range in yield was observed in PB when compared with PA. No statistically significant differences were observed between PA and PB in the crop quality parameters bulb moisture content, total soluble solids, pH and total acidity.

Models that accurately describe and predict growth and nutrient utilization of fish can be useful in developing strategies to improve the economic and environmental sustainability of aquaculture operations. Current bioenergetics models are not sufficiently flexible to be applied to the wide range of conditions encountered in aquaculture. There is a need to move from bioenergetics approaches to more mechanistic approaches based on nutrient utilization by fish. A non-ruminant nutrient-based growth model has been successfully used in pig production. The model explicitly describes the utilization of energy-yielding nutrients and metabolites for body protein deposition (Pd) and body lipid deposition (Ld) at the whole animal level. Partitioning of intake of energy-yielding nutrients between Pd and Ld is governed by a minimum ratio (minLP) of the body lipid mass (L) to protein mass (P), a maximum daily rate of Pd (PdMax), or maximum efficiency of using intake of the first limiting dietary essential amino acid (AA) for body Pd. The growth model was adapted to rainbow trout (Oncorhynchus mykiss (Walbaum 1792)) through parameterization and various modifications consistent with its framework. The fish nutrient-based model was evaluated by comparing model simulations with data from various experiments carried out with rainbow trout. Significant discrepancies between model predictions and experimental observations were observed. The model predicted energy retention well but did not always accurately predict growth rate, nor Pd and Ld. Overall, the model underestimated growth rate (expressed as thermal-unit growth coefficient (TGC)) by 37% and Pd by 15% and overestimated Ld by 13%. These discrepancies are probably attributable to differences in nutrient utilization and partitioning mechanisms between fish and pigs. The development of more reliable models requires better understanding of the nutritional and endogenous determinants of fish growth.

The objectives of the current study were to quantify the individual variation in daily milk yield response to concentrate intake during early lactation and to assess the economic prospects of exploiting the individual variation in milk yield response to concentrate intake. In an observational study, data from 299 cows on four farms in the first 3 weeks of the lactation were collected. Individual response in daily milk yield to concentrate intake was analysed by a random coefficient model. Marked variation in individual milk yield response to concentrate intake was found on all four farms. An economic simulation was carried out, based on the estimated parameter values in the observational study. Individual optimization of concentrate supply is compared with conventional strategies for concentrate supply based on averaged population response parameters. Applying individual economic optimal settings for concentrate supply during early lactation, potential economic gain ranges from €0·20 to €2·03/cow/day.

The reality of climate change has rarely been questioned in Europe in the last few years as a consensus has emerged amongst a wide range of national to local environmental and resource policy makers and stakeholders that climate change has been sufficiently demonstrated in a number of sectors. A number of site-based studies evaluating change of attainable yields of various crops have been conducted in Central Europe, but studies that evaluate agroclimatic potential across more countries in the region are rare. Therefore, the main aim of the present study was to develop and test a technique for a comprehensive evaluation of agroclimatic conditions under expected climate conditions over all of Central Europe with a high spatial resolution in order to answer the question posed in the title of the paper ‘Is rainfed crop production in central Europe at risk?’ The domain covers the entire area of Central Europe between latitudes 45° and 51·5°N and longitudes 8° and 27°E, including at least part of the territories of Austria, the Czech Republic, Germany, Hungary, Poland, Romania, Slovakia, Switzerland and Ukraine. The study is based on a range of agroclimatic indices that are designed to capture complex relations existing between climate and crops (their development and/or production) as well as the agrosystems as a whole. They provide information about various aspects of crop production, but they are not meant to compete with other and sometimes more suitable tools (e.g. process-based crop models, soil workability models, etc.). Instead, the selected indices can be seen as complementary to crop modelling tools that describe aspects not fully addressed or covered by crop models for an overall assessment of crop production conditions. The set of indices includes: sum of effective global radiation, number of effective growing days, Huglin index, water balance during the period from April to June (AMJ) and during the summer (JJA), proportion of days suitable for harvesting of field crops in June and July, and proportion of days suitable for sowing in early spring as well as during the autumn. The study concluded that while the uncertainties about future climate change impacts remain, the increase in the mean production potential of the domain as a whole (expressed in terms of effective global radiation and number of effective growing days) is likely a result of climate change, while inter-annual yield variability and risk may also increase. However, this is not true for the Pannonian (the lowlands between the Alps, the Carpathian Mountains and the Dinaric Alps) and Mediterranean parts of the domain, where increases in the water deficit will further limit rainfed agriculture but will probably lead to an increase in irrigation agriculture if local water resources are dwindling. Increases in the severity of the 20-year drought deficit and more substantial water deficits during the critical part of the growing season are very likely over the central and western part of the domain. Similarly, the inter-annual variability of water balance is likely to increase over the domain. There is also a chance of conditions for sowing during spring deteriorating due to unfavourable weather, which might increase the preference given to winter crops. This is already likely due to their ability to withstand spring drought stress events. Harvesting conditions in June (when harvest of some crops might take place in the future) are not improving beyond the present level, making the planning of the effective harvest time more challenging. Based on the evidence provided by the present study, it could be concluded that rainfed agriculture might indeed face more climate-related risks, but the overall conditions will probably allow for acceptable yield levels in most seasons. However, the evidence also suggests that the risk of extremely unfavourable years, resulting in poor economic returns, is likely to increase.

Agricultural crop management decisions often require data on hydraulic properties of soils. Little information is available on hydraulic properties of clay soils that are impounded by rainwater (known as ‘Haveli’ lands) every year during the monsoon season in large tracts of Madhya Pradesh in India. Estimating hydraulic properties using global pedotransfer functions (PTFs) is one possible way to collect such information. Rules in the widely used global PTF Rosetta were executed to obtain estimates of two important hydraulic properties, namely soil water retention characteristics (SWRC) and saturated hydraulic conductivity (Ks). SWRC estimates obtained with maximum input (particle size distribution, bulk density, field capacity and permanent wilting point) in Rosetta were relatively closer to the laboratory-measured data as compared with the estimates obtained with lower levels of input. Root mean square error (RMSE) of estimates ranged from 0·01 to 0·05 m3/m3. Hierarchical PTFs to predict Ks from basic soil properties were derived using statistical regression and artificial neural networks. Evaluation of these indicated that neural PTFs were acceptable and hence could be used without loss of accuracy.

Biofuels can reduce greenhouse gas (GHG) emissions by replacing fossil fuels. However, the energy yield from agronomic crops varies due to local climate, weather and soil variability. A variation in the yield of raw material used (feedstock) could also cause variability in GHG reductions if biofuels are used. The goal of the present study was to determine the net reduction of GHG emissions if ethanol from wheat produced in different regions of the south-eastern USA is used as an alternative to gasoline from fossil fuel sources. Two scenarios were investigated; the first included ethanol produced from grain only, and the second included ethanol produced from both grain and wheat straw. Winter wheat yield was simulated with the Cropping System Model (CSM)-CERES-Wheat model for climate, soil and crop management representing six counties in the following USA states: Alabama, Florida and Georgia. Ethanol production was determined from the simulated grain and straw yields together with fixed grain and straw yield ethanol ratios. Subsequently, net reductions in GHG emissions were determined by accounting for the emissions from the replaced gasoline, and by animal feed and electricity that were replaced by ethanol processing co-products. Greenhouse gases that were emitted in the ethanol production chain were also taken into account. Across all locations, the reduction in GHG emissions was 187 g CO2-equivalents/km in the grain-only scenario and 208 g CO2-equivalents/km in the grain and straw scenario. The reductions in GHG emissions varied significantly between locations and growing seasons within the two scenarios. Similar approaches could be applied to assess the environmental impact of GHG emissions from other biofuels.

Super-sweet maize (shrunken2, sh2) has a longer post-harvest life than standard sweetcorn (sugary1, su1), but is less well-adapted to cold conditions. The objective of the present work was to determine if the replacement of su1 by sh2 alters the combining abilities of sweetcorn inbreds for adaptation to early planting under cold conditions. Two diallel sets of su1 and sh2 near-isogenic inbred lines were evaluated in a cold chamber and by early field planting. For most of the traits related to adaptation, except silking date, there were significant mutant×genotype interactions and the estimates of general combining ability (GCA) of each version of the same inbred were different, probably due to epistasis. Therefore, to widen the genetic base of the super-sweet germplasm for adaptation, conversion of the earliest su1 inbreds to sh2, ignoring other characteristics such as emergence or early vigour in early planting or cold tests, is proposed.

The objective of the current study was to apply the Vitti–Dias model to investigate phosphorus (P) metabolism in growing pigs fed a diet supplemented with microbial phytase. The basal diet contained maize, defatted rice bran, vegetable oil, soybean meal, limestone, salt and a vitamin and mineral mix. There was no inorganic P in the diet and phytase was added at levels of 253, 759, 1265 and 1748 phytase units (PU)/kg of feed. The compartmental model included four pools of P: (1) gut lumen, (2) plasma, (3) bone and (4) soft tissue. A single dose of 32P was administered, and specific radioactivity was measured in plasma, faeces, bone and soft tissue (muscle, heart, liver and kidney) at different times post-dosing for calculation of P flows between pools. Total P absorbed showed a negative relationship with total P excreted in faeces and was strongly correlated with bone P retention, suggesting that absorbed P was channelled to bone to address its physiological growth. Average efficiency of metabolic utilization of absorbed P was estimated to be 0·94, with 0·52 g/g of total net P balance being accreted in bone and the rest in soft tissue (including muscle and some vital organs). The Vitti–Dias model provided suitable representation of P interchange between compartments (in particular, flows between gut and plasma and partitioning of available P between bone and soft tissue), resulting in estimates of P flows comparable with values calculated from balance data.

Climate represents one of the main inputs necessary for plants to complete their vegetative–productive cycle, having a direct effect on the onset and duration of phenological stages and development of crops. Equally important are its indirect effects, affecting field operations such as the application of fertilizer, pruning and crop protection, finally determining the yield.

In the present study, phenological stages of the Sangiovese grapevine for the production of Nobile di Montepulciano wine were analysed and related to historical series of meteorological information (since 1970 in Tuscany, Italy). Weather conditions were described through large-scale meteorological information; in particular geopotential height at the 500 hPa level (500 hPa GPH) and North Atlantic Oscillation (NAO) index were considered. All data were provided by the National Oceanic and Atmospheric Administration-Cooperative Institute for Research in Environmental Sciences (NOAA-CIRES) Climate Diagnostics Center, Boulder, Colorado, USA, available from the NOAA-CIRES website (http://www.cdc.noaa.gov/) and processed by the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis Project. Conventional meteorological data, such as air temperature and cumulated rainfall, from ground weather stations were also used.

The effects of meteorological parameters on crop phenology (bud-break, flowering and harvest time) were investigated by means of regression analysis, while teleconnections between phenological data and large-scale meteo-climatological data were analysed through correlation maps created using the interactive plotting and analysis link from the NOAA-CIRES website (http://www.cdc.noaa.gov). All correlations were calculated on a monthly to a multi-monthly basis, and also in relation to the different physiological stages of the crop, from 1970 to 2006.

The climate change and variability impact on the crop was investigated by trend analysis of meteorological information and its effect on the onset of grapevine phenological stages.

The results demonstrated that large-scale meteorological information has a significant effect on the onset of the phenological stages of grapevine. In particular, winter NAO was negatively correlated with bud-break and flowering dates, while GPH of February–March, March–May and May–September were negatively correlated with bud-break, flowering and harvest dates, respectively. The trend analysis demonstrated that the change and variability of climate, due to global warming, directly affects the development of grapevine leading to an anticipation of all considered phenophases.

A dynamic mathematical model of a closed mammary system in lactating cows was developed to incorporate the setpoint concept of tissue activity, using equations where nutrient supply and absorption are locally regulated so as to maintain a given rate of milk protein yield. The model consists of 12 differential equations, 11 of which are concerned with intracellular biochemical compartments and one describes the volume of tissue actively perfused by blood (AP). The intracellular compartments are: amino acids (AAs), acetate, fatty acids (FAs), β-hydroxybutyrate, glucose-6-phosphate, fructose-6-phosphate, phospho-glyceraldehyde, pyruvate, mitochondrial acetyl-CoA, adenosine triphosphate (ATP) and adenosine diphosphate (ADP). The model simulates mechanisms which are aimed at reproducing and, thereby, explain variations in mammary plasma flow (MPF) observed experimentally. The AP changes according to variations in the metabolic status or in the metabolic requirements of the gland. Should the tissue energy charge (i.e. ATP/ADP ratio) exceed a baseline ratio, then AP decreases and consequently MPF declines. Conversely, when milk protein yield increases, AP increases and MPF rises. In the present model, AA uptake by the mammary gland is inhibited by intracellular AAs. It is also assumed that, when milk protein yield diminishes, the respiratory chain and ATP synthesis become uncoupled and consequently ATP yield is reduced. Model evaluation included behavioural analysis and sensitivity analysis. Behaviour analysis was conducted to test whether the model mechanisms reproduced the scenarios from which the model hypotheses were developed, and took into consideration: an increase in arterial glucose concentration (HIGLC), increases in arterial concentrations of non-esterified FAs, triacylglycerol and β-hydroxybutyrate (HIFAT), a 50% reduction of arterial histidine concentration (LOHIS), and a hyperinsulinaemic euglycaemic clamp (HIINS). Both HIGLC and HIFAT resulted in a decrease in MPF and in milk protein yield; moreover, the scenario HIGLC also produced a notable decrease in the extraction of glucose. The scenario LOHIS resulted in increased MPF and extraction of His from plasma. However these responses were not sufficiently large to prevent a severe reduction of milk protein yield which was accompanied by a reduction in the extraction of other essential AAs. The scenario HIINS resulted in an increase of MPF and of milk protein yield, in the extraction of His and of other essential AAs. Model sensitivity analysis focused on variation of both affinity and inhibition constants of some of the Michaelis–Menten equations. Improvements in model structure and directions for future research suggested by the modelling analysis are discussed.

Genetic variability in carrots is a consequence of allogamy, which leads to a high level of inbreeding depression, affecting the development of new varieties. To understand the extent of genetic variability in 40 elite indigenous breeding lines of subtropical carrots, 48 DNA markers consisting of 16 inter simple sequence repeats (ISSRs), 10 universal rice primers (URPs), 16 random amplification of polymorphic DNA (RAPD) and six simple sequence repeat (SSR) markers were used. These 48 markers amplified a total of 591 bands, of which 569 were polymorphic (0·96). Amplicon size ranged from 200 to 3500 base pairs (bp) in ISSR, RAPD and URPs markers and from 100 to 300 bp in SSR markers. The ISSR marker system was found to be most efficient with (GT)n motifs as the most abundant SSR loci in the carrot genome. The unweighted pair group method with arithmetic mean (UPGMA) analysis of the combined data set of all the DNA markers obtained by four marker systems classified 40 genotypes in two groups with 0·45 genetic similarity with high Mantel matrix correlation (r=0·92). The principal component analysis (PCA) of marker data also explained 0·55 of the variation by first three components. Molecular diversity was very high and non-structured in these open-pollinated genotypes. The study demonstrated for the first time that URPs can be used successfully in genetic diversity analysis of tropical carrots. In addition, an entirely a new set of microsatellite markers, derived from the expressed sequence tags (ESTs) sequences of carrots, has been developed and utilized successfully.

A dynamic, mechanistic model of enteric fermentation was used to investigate the effect of type and quality of grass forage, dry matter intake (DMI) and proportion of concentrates in dietary dry matter (DM) on variation in methane (CH4) emission from enteric fermentation in dairy cows. The model represents substrate degradation and microbial fermentation processes in rumen and hindgut and, in particular, the effects of type of substrate fermented and of pH on the production of individual volatile fatty acids and CH4 as end-products of fermentation. Effects of type and quality of fresh and ensiled grass were evaluated by distinguishing two N fertilization rates of grassland and two stages of grass maturity. Simulation results indicated a strong impact of the amount and type of grass consumed on CH4 emission, with a maximum difference (across all forage types and all levels of DMI) of 49 and 77% in g CH4/kg fat and protein corrected milk (FCM) for diets with a proportion of concentrates in dietary DM of 0·1 and 0·4, respectively (values ranging from 10·2 to 19·5 g CH4/kg FCM). The lowest emission was established for early cut, high fertilized grass silage (GS) and high fertilized grass herbage (GH). The highest emission was found for late cut, low-fertilized GS. The N fertilization rate had the largest impact, followed by stage of grass maturity at harvesting and by the distinction between GH and GS. Emission expressed in g CH4/kg FCM declined on average 14% with an increase of DMI from 14 to 18 kg/day for grass forage diets with a proportion of concentrates of 0·1, and on average 29% with an increase of DMI from 14 to 23 kg/day for diets with a proportion of concentrates of 0·4. Simulation results indicated that a high proportion of concentrates in dietary DM may lead to a further reduction of CH4 emission per kg FCM mainly as a result of a higher DMI and milk yield, in comparison to low concentrate diets. Simulation results were evaluated against independent data obtained at three different laboratories in indirect calorimetry trials with cows consuming GH mainly. The model predicted the average of observed values reasonably, but systematic deviations remained between individual laboratories and root mean squared prediction error was a proportion of 0·12 of the observed mean. Both observed and predicted emission expressed in g CH4/kg DM intake decreased upon an increase in dietary N:organic matter (OM) ratio. The model reproduced reasonably well the variation in measured CH4 emission in cattle sheds on Dutch dairy farms and indicated that on average a fraction of 0·28 of the total emissions must have originated from manure under these circumstances.