One of the main problems in estimating the effects of climate change on crops is the identification of those factors limiting crop growth in a selected environment. Previous studies have indicated that considering simple trends of either precipitation or temperature for the coming decades is insufficient for estimating the climate impact on yield in the future. One reason for this insufficiency is that changes in weather extremes or seasonal weather patterns may have marked impacts.

The present study focuses on identifying agroclimatic parameters that can identify the effects of climate change and variability on winter wheat yield change in the Pannonian lowland. The impacts of soil type under past and future climates as well as the effect of different CO2 concentrations on yield formation are also considered. The Vojvodina region was chosen for this case study because it is a representative part of the Pannonian lowland.

Projections of the future climate were taken from the HadCM3, ECHAM5 and NCAR-PCM climate models with the SRES-A2 scenario for greenhouse gas (GHG) emissions for the 2040 and 2080 integration periods. To calibrate and validate the Met&Roll weather generator, four-variable weather data series (for six main climatic stations in the Vojvodina region) were analysed. The grain yield of winter wheat was calculated using the SIRIUS wheat model for three different CO2 concentrations (330, 550 and 1050 ppm) dependent on the integration period. To estimate the effects of climatic parameters on crop yield, the correlation coefficient between crop yield and agroclimatic indices was calculated using the AGRICLIM software. The present study shows that for all soil types, the following indices are the most important for winter wheat yields in this region: (i) the number of days with water and temperature stress, (ii) the accumulated precipitation, (iii) the actual evapotranspiration (ETa) and (iv) the water deficit during the growing season. The high positive correlations between yield and the ETa, accumulated precipitation and the ratio between the ETa and reference evapotranspiration (ETr) for the April–June period indicate that water is and will remain a major limiting factor for growing winter wheat in this region. Indices referring to negative impact on yield are (i) the number of days with a water deficit for the April–June period and (ii) the number of days with maximum temperature above 25 °C (summer days) and the number of days with maximum temperature above 30 °C (tropical days) in May and June. These indices can be seen as indicators of extreme weather events such as drought and heat waves.

Current agricultural practices rely on crops with developmental phenologies adapted to local climate, photoperiods and soils; however, global climate change will alter some abiotic factors (e.g. temperature and precipitation). Previously adapted varieties may be poorly prepared for these changing conditions, if such conditions induce mismatched phenologies. Crops that depend on cross-pollination and synchronous flowering may be most susceptible, e.g. monoecious plants have separate male and female flowers, and changes in flowering synchrony may alter yield. Using genetically diverse (open-pollinated (OP)) and genetically homogeneous (hybrid) varieties of a monoecious crop, courgette, also known as zuchinni (Cucurbita pepo), phenological responses to experimentally manipulated moisture conditions were explored in an agricultural context. Under drier and wetter conditions, the hybrid courgette plants shifted towards a male-biased floral sex ratio due to the reduced production of female flowers. However, flowering synchrony and fruit production were unaffected by moisture treatment in both varieties. The hybrid and OP varieties differed in many traits related to floral sex ratios, phenology, synchrony and fruit production. Further, the OP variety displayed more phenotypic variation than the hybrid in many traits. Being in a population context rather than relying on self-pollination increased the availability of potential mates for a given female flower in both the hybrid and, particularly, the OP variety. Thus, the increased genetic diversity found in OP v. hybrid varieties may buffer the possible environmental effects on flowering synchrony within a cropping context. Finally, the likelihood of female flowers setting fruit increased with the number of male flowers within a population, and the rate of increase was higher in the hybrid variety. In summary, climate change is predicted to reduce investment in female function in some monoecious crops and genetically diverse varieties may play an important role in maintaining reproductive synchrony in altered environments.

The present study investigates regional climate change impacts on agricultural crop production in Central and Eastern Europe, including local case studies with different focuses in Austria, the Czech Republic and Slovakia. The area studied experiences a continental European climate and is characterized by strong climatic gradients, which may foster regional differences or trends in the impacts of climate change on agriculture. To study the regional aspects and variabilities of climate change impacts on agriculture, the effect of climate change on selected future agroclimatic conditions, crop yield and variability (including the effect of higher ambient CO2 concentrations) and the most important yield limiting factors, such as water availability, nitrogen balance and the infestation risks posed by selected pests were studied. In general, the results predicted significant agroclimatic changes over the entire area during the 21st century, affecting agricultural crop production through various pathways. Simulated crop yield trends confirmed past regional studies but also revealed that yield-limiting factors may change from region to region. For example, pest pressures, as demonstrated by examining two pests, are likely to increase due to warmer conditions. In general, higher potentials for cereal yield increase are seen for wetter and cooler regions (i.e. uplands) than for the drier and warmer lowlands, where yield potentials will be increasingly limited by decreasing crop water availability and heat under most scenarios. In addition, yield variability will increase during the coming decades, but this may decrease towards the end of the 21st century. The present study contributes to the interpretation of previously conducted climate change impact and adaptation studies for agriculture and may prove useful in proposing future research in this field.

The objective of the present study was to compare the performance of seven different, widely applied crop models in predicting heat and drought stress effects. The study was part of a recent suite of model inter-comparisons initiated at European level and constitutes a component that has been lacking in the analysis of sources of uncertainties in crop models used to study the impacts of climate change. There was a specific focus on the sensitivity of models for winter wheat and maize to extreme weather conditions (heat and drought) during the short but critical period of 2 weeks after the start of flowering. Two locations in Austria, representing different agro-climatic zones and soil conditions, were included in the simulations over 2 years, 2003 and 2004, exhibiting contrasting weather conditions. In addition, soil management was modified at both sites by following either ploughing or minimum tillage. Since no comprehensive field experimental data sets were available, a relative comparison of simulated grain yields and soil moisture contents under defined weather scenarios with modified temperatures and precipitation was performed for a 2-week period after flowering. The results may help to reduce the uncertainty of simulated crop yields to extreme weather conditions through better understanding of the models’ behaviour. Although the crop models considered (DSSAT, EPIC, WOFOST, AQUACROP, FASSET, HERMES and CROPSYST) mostly showed similar trends in simulated grain yields for the different weather scenarios, it was obvious that heat and drought stress caused by changes in temperature and/or precipitation for a short period of 2 weeks resulted in different grain yields simulated by different models. The present study also revealed that the models responded differently to changes in soil tillage practices, which affected soil water storage capacity.

Cultivar selection is a dominant factor in crop production to obtain high yield. While previous studies have evaluated a range of impacts and adaptation of climate change (CC) on crop yield, few studies have focused on evaluating the effectiveness of changing cultivars with different vernalization requirements as an adaptation. In the present study, mean and inter-annual variability of yield were quantified for three winter wheat cultivar types at three ecological sites (Shangzhuang in Beijing, Quzhou in Hebei and Huangfanqu in Henan) in the North China Plain, by linking a crop model and the outputs of Providing Regional Climates for Impacts Studies (PRECIS) for both the baseline (1961–90) and future SRES scenarios A2 and B2 (2070–2100). The results showed that a warming trend prolonged the length of the vegetative growth period of local cultivars through reduced vernalization, generally leading to a negative impact on yield. However, the introduction of cultivars with relatively lower vernalization demands from warmer southern to cooler northern regions could be an effective adaptation strategy to offset the negative impact of climatic change. Adjustment in cultivars increased yield at Shangzhuang and maintained it at Quzhou and Huangfanqu. Elevated CO2 would significantly increase yield in the future with or without considering the sensitivities of the selected cultivars. The inter-annual variability of yield generally increased in the A2 scenario, but decreased in the B2 scenario. Overall, winter wheat with semi-winter types or weak-winter types would grow preferentially, while cultivars with winter types would probably be reduced in future.

The present paper demonstrates the development of interspecific hybrids between Manihot esculenta Crantz ssp. esculenta (Mee) and M. esculenta Crantz ssp. flabellifolia (Mef) and paternity analysis using microsatellite markers [simple sequence repeat (SSR)]. Three Mef accessions (FLA005, FLA025V and FLA029V) were used for crosses with varieties of Mee: Saracura, Aipim Bravo, COL 1725, Aipim Rosa, Abóbora, Paraná and PER334. The paternity of the interspecific hybrids was investigated using 24 SSRs. The observed heterozygosity (Ho), polymorphic information content (PIC), probability of identity (PI) and paternity exclusion (PE) were evaluated. The rate of breeding success varied from 17 to 92%, and an average of two pollinations were required for each generated hybrid plant. The Ho value ranged from 0·11 to 0·92, and the PIC value ranged from 0·12 to 0·59. The uneven distribution of allele frequencies was accompanied by a high PI average (0·56). However, the combined PE for 21 loci was 0·99, which allows for the determination of the paternity of the hybrids with good discriminatory power. Of the 74 hybrids evaluated, 0·82 had their paternity confirmed using microsatellite markers. Discriminant analysis of principal components (DAPC) indicated the presence of eight clusters, of which, one was composed of only Mef varieties and the supposed hybrid Fla52Sar-H7, which was a product of apomixis. The parent Mee and hybrids were allocated in the other seven clusters. The data obtained demonstrate that SSR markers can be routinely used in breeding programmes to verify the paternity of interspecific crosses of cassava.

The environmental concern about diffuse pollution from nitrogen (N) fertilizers has led to increased research on the diagnosis of crop N status. The SPAD chlorophyll (Chl) meter is the most commonly used tool for rice (Oryza sativa L.) N status diagnosis, but measurements are conducted at a specific point and readings are affected by different leaf positions. Many measurements per plant must be taken in order to increase the accuracy of N status diagnosis, which limits its application. The present paper attempts to determine rice N status at the canopy level using Multiplex®, a new hand-held optical fluorescence sensor. The fluorescence emission of rice leaves under light excitation was utilized by Multiplex® to non-destructively assess rice leaf Chl and phenolic compound content. A field experiment was conducted in 2011 using a completely randomized split-plot design, with main-plot treatments being six N fertilizer application rates and subplot treatments being different plant densities. Leaf Chl and phenolic compounds were evaluated using the ratio of far-red fluorescence (FRF) to red fluorescence (RF) emission under red light excitation (simple fluorescence ratio, SFR_R) (R2 = 0·35, P < 0·01) and the ratio of decadic logarithm of red to ultra-violet (UV) fluorescence emission (R2 = 0·30, P < 0·01), respectively. Both SPAD reading and fluorescence-based indices including flavonoids (FLAV), nitrogen balance index (NBI_R) and SFR_R could be used to predict rice leaf N contents. The canopy FLAV, SFR_R and NBI_R were all highly correlated to average SPAD readings (R2 > 0·70 in most cases, P < 0·01). Therefore, Multiplex® can be used as an alternative to SPAD to determine rice N status in paddy fields.

The use of selective breeding to reduce methane (CH4) emissions is an option for reducing carbon emissions from livestock farming systems. The current study models UK lowland terminal sire (meat) sheep production systems to study the impacts of including CH4 emissions and/or feed intake as breeding objective and selection criteria traits in sheep breeding systems, on the predicted genetic responses of production traits. Nine breeding goal traits and 15 selection index traits were modelled in a Suffolk breeding flock with a deterministic model of trait economic values (EVs). Methane was given an EV equivalent to a carbon price varying from £0 to £538/t CO2-e. When currently used selection indices added feed intake as a breeding objective, CH4 reductions of 0·15 and 0·05 kg CO2-e/sheep/year were predicted when intake was, or was not, measured, respectively, with a zero carbon price. These reductions were relatively insensitive to carbon price. Overall economic (index) response to selection was insensitive to carbon price and increased with higher feed costs, when neither CH4 nor feed intake was measured. When CH4 and/or intake were measured, overall economic responses increased with higher carbon prices, when feed costs were zero. Methane and intake responses were only sensitive to carbon price (whether CH4 and intake were measured or not) when feed costs were zero. To achieve a desired reduction of 0·1 kg CH4/head/year (cumulative 30% reduction in 20 years) when feed costs were zero, CH4 and/or intake needed to be measured. If CH4 was measured, carbon price needed to be >£50/t CO2-e; if intake was measured carbon price needed to be >£100/t CO2-e. Including feed intake as a breeding objective trait with non-zero feed costs should assist in reducing CH4 in breeding programmes. Selective breeding of terminal sheep by index selection has the potential to contribute a reduction of up to 0·27 kg CO2-e per ewe per annum, depending on the traits measured, feed costs and carbon price. This would help meet the UK Government's greenhouse gas reduction targets for farming systems.

The current investigation analysed the applicability of support vector machines (SVMs), a sub-discipline in the field of artificial intelligence, for the early detection of mastitis. Data used were recorded on the Karkendamm dairy research farm (Kiel, Germany) between January 2010 and December 2011. Data from 215 cows in their first 200 days in milk (DIM) were analysed. Mastitis was specified according to veterinary treatments and defined as disease blocks. The two different definitions used varied solely in the sequence length of the blocks. Only the days before the treatment were included in the blocks. The following parameters were used for the recognition of mastitis: milk electrical conductivity (MEC), milk yield (MY), stage of lactation, month, mastitis history during lactation, deviation from the 5-day moving average of MEC as well as MY, and the 5-day moving standard deviations of the same traits. To develop and verify the model of the SVMs, the mastitis dataset was divided into training and test datasets. Support vector machines are tools for statistical pattern recognition, focusing on algorithms capable of learning and adapting the structure of the input parameters based on the training dataset. The results show that the block sensitivity of mastitis detection considering both mastitis definitions was 84·6%, while specificity was 71·6 and 78·3%, respectively. Showing feasible features for pattern recognition of biological data, SVMs can principally be applied for disease detection. However, without further performance improvement or different study settings (e.g. other indicator variables) SVMs cannot be easily implemented into practical usage.

A two-stage in vitro procedure was used for assessing the activity of parotid saliva to enhance rumen digestion of tanniniferous browse foliage. The procedure consisted of pre-incubation in saliva for 4 h at 39 °C followed by incubation in diluted buffered rumen fluid. Using this procedure, a study was conducted to examine the effects of pre-incubation in sheep (SS), quebracho-supplemented sheep (qSS) and goat (GS) parotid saliva or in McDougall's artificial saliva (AS, used as control) on in vitro rumen fermentation kinetics (estimated using the gas production technique) of browse foliage from six shrub species (Cytisus scoparius, Genista florida, Rosa canina, Quercus pyrenaica, Cistus laurifolius and Erica australis) collected over two seasons (spring and autumn), thus varying the in vitro digestibility (from 0·597 to 0·903) and tannin contents (from 3 to 130 g tannic acid equivalent/kg dry matter (DM)). Saliva was collected from four sheep and four goats fed alfalfa hay, and from four sheep fed the same alfalfa hay but supplemented with quebracho (rich in condensed tannins) for 60 d, through a cannula inserted in the parotid duct, and rumen fluid was always from sheep fed alfalfa hay. The extent of degradation when browse foliage was pre-incubated in qSS was similar to that observed with control AS (0·449 v. 0·452, respectively), and 8% less than the value with pre-incubation in SS (0·490). In vitro fermentation kinetics (gas production parameters) of browse foliage were not significantly enhanced with pre-incubation in qSS compared with SS, whereas in vitro digestibility and extent of degradation in the rumen were significantly reduced with qSS compared with SS. After pre-incubation in sheep and goat saliva, the extent of browse foliage degradation was significantly increased by 4–8% compared with pre-incubation in the control AS. Fermentation efficiency of browse foliage was increased (P<0·05) with pre-incubation in GS compared with SS. Sheep or goat saliva may have some activity to affect in vitro rumen fermentation of the foliage samples incubated, enhancing extent of degradation of tannin-rich browse. However, a relationship between the magnitude of this effect and the tannin content of the browse foliage could not be established, suggesting that sheep and goat saliva may not be particularly important in neutralizing tannins.