Global nitrous oxide (N2O) inventory estimates for pasture systems are refined based on measurements of N2O loss from simulated urine patches. A variety of methods are used for patch simulation but they frequently use a uniform wetted area (UWA), often smaller than a bovine urine patch. However, natural patches follow non-uniform infiltration patterns expanding naturally from a point of deposit with a non-wetted zone of influence. Using 2 litres of urine the UWA method was compared, using a 0·156 m2 collar, with a naturally expanding effective area (NEEA) method, using a 0·462 m2 collar under high (HL) and low (LL) N2O loss conditions. The method chosen affects urine nitrogen (N) loading to the soil. Under HL the UWA method induced a N2O-N loss of 280·6 mg/patch, significantly less than the 434·8 mg/patch loss for the NEEA method, for the same simulated urination. Under LL there was no method effect. Efforts should be made to employ patch simulation methods, which mimic natural deposits and can be achieved, at least in part, by: (a) Using a urine volume and N content similar to that of the animal of interest. (b) Allowing natural infiltration of the chosen urine volume to permit tapering towards the edges. (c) Measuring from the zone of influence in addition to the wetted area, i.e. the patch effective area.

Spodoptera frugiperda, or the fall armyworm (FAW) (Lepidoptera: Noctuidae), is an endemic and important agricultural pest in America. Several outbreaks have occurred with losses estimated at millions of dollars. Insects are affected by climate factors, and climate change may affect geographical range, growth rate, abundance, survival, mortality, number of generations per year and other characteristics. These effects are difficult to project due to the complex interactions among insects, hosts and predators. The aim of the current research is to project the impact of climate change on future suitability for the expansion and final range of FAW as well as highlight the risk of damage due to the pest under current and future conditions. The modelling was carried out using two general circulation models (GCMs), CSIRO Mk3.0 and MIROC-H, for 2050 and 2100 under the A2 Special Report on Emissions Scenarios (SRES), using the known distribution of the species and the CliMond meteorological database. The possible number of generations was estimated to exceed five in the south-eastern USA by 2100. A unique modelling approach linking environmental suitability and number of generations was developed to project the risks of FAW damage. The results show changes in suitability and risk across America, with an increase in the northern hemisphere and decreases or extinction in the southern hemisphere, except for southern Brazil, Uruguay, Paraguay and northern Argentina, which indicate high future levels of risk. The current study highlights the possible extinction of a tropical pest in areas near the Equator. The two GCMs both projected increases in the low-risk category of 40% by 2050 and 23% by 2100, with the medium- and high-risk categories decreasing by >50% by 2050 and >39% by 2100, compared with the current risk. In general, agricultural pest management may become more challenging under future climate change and variation, and thus, understanding and quantifying the possible impacts of FAW under future climate conditions is essential for the future economic production of crops.

Conservation agriculture (CA) is inadequately developed for rice-based cropping systems widely practiced in Bangladesh. The current drawback is the implementation of CA for all crops including rice (Oryza sativa L., ecotype ‘transplanted aman’ [T. aman]) to increase rice–wheat (Triticum aestivum L.) rotation productivity. It is important to identify the best combination of tillage types and cropping systems to achieve a high yield of component crops and improve soil health. Three tillage practices, assigned to main experimental plots [namely, zero tillage (ZT), conventional tillage using a rotary tiller (CT) and deep tillage using a chisel plough (DT)] and three different cropping systems, assigned to sub-plots [namely, WFT: wheat–fallow–T. aman, WMT: wheat–mungbean (Vigna radiata L. Wilczek)–T. aman and WDT: wheat–dhaincha (Sesbania rostrata)–T. aman], were tested. After 4 years, ZT under WDT and WMT significantly increased soil organic matter (SOM) at 0–150 mm depth, and these replicates also held the highest levels of total organic carbon. Soil organic carbon (C) increased at a rate of 1.17 and 1.14 t/ha/y in ZT under WDT and WMT, respectively, while CT and DT under WFT were almost unchanged. After 4 years, SOM build-up by the three-crop system (WDT and WMT) under ZT helped conserve soil moisture and improve other soil properties, such as reduction in soil strength and bulk density and increase plant available water content, thus maintaining an optimum soil water infiltration rate. Zero tillage under WMT and WDT showed significant improvements in root mass density of rice and wheat at increased soil depth. The WDT and WMT plots under DT consistently gave the highest yield followed by WDT and WMT under CT, in contrast with ZT under WMT or WDT, which showed the highest improvement in crop yields over the years. In summary, minimum soil disturbance together with incorporation of a legume/green manure crop into the rice–wheat system as well as the retention of their residues increased soil C status, improved soil properties and maximized grain yields.

A great many plantain varieties are cropped in West and Central Africa, and there is a lack of information about their production potential and suitability for cropping system environments. To obtain benchmark data for the production potential of plantain varieties, experimental and modelling approaches were combined to determine intrinsic growth parameters and to increase understanding of factors affecting yield. Five real plantains commonly cropped in Cameroon and representative of plantain group diversity (Batard, Big Ebanga, Essong, French clair and Mbouroukou n°3) and four plantain-like hybrids (CRBP39, D248, D535 and FHIA21) were studied. A process-based growth model (the AAB model) was developed that accounts for specific characteristics of the plantain crop that includes parameters affecting growth, development and yield. Varietal-specific parameters were determined in a field experiment conducted under nearly non-limiting production conditions while general parameters were drawn from the literature. Parameters describing the conversion of intercepted radiation into dry matter were evaluated by model fitting. Photosynthetic efficiency was significantly higher for real plantains than for plantain-like hybrids. The model realistically simulated development, growth and bunch production for five varieties. These results are the first step in developing a useful tool for assessing the suitability of plantain varieties to different environments. The current study highlights the need for greater knowledge of plantain physiology in order to better model plantain growth and develop variety-specific production approaches.

A total economic merit index (Pasture Profit Index, PPI) for perennial ryegrass variety selection was developed to rank perennial ryegrass varieties (Lolium perenne L.) based on their economic potential for grass-based ruminant production systems. The key traits of importance identified were: spring, mid-season (April 11–August 10) and autumn dry matter (DM) yield, first and second cut silage DM yield, grass quality April to July (inclusive) and sward persistency. Variety persistency was quantified by determining the ground score (GS) change across years, which was associated with a yield threshold which triggered sward replacement. Each one-unit decline in GS was associated with a 1683 kg loss in DM yield. Data generated in the Irish recommended list trials for value for cultivation and use were analysed to quantify the relative performance of each variety for each of the aforementioned traits. A previously developed methodology to generate economic values was used with updated price assumptions to develop economic values, which were applied to the analysed performance data of individual varieties. These data were used to estimate the total economic merit of each variety. Thirty-nine varieties were ranked on total economic merit with the highest performing variety (Cv111) generating €213 per ha/year compared with Cv201, which was the lowest ranking variety generating −€31 per ha/year. Use of the PPI provides information to end users in relation to the economic merit of one variety over another, facilitating a more informed decision-making process at farm level.

Flowering and successful pollination in wheat are key determinants of both quantity and quality of grain. Bread wheat line ‘Paragon’, introgressed with single or multiple daylength insensitivity alleles was used to dissect the effects on the timing and duration of flowering within a hierarchical plant architecture. Flowering of wheat plants was observed in a series of pot-based and field experiments. Ppd-D1a was the most potent known allele affecting the timing of flowering, requiring the least thermal time to flowering across all experiments. The duration of flowering for individual lines was dominated by the shift in the start of flowering in later tillers and the number of tillers per plant, rather than variation in flowering duration of individual spikes. There was a strong relationship between flowering duration and the start of flowering with the earliest lines flowering for the longest. The greatest flowering overlap between tillers was recorded for the Ppd-1b. Across all lines, a warmer environment significantly reduced the duration of flowering and the influence of Ppd-1a alleles on the start of flowering. These findings provide evidence of pleiotropic effects of the Ppd-1a alleles, and have direct implications for breeding for increased stress resilient wheat varieties.

Perennial ryegrass and white clover (WC) have been shown to form compatible mixtures for pasture production under temperate climates. The inclusion of WC has the potential to enhance the performance of grass swards, but the extent of the improvement under contrasting grazing management strategies is unclear. Grazing rotation and fertilizer nitrogen (N) use have been identified as two major factors that can influence the performance of grass–clover swards. The objective of the current study was to examine the effect of differing grazing rotation lengths and the level of N application on the dry matter (DM) yield performance of grass–clover and grass-only swards as well as on WC productivity and persistency under animal grazing. Swards were managed by N application and grazing rotation length: High-N swards were managed on a 21-day grazing rotation (Man 1) and low-N swards were managed on a 30-day grazing rotation (Man 2). The four treatments were: 250 kg N/ha without WC (HN−C), 250 kg N/ha with WC (HN+C), 100 kg N/ha N without WC (LN−C) and 100 kg N/ha with WC (LN+C). There was a significant management × WC interaction over the 3 years for annual DM yield. The LN−C swards produced lower DM yield (−1917 kg DM/ha) than the swards of the other three treatments (11 167 kg DM/ha). Management had a significant effect on annual DM yield with Man 1 swards yielding 801 kg DM/ha more than Man 2 swards (10 288 kg DM/ha). The inclusion of WC yielded significantly more annual DM yield (+1009 kg DM/ha) than grass-only swards. Notably, LN+C produced the same annual total DM yield as swards under High N and a 21-day grazing rotation. Total WC DM yield and proportion across the year was altered significantly by management. Higher N fertilized swards at shorter grazing intervals had a lower WC DM yield (−1544 kg DM/ha) and proportion (−0·13). Dry matter yield of WC with low N application can be similar to that at high N levels if rotation length is used as a mechanism to determine grazing timing. Variations in WC productivity into the final year of the experiment indicate that persistence of significant contributions to DM yield by WC under low N at longer grazing intervals remains unclear after 3 years.

Maize (Zea mays L.) is a major staple food and cash crop in sub-Saharan Africa (SSA). However, its production and productivity are severely constrained by drought. A total of 120 single-cross hybrids and an open-pollinated control variety were evaluated for 2 years at two locations under managed drought and rain-fed conditions in Nigeria. The objective of the present study was to assess their performance, classify them into distinct heterotic groups and identify promising hybrids for commercialization in the West and Central Africa sub-region. General combining ability and specific combining ability mean squares were highly significant for grain yield and other traits under the research environments. However, there was a preponderance of additive gene action over non-additive. Only six out of 39 inbreds were classified into distinct heterotic groups by the testers. The highest-yielding drought-tolerant hybrid, TZEEI 102 × TZEEI 95, out-yielded the open-pollinated control variety by 43·70%. The average yield reduction under drought was 54·90% of the yield under rain-fed conditions. The hybrids TZEEI 81 × TZEE1 79, TZEEI 100 × TZEEI 63 and TZEEI 64 × TZEEI 79 were the highest-yielding and most stable across environments. These outstanding drought-tolerant hybrids, which are also resistant to Striga, have the potential to contribute to food security and increased incomes in SSA and should be tested extensively on-farm and commercialized.

A range of wheat cultivars, including elite cultivars, older cultivars and some preferred by organic growers, were trialled under high and low nitrogen (N) conventional and organic conditions to determine whether cultivars that yield highly under organic conditions have the same relative yield under conventional conditions. A range of cultivar mixtures was also assessed to see whether these gave yield advantages or superiority in either farming system. The conventional trials were grown with and without full fungicide programmes, which largely controlled disease. Amongst the cultivars, Alchemy showed superior yield under organic conditions as did Pegassos, but under conventional conditions Pegassos was always one of the low-ranking cultivars. Under conventional conditions the more recent cultivars Alchemy, Glasgow and Istabraq yielded highly, while an older one, Consort, yielded highly under low fertilizer conditions, and both Ambrosia and Deben also yielded highly generally. Fungicide and high N favoured the disease-susceptible, high-yield cultivars such as Glasgow whereas Consort, an older susceptible cultivar, was favoured by fungicide and low N. Together this demonstrates that whilst the yield characteristics of some elite germplasm are also expressed under organic conditions, at least one cultivar that yielded poorly under conventional conditions showed adaptation towards the organic conditions of these trials. Other cultivars yielding poorly under conventional conditions also gave poor yield under organic conditions. The equal proportion mixtures of cultivars grown under conventional conditions showed no evidence of differences in yield from the mean of the component cultivars grown separately, but combinations of Glasgow, Alchemy and Istabraq gave consistently high yield.

Wheat is an important crop in the highlands of Northern Ethiopia and climate change is expected to be a major threat to wheat productivity. However, the potential impacts of climate change and adaptation on wheat yield has not been documented for this region. Wheat field experiments were carried out during the 2011–2013 cropping seasons in Northern Ethiopia to: (1) calibrate and evaluate Agricultural Production Systems sIMulator (APSIM)-wheat model for exploring the impacts of climate change and adaptation on wheat yield; (2) explore the response of wheat cultivar/s to possible change in climate and carbon dioxide (CO2) under optimal and sub-optimal fertilizer application and (3) assess the impact of climate change and adaptation practices on wheat yield based on integration of surveyed field data with climate simulations using multi-global climate models (GCMs; for short- and mid-term periods) for the Hintalo-Wajrat areas of Northern Ethiopia. The treatments were two levels of fertilizer (optimal and zero fertilization); treatments were replicated three times and arranged in a randomized complete block design. All required information for model calibration and evaluation were gathered from experimental studies. In addition, a household survey was conducted in 2012 in Northern Ethiopia. Following model calibration and performance testing, response of wheat to various nitrogen (N) fertilizer rates, planting date, temperature and combinations of other climate variables and CO2 were assessed. Crop simulations were conducted with future climate scenarios using 20 different GCMs and compared with a baseline. In addition, simulations were carried out using climate data from five different GCM with and without climate change adaptation practices. The simulated yield showed clear responses to changes in temperature, N fertilizer and CO2. Regardless of choice of cultivar, increasing temperatures alone (by up to 5 °C compared with the baseline) resulted in reduced yield while the addition of other factors (optimal fertilizer with elevated CO2) resulted in increased yield. Considering optimal fertilizer (64 kg/ha N) as an adaptation practice, wheat yield in the short-term (2010–2039) and mid-term (2040–2069) may increase at least by 40%, compared with sub-optimal N levels. Assuming CO2 and present wheat management is unchanged, simulation results based on 20 GCMs showed that median wheat yields will reduce by 10% in the short term and by 11% in the mid-term relative to the baseline data, whereas under changed CO2 with present management, wheat yield will increase slightly, by up to 8% in the short term and by up to 11% in the mid-term period, respectively. Wheat yield will substantially increase, by more than 100%, when simulated based on combined use of optimal planting date and fertilizer applications. Increased temperature in future scenarios will cause yield to decline, whereas CO2 is expected to have positive impacts on wheat yield.

Cassava (Manihot esculenta Crantz) root yield measured as fresh weight (hereafter root yield) is declining in much of Asia and Africa. The current study aimed to identify quantitative trait loci (QTL) underlying both root and starch fresh weights in F1 cassava. Eight QTL were associated with root yield, underlying 12·9–40·0% of the phenotypic variation (PVE). Nine QTL were associated with starch content, underlying 11·3–27·3% of the PVE. Quantitative trait loci were identified from four different environments that encompassed two locations and 3 years. Consistent QTL for root yield, YLD5_R11 and YLD8_L09 on linkage group (LG) 16, were detected across years and locations. Quantitative trait loci for starch content, ST3_R09, ST6_R10 and ST7_R11 on LG 11, were found across 3 years. Co-localization of QTL for both traits with positive correlation was detected between YLD3_R10 and ST5_R10 on LG 9. Candidate genes within the QTL that were consistent across multiple environments were identified based on cassava genome sequences. Genes predicted to encode for glycosyl hydrolases, uridine 5’-diphospho-(UDP)-glucuronosyl transferases and UDP-glucosyl transferases were found among the 44 genes located within the region containing the QTL controlling starch content. Sixteen genes predicted to encode proteins that were possibly associated with root yield were identified. The QTL controlling root yield and starch content in the current study will be useful for molecular breeding of cassava through marker-assisted selection. The identification of candidate genes underlying both traits will be useful both as markers and for gene expression studies.

Spot blotch disease caused by Bipolaris sorokiniana (Sacc.) Shoem causes yield losses and reduces grain quality in wheat. Molecular markers reported to be linked with resistance to B. sorokiniana could accelerate the identification of resistant genotypes as they are independent of the environmental effect. However, before they can be utilized for marker assisted selection (MAS), validation in an independent population is required. The objective of the present study was therefore to validate three simple sequence repeat (SSR) molecular markers (Xwgm570, Xgwm544 and Xgwm437) linked with resistance to B. sorokiniana. The markers were validated using 66 wheat genotypes comprising 11 parental genotypes and 55 F2 progenies. Single marker analysis was performed using simple linear regression to ascertain the relationship between the marker and the trait. All the markers were confirmed to be associated with resistance. They all gave significant association with resistance to B. sorokiniana. The markers amplified DNA fragments in the resistant parental genotypes that were similar to those observed in resistant F2 progenies, but absent in the susceptible ones. Hence, these markers could be useful in increasing the efficiency of selection for resistance to B. sorokiniana in wheat breeding. Since the R2 values are low, a combination of two or three SSR markers can be employed during MAS. This was evident by the multiple linear equation which gave a combined R2 value of 18·0%, obtained from the inclusion of all three markers.

One of the probable adverse effects of climate change on agriculture is yield loss due to water scarcity. Assessment of meteorological drought risk with the index of crop water deficit (CWD) can help in determining appropriate adaptation strategies to counter such losses. Using daily weather data from 68 stations in Northeast China (NEC) for 1961–2010, the spatial and temporal behaviour of CWD was assessed and the sensitivity of climatic variables related to CWD during the potential growth period of maize was explored. The results indicated that the potential maize growth period decreased by 26 days due to climate warming. The deficit (i.e. a negative value for water demand) decreased from east to west and decreased gradually during 1978–1984 and sharply during 2000–2010. It is noteworthy that NEC experienced severe droughts especially in the 1970s and the 2000s, and relative humidity was the most sensitive parameter affecting evapotranspiration. Regions in the middle of Heilongjiang and Jilin should take precautions concerning climate change effects on CWD, while the northern part of NEC should take precautions concerning changes in temperature and sunshine hours. Growing late-maturing and drought-tolerant maize varieties is therefore a good option for higher production in NEC, coupled with enhancing the availability of water in this limited-rainfall region, and should form a part of the strategy to cope with climate change.

Controlled irrigation during the dry period associated with adequate nitrogen (N), phosphorous (P) and potassium (K) fertilization led to the accumulation of biochemical compounds in coffee beans considered as positive precursors of beverage quality. Adult plants of coffee (Coffea arabica ‘Rubi’) were cultivated using different water regimes (WR) and fertilization conditions under the dry climate of the Brazilian Cerrado. Coffee-bean physical characteristics were evaluated as well as biochemical composition by near-infrared analysis. The K treatment mostly affected bean biochemistry, lipid and chlorogenic acid (CGA) contents, which increased with increasing amounts of fertilizer. Caffeine contents increased with higher amounts of N, but no significant effects of P treatment on bean biochemical composition were observed. Sucrose and total lipid contents always appeared higher in beans of non-irrigated plants than those beans from plants grown with continuous irrigation. In contrast, caffeine and CGA contents were higher in beans of irrigated as compared with non-irrigated plants. For the first time, the current results showed that controlled management of irrigation during the dry period associated with reasonable NPK fertilization led to the accumulation of biochemical compounds in coffee beans considered as positive precursors of beverage quality.

Little is known about the quantitative relationships between wheat powdery mildew (Blumeria graminis f.sp. tritici) epidemics and climatic variables at the provincial scale in China, particularly under climate change. The present study assesses the actual disease process and corresponding impact on wheat yield and addresses climatic-driven variables that affect a powdery mildew epidemic. Powdery mildew increased in frequency from 1981 to 2010, and wheat yield decreased in most regions. It was clear that differences in disease and yield loss occurred temporally and spatially. Although particular weather variables were positively or negatively related to the disease, multiple stepwise regression analysis indicated that mostly fewer than three variables affected prevalence and severity of powdery mildew in each province. In most cases, some combination of higher temperature, humidity, rainfall and wind led to higher disease severity. These weather factors had different effects on disease development. The influence of climatic variables on powdery mildew tended to decrease from 1981 to 2010, whereas the effect of non-climatic factors increased and was attributed mainly to the use of fungicides and resistant cultivars. Therefore, the results of the current study suggest that wheat powdery mildew in China will not increase consistently in the future. In addition, the quantitative assessment method used in the current study can generally provide a good way to identify disease epidemics under climate change.

Late sowing causes substantial yield reduction in canola. This yield reduction is principally due to lower emergence and poor crop establishment because of prevailing low temperatures. A field experiment was conducted using five sowing dates over two growing seasons (2014/15 and 2015/16). The effect of two seed-priming strategies (hydropriming and osmopriming with zinc sulphate, ZnSO4) was measured in three canola cultivars (Okapi, Zarfam and Talayeh). Results showed that both seed-priming treatments were effective in improving emergence percentage (EP) of canola cultivars. The highest EP occurred in the earlier sowing in both years. On 5 September, EP for the hydropriming, osmopriming and no-primed treatments were 89, 93 and 73% in Okapi, 83, 89 and 69% in Zarfam, and 81, 89 and 72% in Talayeh, respectively (data averaged across both years). Delay in sowing date compared with 5 September caused a sharp reduction in EP in primed seed and control conditions. Maximum seedling emergence rate and coefficient of uniformity of emergence were seen in early sowing for Okapi cultivar with ZnSO4 osmopriming. Experimental evidence showed that in canola cultivars the activities of superoxide dismutase, peroxidase and catalase were higher in the leaves of plants from seed primed with ZnSO4 compared with seed from hydroprimed plants. Cultivar analysis of total antioxidant content activities indicated, the maximum increase was observed in the Okapi and Talayeh cultivars.

Sorghum [Sorghum bicolor (L.) Moench] grown in India is of two adaptive types: rainy and post-rainy. The post-rainy sorghum is predominantly consumed by humans. While releasing new cultivars through multi-location testing, major emphasis is given to the superiority of new cultivars over existing cultivars, with very little emphasis on the genotype × environment interaction (GEI). To understand the complexity of GEI in post-rainy sorghum testing location trials, the multi-location evaluation data of two post-rainy seasons (2009/10 and 2010/11) under the All India Coordinated Sorghum Improvement Project were analysed. In both years, location explained the highest proportion of total sum of squares followed by the GEI effect and main effect of genotype. Additive main effects and multiplicative interaction (AMMI), stability values (ASV) and genotype + genotype × environment interaction (GGE) instability values recorded high correlation resulting in identification of the best performing cultivars. However, the rank correlations were lower, though still significant. A mixture of crossover and non-crossover GEI was a common occurrence in both years. ‘Which-won-where’ analysis suggested the existence of four possible mega-environments (ME) among post-rainy testing locations, with a few non-informative locations within ME. Mega-environments are characterized by soil type, rainfall pattern and moisture conservation practices. The present study indicated the possibility of reducing the number of test locations by eliminating non-representative highly correlated locations and suggested the need to breed for location-specific genotypes rather than genotypes with wider adaptability.

Maize in Canada is grown mainly in the south-eastern part of the country. No comprehensive studies on Canadian maize yield levels have been done so far to analyse the barriers of obtaining optimal yields associated with cultivar, environmental stress and agronomic management practices. The objective of the current study was to use a modelling approach to analyse the gaps between actual and potential (determined by cultivar, solar radiation and temperature without any other stresses) maize yields in Eastern Canada. The CSM–CERES–Maize model in DSSAT v4·6 was calibrated and evaluated with measured data of seven cultivars under different nitrogen (N) rates across four sites. The model was then used to simulate grain yield levels defined as: yield potential (YP), water-limited (YW, rainfed), and water- and N-limited yields with N rates 80 kg/ha (YW, N-80N) and 160 kg/ha (YW, N-160N). The options were assessed to further increase grain yield by analysing the yield gaps related to water and N deficiencies. The CSM–CERES–Maize model simulated the grain yields in the experiments well with normalized root-mean-squared errors <0·20. The model was able to capture yield variations associated with varying N rates, cultivar, soil type and inter-annual climate variability. The seven calibrated cultivars used in the experiments were divided into three grades according to their simulated YP: low, medium and high. The simulation results for the 30-year period from 1981 to 2010 showed that the average YP was 15 000 kg/ha for cultivars with high yield potential. The YP is generally about 6000 kg/ha greater than the actual yield (YA) at each experimental site in Eastern Canada. Two-thirds of this gap between YP and YA is probably associated with water stress, as a gap of approximately 4000 kg/ha between the YW and the YP was simulated. This gap may be reduced through crop management, such as introducing irrigation to improve the distribution of available water during the growing season. The simulated yields indicated a gap of about 3000 and 1000 kg/ha between YW and YW,N-80N for cultivars with high YP and low YP, respectively. The gap between YW and YW,N-160N decreased to <2000 kg/ha for high Yp cultivars with little difference for the low Yp cultivars. The different yield gaps among cultivars suggest that cultivars with high YP require high N rates but cultivars with low YP may need only low N rates.

The production of winter wheat (Triticum aestivum L.) is affected by crop population structures and field microclimates. This 3-year study assessed the effect of different precision planting patterns and irrigation conditions on relative humidity (RH), air and soil temperature within the canopy, intercepted photosynthetically active radiation (iPAR), evapotranspiration (ET), water productivity (WP) and grain yields. Field experiments were conducted from 2011 to 2014 on a two-factor split-plot design with three replicates. The experiments involved three precision planting patterns (single row, alternating single and twin rows [hereafter ‘single–twin’] and twin row) and three irrigation treatments (0 mm (I0), 90 mm (I90) and 180 mm (I180)). Planting patterns and irrigation treatments exerted a significant effect on RH, air and soil temperature, iPAR, ET, WP and grain yield. The lowest RH and iPAR levels were detected in the single row pattern. When the irrigation treatment was identical, the highest soil and air temperatures were detected in the single row pattern, followed by the single–twin row and twin row patterns. Compared with the single row, the single–twin and twin row patterns increased ET by 0·3 and 1·4, WP by 4·7 and 5·7% and yields by 6·0 and 7·9%, respectively. Compared with I0, the I90 and I180 irrigation treatments increased ET by 0·3 and 1·4%, and WP by 4·7 and 5·7%, respectively. The grain yields of the twin row pattern were 5·8 and 1·7% higher than those of the single row and single–twin row patterns, respectively. Compared with I0, I90 increased yield by 19·3%. The twin row pattern improved crop structure and farmland microclimate by increasing RH and iPAR, and reducing soil and air temperatures, thus increasing grain yield. These results indicated that a twin row pattern effectively improved grain yield at I0. On the basis of iPAR, WP and grain yield, it was concluded that a twin row pattern combined with an I90 irrigation treatment provided optimal cropping conditions for the North China plain.

The response of grain yield, grain nitrogen (N), phenological development and evapotranspiration of winter wheat to climate change was analysed over an 80-year period based on climate change predictions of four regional circulation models (RCMs) under the IPCC (International Panel on Climate Change) A1B emission scenario for the 21st century using three process-based models; A 20-year set (1991–2010) of observed daily climate data from Aarslev, Denmark was used to form the baseline, from which the RCM data were generated. The simulation of crop growth was performed with increasing carbon dioxide (CO2) levels and under continuous mono-cropping system at different N input rates. Results indicated that grain yield and grain N will be reduced in the future despite increased CO2 concentration in the atmosphere. While the increased N input may increase yield, it will not increase grain N. The present study suggested that in Denmark, alternative strategies for organic N acquisition of plants must be developed. Statistical analyses showed that while the crop models were the main source of uncertainty in estimating crop performance indicators in response to climate change, the choice of RCM was the main source of uncertainty in relation to baseline estimations.