Soybean is an important oil- and protein-producing crop and over the last few decades soybean genetic transformation has made rapid strides. The probability of occurrence of transgene flow should be assessed, although the discrimination of conventional and transgenic soybean seeds and their hybrid descendants is difficult in fields. The feasibility of non-destructive discrimination of conventional and glyphosate-resistant soybean seeds and their hybrid descendants was examined by a multispectral imaging system combined with chemometric methods. Principal component analysis (PCA), partial least squares discriminant analysis (PLSDA), least squares-support vector machines (LS-SVM) and back propagation neural network (BPNN) methods were applied to classify soybean seeds. The current results demonstrated that clear differences among conventional and glyphosate-resistant soybean seeds and their hybrid descendants could be easily visualized and an excellent classification (98% with BPNN model) could be achieved. It was concluded that multispectral imaging together with chemometric methods would be a promising technique to identify transgenic soybean seeds with high efficiency.

A warmer and potentially drier future climate is likely to influence the production of forage crops on dairy farms in the southeast dairy regions of Australia. Biophysical modelling was undertaken to explore the resilience of forage production of individual forage crops to scalar increases in temperature, atmospheric carbon dioxide (CO2) concentration and changes in daily rainfall. The model APSIM was adapted to reflect species specific responses to growth under elevated atmospheric CO2 concentrations. It was then used to simulate 40 years of production of forage wheat, oats, annual ryegrass, maize grown for silage, forage sorghum, forage rape and alfalfa grown at three locations in southeast Australia with increased temperature scenarios (1, 2, 3 and 4 °C of warming) and atmospheric CO2 concentration (435, 535, 640 and 750 ppm) and decreasing rainfall scenarios (10, 20 or 30% less rainfall). At all locations positive increases in DM yield compared with the baseline climate scenario were predicted for lucerne (2·6–93·2% increase), wheat (8·9–37·4% increase), oats (6·1–35·9% increase) and annual ryegrass (9·7–66·7% increase) under all future climate scenarios. The response of forage rape and forage sorghum varied between location and climate change scenario. At all locations, maize was predicted to have a minimal change in yield under all future climates (between a 2·6% increase and a 6·8% decrease). The future climate scenarios altered the seasonal pattern of forage supply for wheat, oats and lucerne with an increase in forage produced during winter. The resilience of forage crops to climate change indicates that they will continue to be an important component of dairy forage production in southeastern Australia.

Development of partial inter-specific hybrid (PIH) rice is a promising approach for exploiting inter-specific heterosis between Oryza glaberrima and Oryza sativa. In the present study, the relationship between genetic distance (GD) of parental lines and yield performance of the PIHs was assessed using partial diallel crosses between three indica male sterile lines and 14 introgression lines (ILs) with different fragments of O. glaberrima genes. Twenty two out of the 42 PIHs expressed positive heterobeltiosis (i.e., the Fl hybrid showed superiority over the better parent in the target trait) for panicle number, spikelet number, thousand grain weight and grain yield/plant. The proportion of O. glaberrima genome in the ILs ranged from 0·03 to 0·41, as revealed by 16 informative simple sequence repeat markers. Significant positive correlations were found between the proportion of O. glaberrima genome of the ILs and the GD between the ILs and the three different female parents. Heterosis of spikelet number per panicle in the hybrids was positively proportional with the O. glaberrima genome content of the parental ILs, while that of fertile grain percentage was negatively proportional to the O. glaberrima genome proportion. On average, the PIHs with higher grain yield and highest heterobeltiosis were obtained from the ILs carrying between 0·15 and 0·30 of O. glaberrima genome. The results indicated that a small proportion (<0·15) of the O. glaberrima genome in the ILs might limit heterosis expression of spikelet number per panicle, while a very large proportion (>0·30) of the O. glaberrima genome decreased the grain filling percentage in the PIHs, thus an intermediate range of O. glaberrima genome proportion should be more suitable for breeding heterotic PIHs. The exploitation of inter-specific heterosis between O. glaberrima and O. sativa has potential value for heterotic breeding in rice.

The present study applies refined and improved scenarios for climate change to quantify the effects of potential alterations in climatic factors on localities for wheat and cotton production, which are two crops important to Australia's economy. The future distributions of Gossypium (cotton) and Triticum aestivum L. (wheat) were modelled using CLIMEX software with the A2 emission scenario generated by CSIRO-Mk3·0 and MIROC-H global climate models. The results were correlated to identify areas suitable for these economically important crops for the years 2030, 2050, 2070 and 2100 in Australia. The analysis shows that the areas where wheat and cotton can be grown in Australia will diminish from 2030 to 2050 and 2070 through to 2100. While cotton can be grown over extensive areas of the country until 2070, the area grown to wheat will decrease significantly over the period.

To gain protection under the International Convention for the Protection of New Varieties of Plant, new plant varieties must be distinguishable from existing varieties in at least one important characteristic. Assessment of quantitative characteristics often uses a procedure based on analysis of variance of variety-by-year means for 2 years of trials. In the current paper, a new method is described that can identify those reference varieties that are so different from a candidate that there would be no reason to compare them in the subsequent year, resulting in potential cost savings. It is more objective and transparent than existing practice for quantitative characteristics based on expert opinion. The method calculates thresholds for quantitative characteristics. The thresholds are defined so that if in the first year the difference between two varieties in a characteristic is larger than the characteristic's threshold then it is highly likely that the varieties would be distinct after 2 years. Thresholds were derived based on statistical predictions of the full decision after 2 years using the first year results combined with historical data. It is shown that these thresholds are sensitive to yearly heterogeneity in the variety-by-year variation. The method accommodates this heterogeneity by modelling yearly residual variances with the inverse gamma distribution. This extension meant that exact analytical formulae were not available so an approximation was suggested. Using simulation it was found that the approximation was reasonable; for thresholds corresponding to a high probability of distinctness, the approximate thresholds were a little higher than required. The method was evaluated on a 19-year data set for field pea, comparing decisions based on first year thresholds with those based on the full 2 years. It was found that with the probability of distinctness set at 0·99, the calculated thresholds were generally lower than the existing expert-set thresholds but had acceptable levels of false positives and false negatives.

In order to reduce the environmental impact of agriculture and improve the resilience and sustainability of our food systems, there is an increasing interest in shifting from the present agricultural systems, which are characterized by high external inputs, to low-input productive systems characterized by high resilience and sustainability. Purposely developed varieties are needed for the latter. With the rapid disappearance of landraces, heterogeneous populations such as composite cross populations (CCPs) or line mixtures, developed through evolutionary plant breeding, could be the ideal source of breeding material for the development of new cultivars for low-input productive systems. Parental lines of CCPs should be selected among old breeding lines, varieties or landraces because the specific characteristics required for low-input or organic farming systems might have been lost during selection of modern varieties. In the current scenario of renewed interest in evolutionary plant breeding, the evolution of diversity in heterogeneous populations needs to be better investigated to maximize the advantages that can be obtained by their utilization.

The present paper reports on the analysis of 88 barley plants chosen randomly from a CCP, namely AUT DBA (where AUT indicates autumn sowing and DBA is the acronym of the former Department) that was multiplied for 13 years under a low-input management system without any conscious human selection, aiming to investigate the morphological diversity still existing in the population and its potential value as source of breeding material for low-input/organic agriculture and understanding the traits that contributed to the adaptive success of certain groups of individuals.

Eighteen plant and spike morphological traits were analysed using bi-dimensional spatial analysis, cluster analysis, non-parametric tests and multivariate approaches. Low lodging and loose smut damage were observed in the CCP where several individuals were superior to the best control for at least one of the four yield-related traits, namely spike weight, number of seeds per spike, weight of seeds in a spike and grain weight. Three morphological clusters were identified using cluster analysis. Clusters 2 and 3 grouped the largest number of CCP individuals which, compared with those in cluster 1, were characterized mainly by heavier spikes with higher seed number, taller culms and early flowering. Interestingly, the plant architecture of all the controls was different from that of the most frequent genotypes in the CCP, showing that low-input systems may require a plant architecture different from the one usually considered as the most suitable for high-input systems. Taking advantage of results from Raggi et al. (2015), phenotypic data were also analysed according to individual genetic group assignment. Results suggest that plant height at the beginning of stem elongation, and days to heading, together with traits related to culm and leaf morphology, could have played a significant role in determining the success of plants from genetic group D, which is the group most represented in the CCP.

According to the wide range of morphological diversity existing in the AUT DBA and the high percentage of lines that show favourable combinations of different traits, this population could be a useful gene-pool from which to select lines for breeding activities. Even though further use of the CCP for breeding purposes may be limited by its possible evolution, there are different ways of manipulating the CCP to counteract the undesirable changes without great economic and/or technical efforts. The high number of multi-locus genotypes and the evolutionary responses observed in AUT DBA show that the prediction that phenotypic micro-evolution in natural systems may be limited by low genetic variances in harsh environments and low selection pressure in good environments is not necessarily true for low-input systems.

Association mapping based on linkage disequilibrium (LD) is a promising tool to identify genes responsible for quantitative variations underlying complex traits. The present paper presents an association mapping panel consisting of 172 upland cotton (Gossypium hirsutum L.) accessions. The panel was phenotyped for five cotton plant architecture traits across multiple environments and genotyped using 386 simple sequence repeat (SSR) markers. Of these markers, 101 polymorphic SSR markers were used in the final analysis. There were abundant phenotypic variations within this germplasm panel and a total of 267 alleles ranging from two to seven per locus were identified in all collections. The threshold of LD decay was set to r2 = 0·1 and 0·2, and the genome-wide LD extended up to about 13–14 and 6–7 cM, respectively, providing the potential for association mapping of agronomically important traits in upland cotton. A total of 66 marker–trait associations were detected based on a mixed linear model, of which 35 were found in more than one environment. The favourable alleles from 35 marker loci can be used in marker-assisted selection of target traits. Both the synergistic alleles and the negative alleles for some traits, especially plant height and fruit branch angle, can be utilized in plant architecture breeding programmes according to specific breeding objectives.

Lolium rigidum L. (rigid ryegrass) is one of the most extensive and harmful weeds in winter cereal crops. A bioclimatic model for this species was developed using CLIMEX. The model was validated with records from North America and Oceania and used to assess the global potential distribution of L. rigidum under the current climate and under two climate change scenarios. Both scenarios represent contrasting temporal patterns of economic development and carbon dioxide (CO2) emissions. The projections under current climatic conditions indicated that L. rigidum does not occupy the full extent of the climatically suitable area available to it. Under future climate scenarios, the suitable potential area increases by 3·79% in the low-emission CO2 scenario and by 5·06% under the most extreme scenario. The model's projection showed an increase in potentially suitable areas in North America, Europe, South America and Asia; while in Africa and Oceania it indicated regression. These results provide the necessary knowledge for identifying and highlighting the potential invasion risk areas and for establishing the grounds on which to base the planning and management measures required.

Nitrogen (N) supply is essential for achieving high grain yield in maize production, but excessive N application can lead to lodging risks and potential yield loss. The main objective of the present study was to investigate the effect of ethephon application under different N fertilizer rates in reducing maize lodging. Field experiments were conducted to determine the interactive effects of ethephon (0 and 180 g/ha) and N rate (0, 75, 150 and 225 kg N/ha) on the morphological and chemical characteristics of basal internode and yield across two summer maize-growing seasons (2011/12) in Wuqiao of the North China Plain. Findings showed that ethephon significantly increased the maximum diameter of the 7th to 14th internodes, and decreased the internode lengths, which led to a decrease in plant and ear heights under different N rates. Significant ethephon × N interaction effects were observed on the diameter and length of internode, dry weight per unit internode length and breaking resistance. Ethephon significantly increased N, cellulose and hemicellulose contents of the basal internode, but cellulose and hemicellulose contents decreased as the rate of N application increased. Internode diameter, dry weight per unit internode length, and N content of the basal internode were significantly positively correlated with breaking resistance. Ethephon significantly increased grain yield and harvest index in 2011, but not in 2012. Grain yield and above-ground biomass were increased with increasing N application in both growing seasons, showing linear and quadratic responses. These results suggested that ethephon could increase stalk strength by improving the morphological and chemical characteristics of the basal internode, and maintain high yield and biomass under high N rates.

Rice (Oryza sativa L.) is one of the most important cereal crops in the world and a potentially important source of zinc (Zn) in the diet. The improvement of Zn content of rice is a global challenge with implications for both rice production and human health. The objective of the present study was to identify the effects of nitrogen (N) fertilizer rates and Zn application methods on Zn content of rice by evaluating rice production on native soils with different Zn availabilities in 2010/11. The results indicated that Zn application increased rice grain yield and Zn content in grains compared with the control; however, this effect was also affected by the native soil Zn availability, N fertilizer rate and Zn fertilizer application method. The native soil Zn status was the dominant factor influencing grain yield and grain Zn content in response to Zn fertilizer application. Grain Zn content ranged from 19·74 to 26·93 mg/kg under the different Zn statuses. The results also indicated that Zn application method has a significant influence on grain yield. Application of Zn fertilizer to the soil was more effective than the foliar spray on rice grain yield; however, the foliar spray resulted in a greater increase in grain Zn content when compared with soil application. Grain Zn content was affected by application method and displayed the following general trend: soil application + foliar spray > foliar spray > soil application. The experiments investigating the effect of N fertilizer rate combined with Zn application method showed a clear increase in both grain yield and Zn content as the N fertilizer level increased from 200 to 300 kg/ha. In addition, the results also indicated that N content and accumulation increased in all plant tissues, which suggests that Zn application might influence the uptake and translocation of N in rice plants. These results suggest that soil application in addition to a foliar spray of Zn should be considered as an important strategy to increase grain yield and grain Zn content of rice grown in soils with low background levels of Zn-associated diethylene triamine pentaacetate acid. Moreover, this process could be further strengthened by a high N application rate. In conclusion, these results demonstrate the potential of optimizing nutrient management using Zn fertilizer to obtain higher grain yields and higher grain Zn content in fields with low native Zn status.

Climate change is expected to affect optimum agricultural management practices for autumn-sown wheat, especially those related to sowing date and nitrogen (N) fertilization. To assess the direction and quantity of these changes for an important production region in eastern Austria, the agricultural production systems simulator was parameterized, evaluated and subsequently used to predict yield production and grain protein content under current and future conditions. Besides a baseline climate (BL, 1981–2010), climate change scenarios for the period 2035–65 were derived from three Global Circulation Models (GCMs), namely CGMR, IPCM4 and MPEH5, with two emission scenarios, A1B and B1. Crop management scenarios included a combination of three sowing dates (20 September, 20 October, 20 November) with four N fertilizer application rates (60, 120, 160, 200 kg/ha). Each management scenario was run for 100 years of stochastically generated daily weather data. The model satisfactorily simulated productivity as well as water and N use of autumn- and spring-sown wheat crops grown under different N supply levels in the 2010/11 and 2011/12 experimental seasons. Simulated wheat yields under climate change scenarios varied substantially among the three GCMs. While wheat yields for the CGMR model increased slightly above the BL scenario, under IPCM4 projections they were reduced by 29 and 32% with low or high emissions, respectively. Wheat protein appears to increase with highest increments in the climate scenarios causing the largest reductions in grain yield (IPCM4 and MPEH-A1B). Under future climatic conditions, maximum wheat yields were predicted for early sowing (September 20) with 160 kg N/ha applied at earlier dates than the current practice.

Grain yield in bread wheat is often tightly associated with grain number/m2. In turn, spike fertility (SF), i.e., the quotient between grain number and spike chaff dry weight, accounts for a great proportion of the variation in grain number among cultivars. In order to examine the potential use of SF as a breeding target, (1) variation for the trait was assessed in six datasets combining commercial cultivars under different environmental conditions, (2) trait heritability was estimated in a set of F1 hybrids derived from controlled crosses between cultivars with contrasting SF and (3) SF distribution pattern was analysed in two F2 segregating populations. Analysis of commercial cultivars revealed considerable variation for SF, under both optimal and sub-optimal conditions. In addition, genotypic variation was consistently larger than genotype × environment interaction variation in all datasets. Narrow sense heritability, estimated by the mid-parent-offspring regression of 20 F1 hybrids and their respective parents, was 0·63. Data from two F2 populations exhibited bell-shaped and symmetric frequency distributions of SF, with a SF mean intermediate between the parental values. Substantial transgressive segregation was detected in both F2 populations. In conclusion, SF appears to be a heritable trait with predominantly additive effects. This warrants further investigation on the feasibility of using SF as an early selection criterion in wheat breeding programs aimed at increasing grain yield.

Safety evaluation of a genetically modified (GM) crop is accomplished by establishing its substantial equivalence to non-GM reference crops with a history of safe use. Testing hypotheses of equivalence rather than difference is the appropriate statistical approach. A necessary first step in this regard is to specify a reasonable equivalence criterion that includes a measure for discrepancy between the GM and reference crops as well as a regulatory threshold. The present work explored several equivalence criteria and discussed their pros and cons. Each criterion addresses one of three ordered classes of equivalence: super, conditional and marginal equivalence. Their implications were investigated over an array of parameter values estimated from a real-world dataset. Marginal equivalence was identified as adhering most closely to the concept of substantial equivalence. Because conditional equivalence logically implies marginal equivalence and is practically quantifiable from current field designs, the present work recommends conditional equivalence criteria while encouraging producers to improve their design to enable testing marginal equivalence in the future. Contrary to concerns of the ag-biotech industry, empirical evidence from recent publications indicates that a linear mixed model currently implemented by the European Food Safety Authority is adequate for assessing equivalence despite its lack of genotype-by-environment interaction terms.

The historical temperature (1981–2007) and phenological (1986–2011) data were analysed for the region of Sremski Karlovci, one of the oldest grapevine growing areas in Europe, with the aim of detecting trends of changes in the data, evaluating the sensitivity of grapevine phenology to temperature and revealing diversity among cultivars in their response to observed changes in temperature. The onset dates of four major phenological stages (budburst, flowering, veraison and harvest), along with the corresponding growth intervals between them, were examined for 20 wine grape cultivars. A number of climatically important parameters for viticulture were calculated for the calendar year, growing season and different grapevine growth periods. Significant increases were detected in average and heat-related extreme temperature indices. The greatest rate of change in temperature variables across the growing season was observed during the period from the beginning of flowering to the beginning of veraison and the smallest during the ripening period. Linear trends indicated that all phenological stages, except budburst, have advanced significantly. Averaged across all cultivars, detected trends were –0·4, –0·7 and –0·6 days/year for the beginning of flowering, the beginning of veraison and harvest date, respectively. Observed warming and change in the timing of phenological events did not significantly affect the duration of the growth intervals, which can be explained by significant inter-correlation between the phenological stages’ onset. Ripening was occurring under warmer conditions due to earlier flowering and veraison, rather than because of considerably higher temperatures preceding harvest or shortening of the ripening period. Most of the variation in phenology timing (74–90%) can be explained by a linear relationship between the onset date of phenological stage and temperature, with mean and maximum temperatures being more important than minimum temperatures. According to the current results, a 1 °C increase in the most influential temperature variable during the most relevant periods for the onset of phenological stages led to an advancement in the beginning of budburst, the beginning of flowering, the beginning of veraison and harvest by 3·6, 3·1, 5·2 and 7·4 days, respectively, on average for all cultivars. Among the cultivars studied, Pinot Noir displayed the greatest phenology advancement in response to increased temperature.

In search of a suitable resource conservation technology under pigeonpea (Cajanus cajan L.)–wheat (Triticum aestivum L.) system in the Indo-Gangetic Plains, the effects of conservation agriculture (CA) on crop productivity and water-use efficiency (WUE) were evaluated during a 3-year study. The treatments were: conventional tillage (CT), zero tillage (ZT) with planting on permanent narrow beds (PNB), PNB with residue (PNB + R), ZT with planting on permanent broad beds (PBB) and PBB + R. The PBB + R plots had higher pigeonpea grain yield than the CT plots in all 3 years. However, wheat grain yields under all plots were similar in all years except for PBB + R plots in the second year, which had higher wheat yield than CT plots. The contrast analysis showed that pigeonpea grain yield of CA plots was significantly higher than CT plots in the first year. However, both pigeonpea and wheat grain yields during the last 2 years under CA and CT plots were similar. The PBB + R plots had higher system WUE than the CT plots in the second and third years. Plots under CA had significantly higher WUE and significantly lower water use than CT plots in these years. The PBB + R plots had higher WUE than PNB + R and PNB plots. Also, the PBB plots had higher WUE than PNB in the second and third years, despite similar water use. The interactions of bed width and residue management for all parameters in the second and third years were not significant. Those positive impacts under PBB + R plots over CT plots were perceived to be due to no tillage and significantly higher amount of estimated residue retention. Thus, both PBB and PBB + R technologies would be very useful under a pigeonpea–wheat cropping system in this region.

Grazing season length (GSL) on grassland farms with ruminant production systems can influence farm economics, livestock disease transmission, environmental impact, milk and meat quality, and consumer choice. Bioclimatic variables are biologically meaningful climate variables that may enable predictions of the impact of future climate change on GSL on European farms. The present study investigated the spatial relationship between current GSL (months) measured by EUROSTAT on dairy, beef and sheep farms in 706, 774 and 878 regions, respectively, and bioclimatic variables. A stepwise multiple regression model revealed a highly significant association between observed GSL and bioclimatic variables across Europe. Mean GSL was positively associated with the mean temperature of the coldest quarter and isothermality, and negatively associated with precipitation in the wettest month. Extrapolating these relationships to future climate change scenarios, most European countries were predicted to have a net increase in GSL with the increase being largest (up to 2·5 months) in the north-east of Europe. However, there were also predictions of increased variability between regions and decreases in GSL of up to 1·5 months in some areas such as the west of France, the south-west of Norway and the west coast of Britain. The study quantified and mapped the potential impact of climate change on GSL for dairy, beef and sheep farms across Europe.

Drought risk is considered to be among the main limiting factors for maize (Zea mays L.) production in the Northeast Farming Region of China (NFR). Maize yield data from 44 stations over the period 1961–2010 were combined with data from weather stations to evaluate the effects of climatic factors, drought risk and irrigation requirement on rain-fed maize yield in specific maize growth phases. The maize growing season was divided into four growth phases comprising seeding, vegetative, flowering and maturity based on observations of phenological data from 1981 to 2010. The dual crop coefficient was used to calculate crop evapotranspiration and soil water balance during the maize growing season. The effects of mean temperature, solar radiation, effective rainfall, water deficit, drought stress days, actual crop evapotranspiration and irrigation requirement in different growth phases were included in the statistical model to predict maize yield. During the period 1961–2010, mean temperature increased significantly in all growth phases in NFR, while solar radiation decreased significantly in southern NFR in the seeding, vegetative and flowering phases. Effective rainfall increased in the seeding and vegetative phases, reducing water deficit over the period, whereas decreasing effective rainfall over time in the flowering and maturity phases enhanced water deficit. An increase in days with drought stress was concentrated in western NFR, with larger volumes of irrigation needed to compensate for increased dryness. The present results indicate that higher mean temperature in the seeding and maturity phases was beneficial for maize yield, whereas excessive rainfall would damage maize yield, in particular in the seeding and flowering phases. Drought stress in any growth stage was found to reduce maize yield and water deficit was slightly better than other indicators of drought stress for explaining yield variability. The effect of drought stress was particularly strong in the seeding and flowering phases, indicating that these periods should be given priority for irrigation. The yield-reducing effects of both drought and intense rainfall illustrate the importance of further development of irrigation and drainage systems for ensuring the stability of maize production in NFR.

A comparative study of the effect of organic fertilization at different times and doses on soil fertility and crop yield was performed over 3 years in a calcareous loamy soil. Nutrient availability in the soil and macronutrient concentration in leaves and in the edible part of the plants was examined in plots that were previously handled conventionally and ecologically for several years. The organic fertilizers used were manure compost at two doses in plots after 4 years of organic management treatment, and green residues of previous crops in plots with 10 years of organic management. In general, soil organic carbon (C), nitrogen (N), phosphorous (P) and magnesium (Mg) contents were found to be considerably greater in organically fertilized soils in comparison with soil receiving mineral fertilizer (conventional treatment (CT)). For C and N, the highest contents were observed in the long-term organic treatment (OR). However, few differences were found for potassium (K) and sodium (Na). The results obtained for electrical conductivity and pH indicated that, in general, there were no significant differences between treatments. The differences in the values of EC and pH occurred among cultivation cycles irrespective of the type of fertilization, but there was a contradictory trend for each of the above parameters. The results obtained for leaves and the edible part of the plant indicated that, in general, there were no significant differences between treatments, except for P with a trend for higher P content in organic crops. The nitrate values in leaves showed great variability, making it difficult to draw conclusions. The associations of fertilization and the chemical properties of soil with nutrient content in crops were checked by principal component analysis (PCA). For soil data, different clusters were observed between CT and OR treatments. However, PCA showed that the influence of crop type on plant nutrient concentrations was greater than type of fertilization. The effect of fertilization on crop yield was variable depending on plant species. The results indicated that organic fertilization did not cause deficiencies in the nutrient content and yield of vegetables when compared with conventional fertilization, showing that ecological management can be used effectively.

Crop canopy characteristics and management factors that affect the canopy structure can influence crop competitive ability against weeds. The goal of the current study was to understand the interaction between nitrogen (N) fertilizer rate and redroot pigweed (Amaranthus retroflexus) density on common bean (Phaseolus vulgaris L.) canopy characteristics and N assimilation. Experiments were conducted to determine the growth responses of two bean genotypes with contrasting growth habits to different N fertilizer rates under no, low and high redroot pigweed pressure. Nitrogen was applied at rates of 0, 50, 100 and 200 kg/ha for a semi-erect variety and 0, 35, 70 and 140 kg/ha for an erect bean variety. Leaf area index (LAI), leaf area duration (LAD), leaf chlorophyll, N assimilation and N assimilation rate for both bean growth habits increased with N application rate at no and low weed density. The negative effect of redroot pigweed competition on LAI, LAD, N assimilation and N assimilation rate increased with redroot pigweed density, and with N application rate for the high weed density. Stepwise multiple regression analysis showed that N assimilation and chlorophyll concentration accounted for 0·73–0·87, overall, of the variation in yield loss due to weed competition. It is concluded that greater N assimilation in the semi-erect growth habit compared with the erect growth habit is the cause of its higher competitive ability against the weed, as it improves the effective canopy traits that confer potential for resource pre-emption.

Understanding the physiological mechanisms of biomass accumulation and partitioning in the grain, and the nitrogen (N) uptake associated with different plant densities and N management strategies, is essential for achieving both high yield and N use efficiency (NUE) in maize plants. A field experiment was conducted in 2013 and 2014, using five rates of N application and three plant densities (6·0, 7·5 and 9·0 plants/m2) in Quzhou County on the North China Plain (NCP). The objective was to evaluate whether higher plant density can produce more biomass allocated to the grain to achieve higher grain yield and to determine the optimal N management strategies for different plant densities. The highest grain yield and NUE were achieved in the 7·5 plants/m2 treatment; both the sub-optimal (6·0 plants/m2) and supra-optimal (9·0 plants/m2) plant densities resulted in diminished yield and NUE. Compared to 6·0 plants/m2, the 7·5 plants/m2 treatment displayed higher biomass accumulation during the grain-filling period and also exhibited more biomass allocated to kernels with similar total biomass accumulation compared with the 9·0 plants/m2 treatment, which contributed to its higher grain yield. The N uptake in the 7·5 plants/m2 treatment was similar to that in the 9·0 plants/m2 treatment up to pre-silking. However, the post-silking N uptake of the 7·5 plants/m2 treatment was 66·4 kg/ha, which was 29·1% higher than that of the 9·0 plants/m2 treatment. Furthermore, the highest maize grain yield was achieved in the 0·7 × optimal N rate (ONR × 0·7), ONR and ONR × 1·3 treatments for 6·0, 7·5 and 9·0 plants/m2, respectively, which suggests that different N management strategies are needed for different plant densities. In conclusion, selecting a planting density of 7·5 plants/m2 with an in-season root zone N management is a potentially effective strategy for achieving high grain yield and high NUE for maize production on the NCP.