Some biological and chemical properties of a Gleysol were examined after 24 years of soil tillage (chisel plough – CP, mouldboard plough – MP, no-till – NT) and that of ploughing the 24-yr NT (P-NT) once, in two cropping systems (conventional – CONV, organic – ORG) applied over 4 years (2007–2010) of a long-term experiment (autumn 1987–autumn 2011) at La Pocatière, Québec, Canada. The 0–10, 10–20 and 20–30 cm soil depths were sampled in autumn 2011 after a maize trial. Tillage affected light fraction organic carbon (LFOC), light fraction organic nitrogen (LFON) and mineralizable N (Nmin) in soil, with the lowest LFOC, LFON and Nmin values in the MP treatment. No-till had lower soil pH than the other tillage systems in the 10–20 and 20–30 cm soil depths. Tillage affected the amounts of nitrate-N in 0–10 and 10–20 cm soil depths, with the lowest amounts for MP (4.3 kg nitrate-N/ha) compared with NT (7.2 or 8.5 kg nitrate-N/ha) or CP (7.7 kg nitrate-N/ha). The P-NT had no negative impact on organic C and N, or available nutrients in soil. Cropping system had no effect on soil organic C and N, available nutrients or pH. Findings suggest that long-term NT or CP may result in greater storage of organic C and N in soil and improve available nutrients compared with MP. Ploughing 25-year-old NT plots redistributed available nutrients in the profile but had no negative effect on soil organic C or N.

Prior to applying the cropping system model-CERES-Rice model to deep water rice (DWR), it is important to estimate the rice genetic coefficients (GC). The goal of the current study was to compare two methods for estimating GC using a GC calculator (GENCALC) and generalized likelihood uncertainty estimation (GLUE) for three flooded rice (FDR) varieties. Data from a field experiment on the effect of planting date and variety on FDR production was conducted in 2009 on a DWR area in Bang Taen His Majesty's Private Development Project, Prachin Buri, Thailand. The experimental design was split-plot with four main plots (planting dates) and three sub-plots (FDR varieties) with four replications. The simulated values for anthesis date, maturity date and grain weight using GENCALC produced normalized root mean square errors (RMSEn) of 3.97, 3.69 and 3.68, while using GLUE produced RMSEn of 3.67, 2.50 and 3.68, respectively. The simulated grain number and grain yield under GENCALC GC were not significantly different from the observed values but were higher than simulated values for GLUE GC. Simulated values of above-ground biomass for both GENCALC (11 727 kg/ha) and GLUE GC (11 544 kg/ha) were overestimated compared to observed values (8512 kg/ha). In addition, good agreements of leaf N values were found with D-index values of 0.94 and 0.96 using GENACALC and GLUE GC simulations, respectively. Therefore, the GENCALC and GLUE GC estimators of DSSAT can both be used for estimating GC of FDR in the DWR area in Thailand and similar agro-ecosystems in Southeast Asia.

Bacterial inoculation of soybean seeds to improve biological nitrogen fixation is a well-known practice to achieve higher seed and protein yield with reduced fertilization. The optimal inoculation strategy in temperate regions is unknown because soybeans are rarely cultivated under colder growing conditions. The aim of the present work was to determine the most suitable inoculation strategy for soybean cultivation in Belgium. Field trials were set up with four Bradyrhizobium inoculants (HiStick, Force 48, Biodoz and Optimize) at two locations over 2 years (2014–2015) and compared with a non-inoculated control treatment. In addition, HiStick was tested at three doses and Optimize at two time periods prior to sowing. Under Belgian conditions, all inoculants were effective in establishing rhizobial symbiosis, resulting in increased yield, protein content, protein yield and thousand-grain weight compared with the non-inoculated control. A single dose of HiStick was sufficient to establish symbiosis. Pre-inoculation with Optimize 2 weeks before sowing gave an intermediate performance for most parameters between the non-inoculated control treatment and inoculation with Optimize 24 h prior to sowing. Among the four products tested, Biodoz seemed the best product for inoculation under cool growing conditions. Based on the atpD gene, the bacterial strain of Biodoz showed complete similarity with Bradyrhizobium diazoefficiens, while strains of other products were identified as Bradyrhizobium japonicum. In vitro growing capacity of the Biodoz strain at 8 °C was higher compared with the other strains. Better cold adaptation of the Biodoz strain might be a possible explanation for the better performance of Biodoz in Belgium.

Plant ecotypes represent heterogeneous, local adaptation of domesticated species and thereby provide genetic resources that meet current and new challenges for farming in drought-prone environments. A total of 536 Sardari bread wheat ecotypes, assembled from different geographical regions of Iran, were studied under rainfed cold conditions for three cropping seasons (2009–12). The main objectives were to (i) quantify the performance of the Sardari wheat ecotypes under cold rainfed conditions and (ii) provide information that would enable germplasm management and utilization in wheat breeding programmes to enhance the development of better adapted varieties for the rainfed cold conditions of Iran. All the ecotypes were evaluated for grain yield and several drought-adaptive traits. Combined analysis of variance indicated significant differences between years, ecotypes and their interaction effects for each studied trait. The Sardari wheat ecotypes showed considerable variability for the phenotypic traits and stability performance that could be utilized for wheat improvement in cold rainfed areas. Many of the Sardari wheat ecotypes exhibited a high combination of yield and stability for both drought and cold stresses, comparable to control cultivars. Multivariate analyses indicated several significant patterns among ecotypes from different geographical regions. In conclusion, selection from current Sardari wheat ecotypes may lead to yield stability and specific adaptation, which provides opportunities for this collection to be useful for genetic improvement of drought tolerance in bread wheat.

The significant expansion of whiskey distillation in Ireland has increased requirements on the Irish malting barley industry to supply spring barley with low grain nitrogen concentration (GNC). Published literature suggests that genetics, soil type and environmental conditions are the predominant drivers controlling production of malting barley with low GNC values. However, it is acknowledged that agronomic practices such as sowing date and nitrogen (N) application are also important factors in determining the grain yield (GY) and grain quality (GQ) of malting barley. The effects of four N fertilizer rates (90, 110, 130 and 150 kg N/ha) and two sowing dates (March and April) on GY and GQ of a two-row spring barley variety (Hordeum vulgare L. cvar Overture) was evaluated at two different sites over a 3-year period (2014–2016). Earlier sowing dates resulted in significantly higher mean GY (7.98 t/ha) compared with later sowing dates (7 t/ha). GY and GNC also increased consistently with greater increments of fertilizer N. Earlier sowing dates also significantly improved several distilling malt quality parameters, such as soluble extract (SE), fermentable extract, predicted spirit yield and fermentability. Later sowing dates increased diastatic power and soluble N. The results of the current study suggest that the likelihood of producing spring malting barley with low GNC values and better malting quality is enhanced through earlier sowing dates on suitable soil types. Earlier sowing dates also facilitated the use of higher fertilizer N rates, enabling high GY potential without crossing the GNC threshold for the distilling market.

The present study aim to explore temporal–spatial patterns of water use (WU) efficiency and its influencing factors of maize production in China during 1998–2010. WU and productivity (WP) were quantified by taking irrigation loss into account and the links between WP and nine selected indicators were revealed by the partial least squares regression (PLSR) model. Results showed that national WU and WP in maize production were 138.56 cubic gigametres (Gm3; 0.755 green and 0.245 blue) and 1.079 kg/m3, respectively. WP was enhanced in the present study due to an increase in irrigated crop yield. Provinces located in the middle–lower part of the Yellow River had high proportions of green water and WP, while high proportions of irrigation water and low WP were found in Northwest China. The dosage of pesticides per unit area, relative humidity, average temperature and precipitation were the dominant factors that affected WP. However, the relationships between WP and solar radiation, fertilizer, agricultural machinery power, irrigation proportion and irrigated efficiency were not significant. Findings of the present research may also provide a reference for regional agricultural water management.

The use of fast and non-destructive techniques for identifying sugarcane varieties enables the development of automatic sorting systems, contributing towards improving pre-processing steps in the alcohol and sugar industries. In this context, principal component analysis (PCA), factorial discriminant analysis (FDA), stepwise forward discriminant analysis (SFDA) and partial least-squares discriminant analysis (PLS-DA) were used to classify four Brazilian sugarcane varieties based on visible/near infrared (Vis/NIR) spectral reflectance measurements (450–1000 nm range) of stalks. All wavelengths contributed towards discriminating the sugarcane varieties, but the 600–750 nm range was most relevant. When evaluating PCA results considering the four sugarcane varieties, two of them overlapped and it was only possible to use classifiers of three varieties. Factorial discriminant analysis, PLS-DA and SFDA reached correct classifications of 0.81, 0.82 and 0.74, respectively, when considering the external validation data and the four sugarcane varieties evaluated. Results showed that Vis/NIR spectroscopy combined with discriminating methods is a promising tool for non-destructive and fast sugarcane variety classification, which can be used in the agro-food industry or directly in the field.

A collection of 45 isolates was created based on bacteria isolated from maize, broad bean, wheat, rye and wild plants such as horsetail and burdock. The aim of the current study was to isolate the bacteria, and then identify and assess the degree of genomic diversity. The molecular identification of microsymbionts isolated from the endosphere (root and stem) of plants grown in agricultural soils was performed using 16S rRNA gene sequencing. To evaluate the genomic diversity between strains that occurred in multiple host plants, 18 bacterial isolates representing four species were subjected to denaturing gradient gel electrophoresis. The 16S rDNA analysis assigned all bacterial isolates to ten genera, from which Rhizobium was represented by 19 isolates, Delftia by 11, Agrobacterium by five, Stenotrophomonas by three, Brevundimonas by two and Novosphingobium, Variovorax, Collimonas, Achromobacter and Comamonas by only one isolate. Furthermore, the genomic diversity of the 11 isolates of Delftia sp. was assessed using the BOX – polymerase chain reaction (BOX-PCR) and enterobacterial repetitive intergenic consensus – PCR (ERIC-PCR) methods. Typing patterns and analysis using BOX-PCR and ERIC-PCR data demonstrated similarities among the tested isolates. In general, the results obtained with BOX-PCR and ERIC-PCR were in good agreement. However, a greater degree of differentiation patterns of the genomic DNA was obtained in the ERIC-PCR method.

Bovine herpes virus 1 (BHV-1) manifests as a latent viral infection putatively affecting bovines. Understanding its effect on cattle herds is critical to maintaining sustainable beef and dairy production systems, as well as aiding in the development of herd health policies. The primary objective of the current study was, therefore, to use a whole-farm bio-economic model to evaluate the effect of herd seroprevalence to BHV-1 on the productive and economic performance of a spring calving beef cow herd. As part of a wider epidemiological study of herd pathogen status, a total of 4240 cows from 134 spring calving beef cow herds across the Republic of Ireland were blood sampled to measure the seroprevalence to BHV-1. Using data from a national breeding database, productive and reproductive performance indicators were used to parameterize a single year, static and deterministic whole-farm bio-economic model. A spring-calving, pasture-based suckler beef cow production system with an emphasis on calf-to-weanling production was simulated. The impact of BHV-1 seropositivity on whole-farm technical and economic performance was relatively small, with a marginal drop in the net margin of 4% relative to a baseline seronegative herd. Subsequent risk factors for increased pathogenicity were considered such as total herd size, percentage of intra-herd movements and vaccination status for BHV-1. In contrast to all others, scenarios representing herds that were either small in size or those which indicated an active vaccination policy for BHV-1 had no reduction in net margin against the baseline as a result of seropositivity to BHV-1.

The aim of the current study was to estimate additive and dominance genetic variance components for days from calving to first service (DFS), a number of services to conception (NSC) and days open (DO). Data consisted of 25 518 fertility records from first parity dairy cows collected from 15 large Holstein herds of Iran. To estimate the variance components, two models, one including only additive genetic effects and another fitting both additive and dominance genetic effects together, were used. The additive and dominance relationship matrices were constructed using pedigree data. The estimated heritability for DFS, NSC and DO were 0.068, 0.035 and 0.067, respectively. The differences between estimated heritability using the additive genetic and additive-dominance genetic models were negligible regardless of the trait under study. The estimated dominance variance was larger than the estimated additive genetic variance. The ratio of dominance variance to phenotypic variance was 0.260, 0.231 and 0.196 for DFS, NSC and DO, respectively. Akaike's information criteria indicated that the model fitting both additive and dominance genetic effects is the best model for analysing DFS, NSC and DO. Spearman's rank correlations between the predicted breeding values (BV) from additive and additive-dominance models were high (0.99). Therefore, ranking of the animals based on predicted BVs was the same in both models. The results of the current study confirmed the importance of taking dominance variance into account in the genetic evaluation of dairy cows.

Monitoring milk quality traits and the classification of raw milk are important steps for generating high-quality dairy products. Given the important roles of the BRG1/BRM-associated factor 60c (BAF60c) gene in the regulation of physiological growth and production, the objective of the current study was to analyse the association between the BAF60c gene and milk quality and establish a gene-based method for pre-evaluating raw milk quality. For this purpose, DNA was isolated from 507 milk samples and genotyped using the polymerase chain reaction-restricted fragment length polymorphism method. Milk quality traits including milk protein percentage (MPP), milk fat percentage (MFP), lactose percentage (LP) and total solids content (TSC) were also evaluated from the same 507 milk samples. The newly found 6060 T > C mutation of the BAF60c gene was associated significantly with MPP and LP, but not with MFP and TSC. The results demonstrated that this mutation could be used for the pre-evaluation of MPP and LP; therefore, raw milk could be graded according to different genotypes.