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.

Sustainable ruminant production systems depend on the ability of livestock to utilize increased quantities of grazed herbage. The current study aimed to compare the effect of white clover (WC) inclusion and perennial ryegrass (PRG) ploidy on herbage dry matter (DM) production, plant morphology, nutritive value and biological nitrogen (N) fixation (BNF) under high N fertilizer use (250 kg N/ha) and high stocking rates (2.75 livestock units/ha). Four sward treatments (diploid-only, tetraploid-only, diploid-WC, tetraploid-WC) were evaluated over a full grazing season at a farmlet scale. White clover inclusion had a significant effect on herbage DM production, herbage growth rate, tiller density, organic matter digestibility, crude protein and BNF. Tetraploid swards had a lower tiller density, lower sward WC content and post-grazing sward height and increased organic matter digestibility and crude protein than diploid swards. White clover inclusion improved herbage DM production and nutritive value across a full grazing season, with tetraploid and diploid swards producing similar herbage DM yields across the year. Perennial ryegrass ploidy had an effect on WC morphology as plants in diploid-WC swards had narrower, longer stolons, fewer branches and more petioles than tetraploid-WC swards. The current study highlights the benefit of including WC in grass-based systems under a high N fertilizer regime and high stocking rate.

The objective of the current study was to evaluate the effects of sugarcane and maize silage mixture v. maize silage in diets of Holstein cows and investigate performance under two environmental conditions. The cows were placed in freestalls, with individuals and stalls assigned to one of four treatments according to a replicated 4 × 4 Latin square design with 20-day periods divided into 11 days of adaptation (wash-out period) and 9 days of collection. Treatments were arranged in a 2 × 2 × 2 factorial design: total diets (maize silage (MS-based diet), the roughage mixture (RM-based diet, sugarcane : maize silage, 500 : 500 g/kg DM) plus concentrate); environmental conditions (with (W) and without (Wo) fan and nebulizers); and measurement times (09.40 and 14.00 h). The temperature and relative humidity was higher at 14.00 h and contributed to increased temperature-humidity index (76.6, W v. 75.9, Wo). Feed dry matter intake (DMI) was similar between diets (20.2 kg/day), but milk production and feed efficiency were lower with RM. Under W conditions, higher fat content and total solids of milk were observed with the RM-based diet, while crude protein and lactose were higher with MS. The Wo conditions increased body surface temperature (BS) in cows fed MS. The rectal temperature (RT) was higher with RM. The BS, RT and respiratory rate were higher at 14.00 h (34.9, 38.6 °C and 58.2 breaths/min) than at 09.40 h. The RM-based diet maintained DMI and milk composition, but not milk production. The use of the cooling system led to higher DMI and feed N efficiency use.

With the development of remote sensing and geostatistical technology, complex environmental variables are increasingly easily quantified and applied in modelling soil organic carbon (SOC). However, this emphasizes data redundancy and multicollinearity problems adding to the difficulty in selecting dominant influential auxiliary variables and uncertainty in estimating SOC stocks. The current paper considers the spatial characteristics of SOC density (SOCD) to construct prediction models of SOCD on the basis of reducing the data dimensionality and complexity using the principal component analysis (PCA) method. A total of 260 topsoil samples were collected from Chahe town, China. Eight environmental variables (elevation, aspect, slope, normalized difference vegetation index, normalized difference moisture index, nearest distance to construction area and road, and land use degree comprehensive index) were pre-analysed by PCA and then extracted as the main principal component variables to construct prediction models. Two geostatistical approaches (ordinary kriging and ordinary co-kriging) and two regression approaches (ordinary least squares and geographically weighted regression (GWR)) were used to estimate SOCD. Results showed that PCA played an important role in reducing the redundancy and multicollinearity of the auxiliary variables and GWR achieved the highest prediction accuracy in these four models. GWR considered not only the spatial characteristics of SOCD but also the related valuable information of the auxiliary attributes. In summary, PCA-GWR is a promising spatial method used here to predict SOC stocks.

In the current study, simulations by five crop models (WOFOST, CERES-Barley, HERMES, DAISY and AQUACROP) were compared for 7–12 growing seasons of spring barley (Hordeum vulgare) at three sites in the Czech Republic. The aims were to compare how various process-based crop models with different calculation approaches simulate different values of transpiration (Ta) and evapotranspiration (ET) based on the same input data and compare the outputs of these simulations with reference data. From the outputs of each model, the water use efficiency (WUE) from Ta (WUETa) and from actual ET (WUEETa) was calculated for grain yields and above-ground biomass yield. The results of the first part of the study show that the model with the Penman approach for calculating ET simulates lower actual ET (ETa) sums, at an average of 250 mm during the growing season, than other models, which use the Penman–Monteith approach and simulate 330 mm on average during the growing season. In the second part of the current study, WUE reference values in the range 1.9–2.4 kg/m3 were calculated for spring barley and grain yield. Values of WUETa/WUEETa calculated from the outputs of individual models for grain yields and above-ground biomass yields ranged from 2.0/1.0 to 5.9/3.8 kg/m3 with an average value of 3.2/2.0 kg/m3 and from 3.9/2.1 to 10.5/6.8 kg/m3 with an average value of 6.5/4.0 kg/m3, respectively. The results confirm that the average values of all models are nearest to actual values.

Policy makers and farmers in north-west Europe are expressing a growing interest in soybean production. However, cool and wet climatic conditions in this region pose challenges for this crop in terms of reaching maturity and producing sufficient yield and create additional disease pressure from the fungal pathogens Sclerotinia sclerotiorum and Rhizoctonia solani. To increase the chance for successful introduction of this new crop in Belgium and to determine the main issues for local soybean breeding programmes, 14 early maturing varieties were screened over a 2-year-period for their agronomic performance. Based on novel bioassays, susceptibility to S. sclerotiorum and R. solani anastomosis group (AG) 2-2IIIB was evaluated. The varieties tested were able to reach sufficient maturity (average seed moisture content of 19.0%) by the beginning of October. Significant differences were observed in most agronomic characteristics, with seed yield and protein content ranging from 2002 to 2916 kg dry matter/ha and 35.5–43.3%, respectively. Taller varieties ripened later but reached higher protein levels compared with shorter varieties. Tolerance to lodging was correlated with seed and protein yield but was not correlated with plant height. Large seeds corresponded with a high protein content. Susceptibility to S. sclerotiorum reflected significant differences between varieties. In contrast, levels of susceptibility to R. solani AG 2-2IIIB were similar between most varieties, with only the variety Primus showing significantly less disease. The results of the current study hold promise for a successful introduction of soybean cultivation in north-west Europe and areas for further crop improvement have been identified.

Remote sensing (RS) offers an efficient and reliable means to map features on Earth. Crop type mapping using RS at various temporal and spatial resolutions plays an important role spanning from environmental to economical. The main objective of the current study was to evaluate the significance of optical data in a multi-temporal crop type classification-based on very high spatial resolution and high spatial resolution imagery. With this aim, three images from WorldView-3 and Sentinel-2 were acquired over Coalville (UK) between April and July 2016. Three vegetation indices (VIs); the normalized difference vegetation index, the green normalized difference vegetation index and soil adjusted vegetation index were generated using red, green and near-infrared spectral bands; then a supervised classification was performed using ground reference data collected from field surveys, Random forest (RF) and decision tree (DT) classification algorithms. Accuracy assessment was undertaken by comparing the classified output with the reference data. An overall accuracy of 91% and κ coefficient of 0·90 were estimated using the combination of RF and DT classification algorithms. Therefore, it can be concluded that integrating very high- and high-resolution imagery with different VIs can be implemented effectively to produce large-scale crop maps even with a limited temporal-dataset.

Quinoa (Chenopodium quinoa Willd) is a dicotyledonous annual species belonging to the family Amaranthaceae, which is nutritionally well balanced in terms of its oil, protein and carbohydrate content. Targeting-induced local lesions in genomes (the TILLING strategy) was employed to find mutations in acetolactate synthase (AHAS) genes in a mutant quinoa population. The AHAS genes were targeted because they are common enzyme target sites for five herbicide groups. Ethyl methane sulfonate (EMS) was used to induce mutations in the AHAS genes; it was found that 2% EMS allowed a mutation frequency of one mutation every 203 kilobases to be established. In the mutant population created, a screening strategy using pre-selection phenotypic data and next-generation sequencing (NGS) allowed identification of a mutation that alters the amino acid composition of this species (nucleotide 1231 codon GTT→ATT, Val→Ile); however, this mutation did not result in herbicide resistance. The current work shows that TILLING combined with the high-throughput of NGS technologies and an overlapping pool design provides an efficient and economical method for detecting induced mutations in pools of individuals.

An experiment was carried out to examine the effects of offering beef steers grass silage (GS) as the sole forage, lupins/triticale silage (LTS) as the sole forage, a mixture of LTS and GS at a ratio of 70:30 on a dry matter (DM) basis, vetch/barley silage (VBS) as the sole forage, a mixture of VBS and GS at a ratio of 70:30 on a DM basis, giving a total of five silage diets. Each of the five silage diets was supplemented with 2 and 5 kg of concentrates/head/day in a 5 × 2 factorial design to evaluate the five silages at two levels of concentrate intake and to examine possible interactions between silage type and concentrate intake. A total of 80 beef steers were used in the 122-day experiment. The GS was well preserved while the whole crop cereal/legume silages had high ammonia-nitrogen (N) concentrations, low lactic acid concentrations and low butyric acid concentrations For GS, LTS, LTS/GS, VBS and VBS/GS, respectively, silage DM intakes were 6.5, 7.0, 7.2, 6.1 and 6.6 (s.e.d. 0.55) kg/day and live weight gains were 0.94, 0.72, 0.63, 0.65 and 0.73 (s.e.d. 0.076) kg/day. Silage type did not affect carcass fatness, the colour or tenderness of meat or the fatty acid composition of the intramuscular fat in the longissimus dorsi muscle.

The feasibility of non-destructive detection and classification of in-shell insect-infested almonds was examined by using multispectral imaging (MSI) technology combined with chemometrics. Differentiation of reflectance spectral data between intact and insect-infested almonds was attempted by using analytical approaches based on principal component analysis and support vector machines, classification accuracy rates as high as 99.1% in the calibration set and 97.5% in the prediction set were achieved. Meanwhile, the in-shell almonds were categorized into three classes (intact, slightly infested and severely infested) based on the degree of damage caused by insect infestation and were characterized quantitatively by the analysis of shell/kernel weight ratio. A three-class model for the identification of intact, slightly infested and severely infested almonds yielded acceptable classification performance (95.6% accuracy in the calibration set and 93.3% in the prediction set). These results revealed that MSI technology combined with chemometrics may be a promising approach for the non-destructive detection of hidden insect damage in almonds and could be used for industrial applications.

Noy-Meir's simple but insightful model of grazing-system dynamics was used to draw broader inferences from empirical data generated by a 17-year field trial with beef cattle grazing a Mediterranean grassland in northern Israel. After calibration of its parameters against the field results, the model predictions were tested against an independent set of data obtained from the study site; they were within acceptable deviations from the inherently noisy field data. The calibrated model was used to analyse the effects of changes to two key grazing-management factors – stocking density and early-season grazing deferment – on biomass dynamics and forage consumption. The simulated results were used to calculate forage deficits and supplementary feed requirements for optimum herd performance during the growth (‘green’) season and throughout the year. The results revealed a critical stocking density of 0.7 Animal Units (AU)/ha, above which early-season deferment reduced the amount of supplementary feed required to maintain the optimum production of the herd. Optimum stocking is higher when the grassland is used mainly in the highly nutritious green season. Responses of the strongly seasonal Mediterranean grassland to the interaction between stocking density and early-season grazing deferment were expressed by a calibrated model, in terms that determine the efficiency of forage supplementation of the herd during the green season and throughout the year.

An experiment was carried out to examine the effects of offering beef cattle five silage diets. These were perennial ryegrass silage (PRGS) as the sole forage, tall fescue/perennial ryegrass silage (FGS) as the sole forage, PRGS in a 50:50 ratio on a dry matter (DM) basis with lupin/triticale silage (LTS), lupin/wheat silage (LWS) and pea/oat silage (POS). Each of the five silage diets was supplemented with 4 and 7 kg of concentrates/head/day in a five silages × two concentrate intakes factorial design. A total of 90 cattle were used in the 121-day experiment. The grass silages were of medium digestibility and were well preserved. The legume/cereal silages had high ammonia N, high acetic acid, low lactic acid, low butyric acid and low digestible organic matter concentrations (542, 562 and 502 g/kg DM for LTS, LWS and POS, respectively). Silage treatment did not significantly affect liveweight gain, carcass gain, carcass characteristics, the instrumental assessment of meat quality or fatty acid composition of the M. longissimus dorsi muscle. In view of the low yields of the legume/cereal crops, it is concluded that the inclusion of spring-sown legume/cereal silages in the diets of beef cattle is unlikely to be advantageous.

The present study was aimed at stimulating the growth and yield of Sri Lankan tea cultivar TRI 2025 grown in different climatic regions in the country. The model was developed and calibrated using weather, crop and soil data collected from different climatic zones. The model is designed to simulate shoot replacement cycle, leaf area of a shoot, shoot growth, dry matter partitioning and tea shoot yield. The model was validated using shoot development and growth data not used for model calibration. These validation data were collected from low, mid and high elevations representing temperature and rainfall gradients in the country. Model calibration showed that thermal time required to initiate the fish leaf, 1st, 2nd and 3rd normal leaf in a tea shoot from the time of natural senescence of the scale leaves were 129, 188, 235, 296 °C days, respectively, and a tea shoot reached the harvestable stage after 393 °C days. The model simulated leaf area (cm2) and fresh weight (g/m2) of tea shoots at different developmental stages and locations which were in good agreement with the measured values at the validation stage (R2 > 0.92 and 0.98, respectively). Similarly, simulated shoot yields (g/m2/month) at the validation stage were strongly correlated with the measured values (n = 12, R2 > 0.58, RMSE = 5–17 g/m2/month). Thus, the model can be used to estimate the shoot yield of tea cultivar TRI 2025 grown in different climatic conditions in Sri Lanka. Areas requiring further improvements to the model are also discussed.

There are many parameters in agriculture that change over time in a sigmoid pattern. In the current study, the double logistic function was used to describe and simulate dry matter (DM) variation of winter rapeseed plant and to explain the growth rate under water stress. Irrigation treatments were full irrigation at all growth stages, water stress during the vegetative stage in early spring, water stress at flowering and podding stages, water stress at grain filling stage and rain-fed treatment with supplemental irrigation at time of planting. A high value for the goodness of fit (0.996) and low value for normalized root mean square error (0.085) showed that the double logistic function can describe and simulate DM variation of rapeseed accurately. DM predicted by the double logistic equation based on growing degree day was slightly closer to the measured DM compared with the DM predicted by the double logistic equation based on days after planting. Results showed that growth rate before the winter cold period was lower than that after this period. There were two maximum growth rates for winter rapeseed: the first occurred before cold period and another after.

The current research paper addresses the hypothesis that management system (grazing vs. stabling) and/or stage of lactation (early- to late-lactation) can influence the lactation performance and milk fatty acid (MFA) profile in dromedary camels. The results obtained revealed that milk and protein yields of stabled camels were higher, while milk fat content was lower compared to grazing camels. In addition, stabled camels produced milk richer in short- and medium-chains fatty acids but lower in long-chain fatty acids and fatty acids linked with possible health benefits such as oleic acid, vaccenic acid (VA) and rumenic acid (RA), when compared to grazing camels. Moreover, atherogenicity index was higher, while overall Δ9-desaturase and health-promoting indices were lower in stabled camels. In a similar way, results demonstrated an increase in milk fat and protein contents as lactation advanced. In fact, camels at mid-lactation produced milk richer in short- and medium-chain fatty acids as well as total saturated fatty acids but poorer in oleic acid, VA, RA, long-chain fatty acids and total unsaturated fatty acids, when compared to milk samples collected at early stage of lactation. Moreover, compared to early- and late-lactations, atherogenicity index was higher while overall-Δ9-desaturase and health promoting indexes were lower at mid-lactation. In conclusion, the intensive stabling system and mid-lactation stage can alter lactation performance and MFA profile in dairy dromedary camels.

Cultivated pastures in southern China are being used to improve forage productivity and animal performance, but studies on grazing behaviour of goats in these cultivated pastures are still rare. In the current study, the grazing behaviour of Yunling black goats under low (5 goats/ha) and high (15 goats/ha) stocking rates (SRs) was evaluated. Data showed that the proportion of time goats spent on activities was: eating (0.59–0.87), ruminating (0.05–0.35), walking (0.03–0.06) and resting (0.01–0.03). Compared with low SR, goats spent more time eating and walking, and less time ruminating and resting under high SR. Goats had similar diet preferences under both SR and preferred to eat grasses (ryegrass and cocksfoot) more than a legume (white clover). The distribution of eating time on each forage species was more uniform under high v. low SR. Bites/step, bite weight and daily intake were greater under low than high SR. Results suggest that the SR affects grazing behaviour of goats on cultivated pasture, and identifying an optimal SR is critical for increasing bite weight and intake.

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.

Superior and inferior rice grains have different weights and are located on the upper primary branch and lower secondary branches of the panicle, respectively. To study differences in germination vigour of these two types of grain, a number of factors were investigated from 0 to 48 h of germination. The present study demonstrated that in inferior grains the starch granule structure was looser at 0 h, with full water absorption at 48 h, while in superior grains the structure was tight and dense. Relative water content increased, and dry matter decreased, more rapidly in inferior grains than in superior ones. Abscisic acid and gibberellin levels, as well as α-amylase activity, also changed more rapidly in inferior grains, while soluble sugar content and amylase coding gene expression increased more rapidly in inferior than superior grains during early germination. The expression of OsGAMYB was higher in inferior grains at 24 h but higher in superior grains at 48 h. The phenotypic index of seedlings was higher in seedlings from superior grains at the two-leaf stage. However, the thousand-grain weight and yield per plant in superior and inferior plants showed no significant difference at harvest. The present study indicates that inferior grains germinate faster than superior ones in the early germination stage. Although inferior grains produced weaker seedlings, it is worthwhile using them in rice production due to their comparative yield potential over that of superior grains.

Good canopy structure is essential for optimal maize (Zea mays L.) production. However, creating appropriate maize canopy structure can be difficult, because the characteristics of individual plants are altered by changes in plant age, density and interactions with neighbouring plants. The objective of the current study was to find a reliable method for building good maize canopy structure by analysing changes in canopy structure, light distribution and grain yield (GY). A modern maize cultivar (ZhengDan958) was planted at 12 densities ranging from 1.5 to 18 plants/m2 at two field locations in Xinjiang, China. At the silking stage (R1), plant and ear height increased with plant density as well as leaf area index (LAI), whereas leaf area per plant decreased logarithmically. The fraction of light intercepted by the plant (F) increased with increasing plant density, but the light extinction coefficient (K) decreased linearly from 0.61 to 0.39. Taking the optimum value of F (95%) as an example, and using measured values of K for each plant density at R1 and the equation from Beer's law, the corresponding (theoretical) LAI for each plant density was calculated and optimum plant density (9.72 plants/m2) obtained by calculating the difference between theoretical LAIs and actual observations. Further analysis showed that plant density ranging from 10.64 to 11.55 plants/m2 yielded a stable GY range. Therefore, taking into account the persistence time for maximum LAI, the plant density required to obtain an ideal GY maize canopy structure should be increased by 10–18% from 9.72 plants/m2.

A probabilistic crop forecast based on ensembles of crop model output (CMO) estimates offers a myriad of possible realizations and probabilistic forecasts of green water components (precipitation and evapotranspiration), crop yields and green water footprints (GWFs) on monthly or seasonal scales. The present paper presents part of the results of an ongoing study related to the application of ensemble forecasting concepts for agricultural production. The methodology used to produce the ensemble CMO using the ensemble seasonal weather forecasts as the crop model input meteorological data without the perturbation of initial soil or crop conditions is presented and tested for accuracy, as are its results. The selected case study is for winter wheat growth in Austria and Serbia during the 2006–2014 period modelled with the SIRIUS crop model. The historical seasonal forecasts for a 6-month period (1 March-31 August) were collected for the period 2006–2014 and were assimilated from the European Centre for Medium-range Weather Forecast and the Meteorological Archival and Retrieval System. The seasonal ensemble forecasting results obtained for winter wheat phenology dynamics, yield and GWF showed a narrow range of estimates. These results indicate that the use of seasonal weather forecasting in agriculture and its applications for probabilistic crop forecasting can optimize field operations (e.g., soil cultivation, plant protection, fertilizing, irrigation) and takes advantage of the predictions of crop development and yield a few weeks or months in advance.