Performance of carrot and onion seed primed with beneficial microorganisms in glasshouse and field trials

Beneficial microorganisms (Clonostachys rosea IK726, Pseudomonas chlororaphis MA342, Pseudomonas fluorescens CHA0, Trichoderma harzianum T22 and Trichoderma viride S17a) were successfully applied to carrot and onion seed during a commercial drum priming process. Applied microorganisms were recovered above the target of at least 1 × 105 cfu g−1 seed following subsequent application of pesticides to the seed according to standard commercial practices of film-coating carrot and pelletting onion seed. Two glasshouse experiments consistently showed that priming improved emergence of carrot seed and that C. rosea IK726 further improved emergence time. Priming improved emergence of onion seed in one glasshouse experiment, but had an unexpected negative effect on emergence in the second experiment, possibly due to the proliferation of an unidentified indigenous microorganism during priming, becoming deleterious in high numbers. In this experiment, the application of beneficial microorganisms during priming negated this effect and significantly improved emergence. For each crop, a series of field trials was also carried out over three years, at two different sites each year. Although some positive effects of different seed treatments were seen on emergence or yield in individual field trials, no consistent effects were found for primed or microorganism-treated seed across all sites and years. However, a combined analysis of data for all years and sites indicated that pesticide application did consistently improve emergence and yield for both carrot and onion. This is the first comprehensive study assessing glasshouse and field performance of carrot and onion seed primed with beneficial microorganisms during a commercial process of drum priming in the UK

Herbicide mixtures at high doses slow the evolution of resistance in experimentally evolving populations of Chlamydomonas reinhardtii

The widespread evolution of resistance to herbicides is a pressing issue in global agriculture. Evolutionary principles and practices are key to the management of this threat to global food security. The application of mixtures of herbicides has been advocated as an anti-resistance strategy, without substantial empirical support for its validation. We evolved experimentally populations of the unicellular green chlorophyte, Chlamydomonas reinhardtii, to minimum inhibitory concentrations (MICs) of single-herbicide modes of action and to pair-wise and three-way mixtures between different herbicides at various total combined doses. Herbicide mixtures were most effective when each component was applied at or close to its MIC. When doses were high, increasing the number of mixture components was also effective in reducing the evolution of resistance. Employing mixtures at low combined doses did not retard resistance evolution, even accelerating the evolution of resistance to some components. At low doses, increasing the number of herbicides in the mixture tended to select for more generalist resistance (cross-resistance). Our results reinforce findings from the antibiotic resistance literature and confirm that herbicide mixtures can be very effective for resistance management, but that mixtures should only be employed where the economic and environmental context permits the applications of high combined doses

Statistical modelling of transcript profiles of differentially regulated genes

Background: The vast quantities of gene expression profiling data produced in microarray studies, and the more precise quantitative PCR, are often not statistically analysed to their full potential. Previous studies have summarised gene expression profiles using simple descriptive statistics, basic analysis of variance (ANOVA) and the clustering of genes based on simple models fitted to their expression profiles over time. We report the novel application of statistical non-linear regression modelling techniques to describe the shapes of expression profiles for the fungus Agaricus bisporus, quantified by PCR, and for E. coli and Rattus norvegicus, using microarray technology. The use of parametric non-linear regression models provides a more precise description of expression profiles, reducing the "noise" of the raw data to produce a clear "signal" given by the fitted curve, and describing each profile with a small number of biologically interpretable parameters. This approach then allows the direct comparison and clustering of the shapes of response patterns between genes and potentially enables a greater exploration and interpretation of the biological processes driving gene expression. Results: Quantitative reverse transcriptase PCR-derived time-course data of genes were modelled. "Splitline" or "broken-stick" regression identified the initial time of gene up-regulation, enabling the classification of genes into those with primary and secondary responses. Five-day profiles were modelled using the biologically-oriented, critical exponential curve, y(t) = A + (B + Ct)Rt + ε. This non-linear regression approach allowed the expression patterns for different genes to be compared in terms of curve shape, time of maximal transcript level and the decline and asymptotic response levels. Three distinct regulatory patterns were identified for the five genes studied. Applying the regression modelling approach to microarray-derived time course data allowed 11% of the Escherichia coli features to be fitted by an exponential function, and 25% of the Rattus norvegicus features could be described by the critical exponential model, all with statistical significance of p < 0.05. Conclusion: The statistical non-linear regression approaches presented in this study provide detailed biologically oriented descriptions of individual gene expression profiles, using biologically variable data to generate a set of defining parameters. These approaches have application to the modelling and greater interpretation of profiles obtained across a wide range of platforms, such as microarrays. Through careful choice of appropriate model forms, such statistical regression approaches allow an improved comparison of gene expression profiles, and may provide an approach for the greater understanding of common regulatory mechanisms between genes

Temperature, light and nitrate sensing coordinate Arabidopsis seed dormancy cycling resulting in winter and summer annual phenotypes

Seeds use environmental cues to sense the seasons and their surroundings to initiate the plants life cycle. Dormancy cycling underlying this process is extensively described, but the molecular mechanism is largely unknown. To address this we selected a range of representative genes from published array experiments in the laboratory and investigated their expression patterns in seeds of Arabidopsis ecotypes, having contrasting life cycles, over an annual dormancy cycle in the field. We show how mechanisms identified in the laboratory are coordinated in response to the soil environment to determine dormancy cycles that result in winter and summer annual phenotypes. Our results are consistent with a seed specific response to seasonal temperature patterns (temporal sensing) involving the gene DELAY OF GERMINATION1 (DOG1) that indicates the correct season; and concurrent temporally driven co-opted mechanisms that sense spatial signals i.e. nitrate via CBL-INTERACTING PROTEIN KINASE 23 (CIPK23) phosphorylation of the NITRATE TRANSPORTER 1 (NRT1.1) and light via PHYTOCHROME A (PHYA). In both ecotypes studied, when all three genes have low expression there is enhanced GIBBERELLIN 3 BETA-HYDROXYLASE 1 (GA3ox1) expression, exhumed seeds have the potential to germinate in the laboratory, and the initiation of seedling emergence occurs following soil disturbance (exposure to light) in the field. Unlike DOG1, expression of MOTHER of FLOWERING TIME (MFT) has an opposite thermal response in seeds of the two ecotypes indicating a role in determining their different dormancy cycling phenotypes

A sensitivity analysis of the prediction of the nitrogen fertilizer requirement of cauliflower crops using the HRI WELL_N computer model

HRI WELL_N is an easy to use computer model, which has been used by farmers and growers since 1994 to predict crop nitrogen (N) requirements for a wide range of agricultural and horticultural crops. A sensitivity analysis was carried out to investigate the model predictions of the N fertilizer requirement of cauliflower crops, and, at that rate, the yield achieved, yield response to the fertilizer applied, N uptake, NO3-N leaching below 30 and 90 cm and mineral N at harvest. The sensitivity to four input factors – soil mineral N before planting, mineralization rate of soil organic matter, expected yield and duration of growth – was assessed. Values of these were chosen to cover ranges between 40% and 160% of values typical for field crops of cauliflowers grown in East Anglia. The assessments were made for three soils – sand, sandy loam and silt – and three rainfall scenarios – an average year and years with 144% or 56% of average rainfall during the growing season. The sensitivity of each output variable to each of the input factors (and interactions between them) was assessed using a unique ‘sequential' analysis of variance approach developed as part of this research project. The most significant factors affecting N fertilizer requirement across all soil types/rainfall amounts were soil mineral N before planting and expected yield. N requirement increased with increasing yield expectation, and decreased with increasing amounts of soil mineral N before planting. The responses to soil mineral N were much greater when higher yields were expected. Retention of N in the rooting zone was predicted to be poor on light soils in the wettest conditions suggesting that to maximize N use, plants needed to grow rapidly and have reasonable yield potential. Assessment of the potential impacts of errors in the values of the input factors indicated that poor estimation of, in particular, yield expectation and soil mineral N before planting could lead to either yield loss or an increased level of potentially leachable soil mineral N at harvest. The research demonstrates the benefits of using computer simulation models to quantify the main factors for which information is needed in order to provide robust N fertilizer recommendations

The effect of within-crop habitat manipulations on the conservation biological control of aphids in field-grown lettuce

Within-crop habitat manipulations have the potential to increase the biological control of pests in horticultural field crops. Wildflower strips have been shown to increase the abundance of natural enemies, but there is little evidence to date of an impact on pest populations. The aim of this study was to determine whether withincrop wildflower strips can increase the natural regulation of pests in horticultural field crops. Aphid numbers in plots of lettuce grown adjacent to wildflower strips were compared with those in plots grown in the absence of wildflowers. The presence of wildflower strips led to a decrease in aphid numbers on adjacent lettuce plants during June and July, but had less impact in August and September. The decrease in aphid numbers was greatest close to the wildflower strips and, the decrease in aphid numbers declined with increasing distance from the wildflower strips, with little effect at a distance of ten metres. The main natural enemies found in the crop were those that dispersed aerially, which is consistent with data from previous studies on cereal crops. Analysis and interpretation of natural enemy numbers was difficult due to low recovery of natural enemies, and the numbers appeared to follow changes in aphid abundance rather than being directly linked to the presence of wildflower strips. Cutting the wildflower strips, to remove floral resources, had no impact on the reduction in aphid numbers achieved during June and July, but decreased the effect of the wildflower strips during August and September. The results suggest that wildflower strips can lead to increased natural regulation of pest aphids in outdoor lettuce crops, but more research is required to determine how this is mediated by natural enemies and how the impact of wildflower strips on natural pest regulation changes during the growing season

Investigating the effects of inter-annual weather variation (1968- 2016) on the functional response of cereal grain yield to applied nitrogen, using data from the Rothamsted Long-Term experiments

The effect of weather on inter-annual variation in the crop yield response to nitrogen (N) fertilizer for winter wheat (Triticum aestivvum L.) and spring barley (Hordeum vulgare L.) was investigated using yield data from the Broadbalk Wheat and Hoosfield Spring Barley long-term experiments at Rothamsted Research. Grain yields of crops from 1968 to 2016 were modelled as a function of N rates using a linear-plus-exponential (LEXP) function. The extent to which inter-annual variation in the parameters of these responses was explained by variations in weather (monthly summarized temperatures and rainfall), and by changes in the cultivar grown, was assessed. The inter-annual variability in rainfall and underlying temperature influenced the crop N response and hence grain yields in both crops. Asymptotic yields in wheat were particularly sensitive to mean temperature in November, April and May, and to total rainfall in October, February and June. In spring barley asymptotic yields were sensitive to mean temperature in February and June, and to total rainfall in April to July inclusive and September. The method presented here explores the separation of agronomic and environmental (weather) influences on crop yield over time. Fitting N response curves across multiple treatments can support an informative analysis of the influence of weather variation on the yield variability. Whilst there are issues of the confounding and collinearity of explanatory variables within such models, and that other factors also influence yields over time, our study confirms the considerable impact of weather variables at certain times of the year. This emphasizes the importance of including weather temporal variation when evaluating the impacts of climate change on crops

Primordia initiation of mushroom (Agaricus bisporus) strains on axenic casing materials

The mushroom (Agaricus bisporus) has a requirement for a ‘‘casing layer’’ that has specific physical, chemical and microbiological properties which stimulate and promote the initiation of primordia. Some of these primordia then may develop further into sporophores, involving differentiation of tissue. Wild and commercial strains of A. bisporus were cultured in axenic and nonaxenic microcosms, using a rye grain substrate covered by a range of organic and inorganic casing materials. In axenic culture, A. bisporus (commercial strain A15) was capable of producing primordia and mature sporophores on charcoal (wood and activated), anthracite coal, lignite and zeolite, but not on bark, coir, peat, rockwool, silica or vermiculite. Of six strains tested, only the developmental variant mutant, B430, produced rudimentary primordia on axenic peat-based casing material. However, none of these rudimentary primordia developed differentiated tissues or beyond 4 mm diameter, either on axenic casing material in the microcosms or in larger-scale culture. In larger-scale, nonaxenic culture, strain B430 produced severely malformed but mature sporophores in similar numbers to those of other strains. Typically, 3–6% of primordia developed into mature sporophores, but significant differences in this proportion, as well as in the numbers of primordia produced, were recorded between 12 A. bisporus strains

A strong immune response in young adult honeybees masks their increased susceptibility to infection compared to older bees

Honeybees, Apis mellifera, show age-related division of labor in which young adults perform maintenance ("housekeeping") tasks inside the colony before switching to outside foraging at approximately 23 days old. Disease resistance is an important feature of honeybee biology, but little is known about the interaction of pathogens and age-related division of labor. We tested a hypothesis that older forager bees and younger "house" bees differ in susceptibility to infection. We coupled an infection bioassay with a functional analysis of gene expression in individual bees using a whole genome microarray. Forager bees treated with the entomopathogenic fungus Metarhizium anisopliae s.l. survived for significantly longer than house bees. This was concomitant with substantial differences in gene expression including genes associated with immune function. In house bees, infection was associated with differential expression of 35 candidate immune genes contrasted with differential expression of only two candidate immune genes in forager bees. For control bees (i.e. not treated with M. anisopliae) the development from the house to the forager stage was associated with differential expression of 49 candidate immune genes, including up-regulation of the antimicrobial peptide gene abaecin, plus major components of the Toll pathway, serine proteases, and serpins. We infer that reduced pathogen susceptibility in forager bees was associated with age-related activation of specific immune system pathways. Our findings contrast with the view that the immunocompetence in social insects declines with the onset of foraging as a result of a trade-off in the allocation of resources for foraging. The up-regulation of immune-related genes in young adult bees in response to M. anisopliae infection was an indicator of disease susceptibility; this also challenges previous research in social insects, in which an elevated immune status has been used as a marker of increased disease resistance and fitness without considering the effects of age-related development

The outstanding scientist, R.A. Fisher:His views on eugenics and race

R.A. Fisher was one of the greatest scientists of the 20th century (Fig. 1). He was a man of extraordinary ability and originality whose scientific contributions ranged over a very wide area of science, from biology through statistics to ideas on continental drift, and whose work has had a huge positive impact on human welfare. Not surprisingly, some of his large volume of work is not widely used or accepted at the current time, but his scientific brilliance has never been challenged. He was from an early age a supporter of certain eugenic ideas, and it is for this reason that he has been accused of being a racist and an advocate of forced sterilisation (Evans 2020). His promotion of eugenics has recently caused various organisations to remove his name from awards and dedications of buildings (Tarran 2020; Rothamsted Research 2020; Society for the Study of Evolution 2020; Gonville and Caius College 2020). A primary aim of this paper is to conduct a careful analysis of his own writings in these areas. Our purpose is neither to defend nor attack Fisher’s work in eugenics and views on race, but to present a careful account of their substance and nature.Publisher PDFPeer reviewe