Innovative cropping systems designed to reach both environmental and production targets: Data set of biotic and abiotic variables from a twelve-year French field trial.

The data set describes variables collected from a French (N 48.84°, E 1.95°) field trial, over a twelve-year period (2009-2020), in which four innovative cropping systems designed to reach multiple environmental and production goals were assessed. The four cropping systems were designed with new combinations of agricultural practices; they differed in terms of pesticide uses, nitrogen inputs, tillage practices, and crop sequences. Both biotic and abiotic variables were measured. In a previous data paper, we focused on nitrogen fluxes collected from two systems, over eight years (2009-2016). In the present one, we enlarge the scope of the variables, including more crop descriptions and environmental indicators, from all four systems, and over a longer period (2009-2020). The biotic data are: growth stages; aboveground plant nitrogen content and biomass collected at different growth stages, depending on the species; yield components of all the crops; and yield harvested with a combine machine. No weed, crop disease, and pest data are described. The abiotic data are physical and chemical properties of the soil (i.e. texture, calcium carbonate content, pH, organic carbon contents, and nitrogen contents) collected at different assessment periods. All agricultural practices, and climate were regularly recorded, and the treatment frequency indexes and the energy consumptions were computed. These data could be used for benchmarking, to design low-input systems, to improve models for parameterization and validation, and to increase the predictive accuracy of models of crop growth and development, specifically for orphan species such as linseed, faba bean or hemp, and for soil carbon and soil nitrogen fluxes in various conditions.

Unlike woodland edges, flower strips do not act as a refuge for cabbage stem flea beetle aestivation.

BACKGROUND: Semi-natural habitats are generally considered to be beneficial to natural enemies of crop pests and pollinators. However, they could also be used by pests, such as the Cabbage Stem Flea Beetle (CSFB), Psylliodes chrysocephala, a major pest of winter oilseed rape, Brassica napus. Adults emerge from pupation in late spring and move to aestivation habitats. Published reports identify forest edges as the major shelter used, but flower strips may also constitute an alternative habitat. This study aimed to: (i) determine the role of perennial flower strips in CSFB aestivation in comparison with woodland edges; (ii) determine the influence of landscape composition on the abundance of aestivating CSFB and (iii) identify the characteristics of the local habitat associated with a high abundance of aestivating CSFB. RESULTS: CSFB emergence from aestivation was monitored with emergence traps from mid-August to mid-October 2021, at 14 sites in France. We found that CSFB preferred woodland edges and did not aestivate in flower strips. We found a negative effect of percentage woodland cover only for the smallest scale studied (250 m radius). We also found positive effects of the percentage of litter and mean tree circumference on the number of aestivating CSFB in woodland edges. CONCLUSION: The aestivation of CSFB is supported by woodland edges, but not by flower strips. This implies that the presence of flower strips near oilseed rape fields does not exacerbate the problems due to this pest. However, the crops in the vicinity of woodlands could be colonized earlier by this pest than more distant fields. © 2023 Society of Chemical Industry.

Nitrous oxide fluxes and soil nitrogen contents over eight years in four cropping systems designed to meet both environmental and production goals: A French field nitrogen data set.

With the development of agroecosystem approaches, new cropping systems have to be designed to deliver multiple ecosystem services. In this context, we assessed four innovative cropping systems, designed to reach multiple environmental and production goals, in a long-term field experiment (2009-2020) at Grignon (France, N 48.84°, E 1.95°). A wide range of measurements were made, for nutrient cycles and organic matter in particular, for an analysis of interactions occurring during the emissions of greenhouse gases. We focus here on nitrogen (N) data collected over eight years (2009-2016). The data include: nitrous oxide fluxes (N2O), soil N contents (NO3 - and NH4 +), aboveground plant N content and biomass at maturity, yield, agricultural practices including N spreading, and climate. The four systems differ in terms of tillage practices, N inputs, and species, which is likely to affect soil N. Field data were collected and N2O fluxes were calculated. These original new cropping systems are innovating, resulting in new combinations of agricultural practices. The data obtained could be used to improve models for parameterization and validation, and to increase the predictive accuracy of models of N losses in original conditions.

Estimating the delay between host infection and disease (incubation period) and assessing its significance to the epidemiology of plant diseases.

Knowledge of the incubation period of infectious diseases (time between host infection and expression of disease symptoms) is crucial to our epidemiological understanding and the design of appropriate prevention and control policies. Plant diseases cause substantial damage to agricultural and arboricultural systems, but there is still very little information about how the incubation period varies within host populations. In this paper, we focus on the incubation period of soilborne plant pathogens, which are difficult to detect as they spread and infect the hosts underground and above-ground symptoms occur considerably later. We conducted experiments on Rhizoctonia solani in sugar beet, as an example patho-system, and used modelling approaches to estimate the incubation period distribution and demonstrate the impact of differing estimations on our epidemiological understanding of plant diseases. We present measurements of the incubation period obtained in field conditions, fit alternative probability models to the data, and show that the incubation period distribution changes with host age. By simulating spatially-explicit epidemiological models with different incubation-period distributions, we study the conditions for a significant time lag between epidemics of cryptic infection and the associated epidemics of symptomatic disease. We examine the sensitivity of this lag to differing distributional assumptions about the incubation period (i.e. exponential versus Gamma). We demonstrate that accurate information about the incubation period distribution of a pathosystem can be critical in assessing the true scale of pathogen invasion behind early disease symptoms in the field; likewise, it can be central to model-based prediction of epidemic risk and evaluation of disease management strategies. Our results highlight that reliance on observation of disease symptoms can cause significant delay in detection of soil-borne pathogen epidemics and mislead practitioners and epidemiologists about the timing, extent, and viability of disease control measures for limiting economic loss.

Host growth can cause invasive spread of crops by soilborne pathogens.

Invasive soilborne plant pathogens cause substantial damage to crops and natural populations, but our understanding of how to prevent their epidemics or reduce their damage is limited. A key and experimentally-tested concept in the epidemiology of soilborne plant diseases is that of a threshold spacing between hosts below which epidemics (invasive spread) can occur. We extend this paradigm by examining how plant-root growth may alter the conditions for occurrence of soilborne pathogen epidemics in plant populations. We hypothesise that host-root growth can 1) increase the probability of pathogen transmission between neighbouring plants and, consequently, 2) decrease the threshold spacing for epidemics to occur. We predict that, in systems initially below their threshold conditions, root growth can trigger soilborne pathogen epidemics through a switch from non-invasive to invasive behaviour, while in systems above threshold conditions root growth can enhance epidemic development. As an example pathosystem, we studied the fungus Rhizoctonia solani on sugar beet in field experiments. To address hypothesis 1, we recorded infections within inoculum-donor and host-recipient pairs of plants with differing spacing. We translated these observations into the individual-level concept of pathozone, a host-centred form of dispersal kernel. To test hypothesis 2 and our prediction, we used the pathozone to parameterise a stochastic model of pathogen spread in a host population, contrasting scenarios of spread with and without host growth. Our results support our hypotheses and prediction. We suggest that practitioners of agriculture and arboriculture account for root system expansion in order to reduce the risk of soilborne-disease epidemics. We discuss changes in crop design, including increasing plant spacing and using crop mixtures, for boosting crop resilience to invasion and damage by soilborne pathogens. We speculate that the disease-induced root growth observed in some pathosystems could be a pathogen strategy to increase its population through host manipulation.

Simulation of consumer exposure to deoxynivalenol according to wheat crop management and grain segregation: case studies and methodological considerations.

We combined agronomic data and a model simulating exposure based on consumption data to assess the impact of crop management and grain segregation procedures on consumer exposure to deoxynivalenol. We used three scenarios of soil tillage at a regional scale and three scenarios of grain segregation for a supply area. The soil tillage scenarios were applied to a range of mean crop contamination levels, with various coefficients representing the degree of tillage. The grain segregation scenarios were applied to two real datasets of DON content distributions. We found that the increase in consumer exposure in response to increases in "risky" crop management practices such as direct-drilling depends largely on mean contamination and on the value of the tillage coefficient. The results for grain segregation procedures showed that exposure was most strongly affected by contamination distributions as the segregation procedure minimising risk differed for the two datasets.

Effects of grain sampling procedures on fusarium mycotoxin assays in wheat grains.

Fusarium mycotoxins are increasingly studied agronomically, chemically, and pathologically in the context of food safety, as a means of preventing new major health crises. Reliable mycotoxin techniques and sampling procedures are required for assessment of the effects of different sources of variation on grain mycotoxin content in agronomic experiments. Analyses were performed with the aim of formulating guidelines for grain sampling to increase the reliability of grain mycotoxin measurement in agronomic experiments. Two toxins in wheat samples, deoxynivalenol and nivalenol, were targeted. With a nested linear mixed model, it was estimated that the uncertainty of nivalenol determination was low (+/-15 microg/kg), whereas that for deoxynivalenol determination was higher (+/-38 microg/kg). It was also found that grinding of the grain decreased the variability of the results. Moreover, despite the heterogeneity in grain mycotoxin content across a given field, it was shown that heads can be harvested manually for agronomic experiments provided that sampling is representative (evenly distributed over the entire plot area). Finally, delaying the assay until after harvest was found to affect the results obtained and should therefore be avoided.

Agronomic approach: cropping systems and plant diseases.

This paper deals with the effects of agronomic practices on parasite life cycles, and the design of integrated crop protection strategies. Cropping systems have a large effect on the size of the primary inoculum and its localisation, on the development and spread of epidemics, and on the coordination of the life cycle of cultivated plants and that of their parasites. They can disrupt ecological equilibria, either favouring or disfavouring the pathogens. By combining information concerning the effects of agricultural techniques on diseases and the physiological effects of diseases on growth and crop production, it is now possible to develop new crop management systems, in which the use of non-chemical methods for preventing diseases is a priority. However, the current knowledge need to be completed by studies on other scales, particularly of the effect of cropping systems on the genetics of disease populations integrating more completely the 'long-term' dimension of sustainable agriculture.