Multivariate global sensitivity analysis for dynamic crop models

Dynamic crop models are frequently used in ecology, agronomy and environmental sciences for simulating crop and environmental variables at a discrete time step. They often include a large number of parameters whose values are uncertain, and it is often impossible to estimate all these parameters accurately. A common practice consists in selecting a subset of parameters by global sensitivity analysis, estimating the selected parameters from data, and setting the others to some nominal values. For a discrete-time model, global sensitivity analyses can be applied sequentially at each simulation date. In the case of dynamic crop models, simulations are usually computed at a daily time step and the sequential implementation of global sensitivity analysis at each simulation date can result in several hundreds of sensitivity indices, with one index per parameter per simulation date. It is not easy to identify the most important parameters based on such a large number of values. In this paper, an alternative method called multivariate global sensitivity analysis was investigated. More precisely, the purposes of this paper are (i) to compare the sensitivity indices and associated parameter rankings computed by the sequential and the multivariate global sensitivity analyses, (ii) to assess the value of multivariate sensitivity analysis for selecting the model parameters to estimate from data. Sequential and multivariate sensitivity analyses were compared by using two dynamic models: a model simulating wheat biomass named WWDM and a model simulating N₂O gaseous emission in crop fields named CERES-EGC. N₂O measurements collected in several experimental plots were used to evaluate how parameter selection based on multivariate sensitivity analysis can improve the CERES-EGC predictions.The results showed that sequential and multivariate sensitivity analyses provide modellers with different types of information for models which exhibit a high variability of sensitivity index values over time. Conversely, when the parameter influence is quite constant over time, the two methods give more similar results. The results also showed that the estimation of the parameters with the highest sensitivity indices led to a strong reduction of the prediction errors of the model CERES-EGC.     

A general method to filter out defective spatial observations from yield mapping datasets

Yield maps are recognized as a valuable tool with regard to managing upcoming crop production but can contain a large amount of defective data that might result in misleading decisions. These anomalies must be removed before further processing to ensure the quality of future decisions. This paper proposes a new holistic methodology to filter out defective observations likely to be present in yield datasets. The notion of spatial neighbourhood has been refined to embrace the specific characteristics of such on-the-go vehicle based datasets. Observations are compared with their newly-defined spatial neighbourhood and the most abnormal ones are classified as defective observations based on a density-based clustering algorithm. The approach was conceived to be as non-parametric and automated as far as possible to pre-process a growing number of datasets without supervision. The proposed approach showed promising results on real yield datasets with the detection of well-known sources of errors such as filling and emptying times, speed changes and non-fully used cutting bar.     

Fleets of robots for environmentally-safe pest control in agriculture

Feeding the growing global population requires an annual increase in food production. This requirement suggests an increase in the use of pesticides, which represents an unsustainable chemical load for the environment. To reduce pesticide input and preserve the environment while maintaining the necessary level of food production, the efficiency of relevant processes must be drastically improved. Within this context, this research strived to design, develop, test and assess a new generation of automatic and robotic systems for effective weed and pest control aimed at diminishing the use of agricultural chemical inputs, increasing crop quality and improving the health and safety of production operators. To achieve this overall objective, a fleet of heterogeneous ground and aerial robots was developed and equipped with innovative sensors, enhanced end-effectors and improved decision control algorithms to cover a large variety of agricultural situations. This article describes the scientific and technical objectives, challenges and outcomes achieved in three common crops.     

Influence of a long-term storage in anaerobic conditions on Norway spruce (Picea abies,L. Karst.) physical and mechanical wood properties

Timber storage is a key aspect of storm damage management. After huge storms, sprinkling storage is usually the most used conservation process but anaerobic storage in sealed silos appears as good alternative to preserve wood quality over long periods. This paper investigates the impact of long-term (57 months) storage of Norway spruce logs in anaerobic atmosphere on wood properties. Tests were performed on clear wood specimens and on lumbers to determine the modulus of elasticity (E), the static bending strength (σ_f) and the dynamic bending strength (K). Storage effects on impregnability and colour variation were also studied. Results show no effect of storage on E, σ_f and K. The naturally poor impregnability of Norway spruce is not improved by the anaerobic conditions, compared to traditional wet storage. Triangle tests reveal no discernible colour variation between logs that underwent anaerobic storage and the control sample. As a conclusion, despite a mould (Gliocladium solani) frequently observed on logs surface after the storage, the process offers ideal conservation conditions. While overall cost remains the main drawback for using anaerobic storage at large scale, the process can be recommended for high value logs, especially since it has few environmental impacts.     

Isolation and concentration of organophosphorus pesticides from drinking water at the ng/L level, using macroreticular resin.

A screening method has been developed for determining organophosphorus pesticides at ng/L levels in drinking water. Sixteen organophosphorus pesticides, diazinon, diazinon-oxon, dimethoate, ronnel, beta-phosphamidon, methyl parathion, ethyl parathion, malathion, chlorpyrifos, fenitrothion, ruelene, methidathion, ethion, EPN, phosalone, and phosmet, were extracted by Amberlite XAD-2 resin from 100 and 200 L drinking water previously spiked with these pesticides. The pesticides were eluted from the XAD-2 resin with acetone-hexane (15+85). The concentrated extract was analyzed by gas chromatography using a nitrogen-phosphorus selective detector and by gas chromatography-mass spectrometry using selected ion monitoring. Recoveries at the 10 and 100 ng/L spiking levels were greater than 90%, except recoveries for dimethoate and phosphamidon were 37 and 42%, respectively. The analysis of 300 L Ottawa tap water showed no detectable amounts (less than 1 ng/L) of any of the 16 organophosphorus pesticides.     

Methodology for land use change scenario assessment for runoff impacts: A case study in a north-western European Loess belt region (Pays de Caux,France)

Changes of agricultural land use often induce changes in hydrological behavior of watersheds. Hence, effective information regarding runoff responses to future land use scenarios provides useful support for decision-making in land use planning and management. The objective of this study is to develop a methodology to assess land use change scenario impacts on runoff at the watershed scale. This objective implies translating qualitative information from scenarios into quantitative input parameters for biophysical models. To do so, qualitative information from scenarios should be quantified and spatialized.     

Impact of <Emphasis Type="Italic">Erysiphe alphitoides</Emphasis> on transpiration and photosynthesis in <Emphasis Type="Italic">Quercus robur</Emphasis> leaves

Oak powdery mildew, (Erysiphe alphitoides) causes one of the most common diseases of oaks. We assessed the impact of this pathogen on photosynthesis and water relations of infected leaves using greenhouse-grown oak seedlings. Transpiration of seedlings infected by oak powdery mildew was also investigated. Altogether, E. alphitoides had a low impact on host gas exchange whether at the leaf or whole plant scale. Maximal stomatal conductance of infected leaves was reduced by 20–30% compared to healthy controls. Severely infected seedlings did not experience any detectable change of whole plant transpiration. The reduction in net CO₂ assimilation, A_n, was less than proportional to the fraction of leaf area infected. Powdery mildew reduced both the maximal light-driven electron flux (J_max) and the apparent maximal carboxylation velocity (Vc_max) although Vc_max was slightly more impacted than J_max. No compensation for the infection occurred in healthy leaves of partly infected seedlings as the reduced photosynthesis in the infected leaves was not paralleled by increased A_n levels in the healthy leaves of the seedlings. However, E. alphitoides had a strong impact on the leaf life-span of infected leaves. It is concluded that the moderate effect of E. alphitoides on oak might be related to the small impact on net CO₂ assimilation rates and on tree transpiration; nevertheless, the severe reduction in leaf life-span of heavily infected leaves may lead to decreased carbon uptake over the growth season.     

The Marine-Derived Macrolactone Mandelalide A Is an Indirect Activator of AMPK

The mandelalides are complex macrolactone natural products with distinct macrocycle motifs and a bioactivity profile that is heavily influenced by compound glycosylation. Mandelalides A and B are direct inhibitors of mitochondrial ATP synthase (complex V) and therefore more toxic to mammalian cells with an oxidative metabolic phenotype. To provide further insight into the pharmacology of the mandelalides, we studied the AMP-activated protein kinase (AMPK) energy stress pathway and report that mandelalide A is an indirect activator of AMPK. Wild-type mouse embryonic fibroblasts (MEFs) and representative human non-small cell lung cancer (NSCLC) cells showed statistically significant increases in phospho-AMPK (Thr172) and phospho-ACC (Ser79) in response to mandelalide A. Mandelalide L, which also harbors an A-type macrocycle, induced similar increases in phospho-AMPK (Thr172) and phospho-ACC (Ser79) in U87-MG glioblastoma cells. In contrast, MEFs co-treated with an AMPK inhibitor (dorsomorphin), AMPKα-null MEFs, or NSCLC cells lacking liver kinase B1 (LKB1) lacked this activity. Mandelalide A was significantly more cytotoxic to AMPKα-null MEFs than wild-type cells, suggesting that AMPK activation serves as a protective response to mandelalide-induced depletion of cellular ATP. However, LKB1 status alone was not predictive of the antiproliferative effects of mandelalide A against NSCLC cells. When EGFR status was considered, erlotinib and mandelalide A showed strong cytotoxic synergy in combination against erlotinib-resistant 11-18 NSCLC cells but not against erlotinib-sensitive PC-9 cells. Finally, prolonged exposures rendered mandelalide A, a potent and efficacious cytotoxin, against a panel of human glioblastoma cell types regardless of the underlying metabolic phenotype of the cell. These results add biological relevance to the mandelalide series and provide the basis for their further pre-clinical evaluation as ATP synthase inhibitors and secondary activators of AMPK.     

Involvement of a sodium channel mutation in pyrethroid resistance in Cydia pomonella L, and development of a diagnostic test

Populations of the codling moth, Cydia pomonella L (Lepidoptera, Tortricidae) have developed resistance to several classes of insecticide such as benzoylureas, juvenile hormone analogues, ecdysone agonists and pyrethroids, but the corresponding resistance mechanisms have not been extensively studied. Knockdown resistance (kdr) to pyrethroid insecticides has been associated with point mutations in the para sodium channel gene in a great variety of insect pest species. We have studied two susceptible strains (S and Sv) and two resistant strains (Rt and Rv) of C pomonella that exhibited 4- and 80-fold resistance ratios to deltamethrin, respectively. The region of the voltage-dependent sodium channel gene which includes the position where kdr and super-kdr mutations have been found in Musca domestica L was amplified. The kdr mutation, a leucine-to-phenylalanine replacement at position 1014, was found only in the Rv strain. In contrast, the super-kdr mutation, a methionine-to-threonine replacement at position 918, was not detected in any C pomonella strain. These data allowed us to develop a PCR-based diagnostic test (PASA) to monitor the frequency of the kdr mutation in natural populations of C pomonella in order to define appropriate insecticide treatments in orchards.