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Managing Pesticide Resistance: Input‐Oriented Versus Result‐Oriented Tax Systems
No full textInternational audiencePesticide resistance is a phenomenon that is becoming increasingly worrying. Heavy reliance on pesticides in the agricultural sector is at the core of this problem. In this paper, we analyse how farmers' pest control strategies can reduce pesticide resistance. We show that Integrated Pest Management is effective in limiting the growth of pesticide resistance. However, because one farmer's choices affect those of their neighbours, externalities remain and public policies are needed. We analyse two tax systems where one is polluting input‐oriented and the other is result‐oriented. We derive conditions under which both tax systems lead to socially optimal strategies. We show that a result‐oriented scheme needs less information on farmers' time preferences
Improving on early exaggeration in t -SNE: Early hierarchization better preserves global structure
No full textInternational audienceIn dimensionality reduction, t-SNE is a local method of neighbor embedding that requires to be carefully initialized in order to preserve the global structure of data to a good extent. In standard t-SNE, the low-dimensional embedding is initialized either randomly or with PCA. Next, gradient descent runs for two successive phases to refine the embedding coordinates iteratively. In the first phase, named early exaggeration, the attractive forces between points are artificially strengthened to prevent the repulsive forces to scatter fragments of the still poorly organized embedding, before the second phase takes over with the genuine gradient, until final convergence. A novel initialization of t-SNE is proposed in this extended work. It proceeds by hierarchizing the data points into a space-partitioning binary tree that yields faithful subsamples of data with 4,8, 16,...2[log2 N], N points; t-SNE runs on these growing subsamples, each obtained embedding initializing the next run. Between two runs, the prototypical point in each tree branch is split into its two children and the embedding is rescaled to account for the increased population. Extended experimental results with 5 repetitions show quantitatively the effectiveness of the method on a variety of artificial and real data sets, while running times get only multiplied by a small constant factor, leaving the computational complexity unchanged. This confirms that early hierarchization can advantageously replace initialization and early exaggeration, making t-SNE a more homogeneous method with fewer meta-parameters. The proposed method is compatible with any method of neighbor embedding (t-SNE, UMAP, etc.) with quadratic, log-linear, or even linear iterations, provided early exaggeration can be disabled and initial coordinates of the embedded data points can be specified
New Insights Into Modeling Quality Change Kinetics, Oil Distribution, and Physicochemical Properties of Banana Chips Using Combined Pre-Frying Treatments
No full textInternational audienceThis study developed low-fat banana chips using various pre-frying treatments, including moisture reduction (MR), hydrocolloid coatings (carboxymethyl cellulose (CMC) and guar gum (GG)), and their combinations with freezing (MRF, CMCF, GGF). Pretreated samples were fried at 180 °C for 180 s (MR and MRF) or 420 s (CMC, CMCF, GG, and GGF) and compared with commercial deep-fat and vacuum-fried chips. Moisture sorption characteristics, dynamic mechanical thermal properties, oil distribution, and physicochemical attributes were evaluated, and quality changes during frying were modeled. Principal component analysis (PCA) showed that most pre-frying treatments were closely correlated with commercial deep-fat fried products, while MR and MRF were positioned between commercial deep-fat and vacuum-fried chips, indicating shared characteristics with both groups. MR and MRF had the lowest oil content among all pre-frying treatments. Penetrated oil accounted for over 97% of the total oil. All treatments produced chips with glass transition temperatures above ambient temperature (30 °C) and monolayer moisture content (2.75 to 6.93% d.b.) exceeding actual moisture content levels (0.17–2.23% d.b.), suggesting a storage stability under ambient conditions. The modified page model was the best described moisture loss during frying, while zero-order reaction kinetics effectively explained quality changes. In conclusion, MR and MRF were effective in producing low-fat banana chips with quality comparable to commercial vacuum-fried products. This work advances current knowledge by demonstrating that pre-frying treatments can serve as cost-effective alternatives to vacuum frying in terms of capital investment while maintaining comparable quality attributes. This finding makes the approach suitable for small- and medium-scale snack manufacturers seeking to meet consumer demand for healthier snack options
Is compulsory inter-municipal cooperation an efficiency booster?
No full textInternational audienceThis paper evaluates the impact of inter-municipal cooperation on municipal efficiency in France. We exploit the “Réforme des Collectivités Territoriales” (RCT) law, approved in 2010, which forced municipalities to join an inter-municipal group (EIMC) by 2014. Focusing on Île-de-France from 2002 to 2019, we first compute municipal efficiency scores, accounting for intra- and inter-EIMC spillover effects. We then causally assess the impact of EIMC integration on municipal efficiency. We find that the RCT law increased municipal efficiency by 1.1% to 1.9%, with a stronger effect for early adopters and with increasing length of exposure
Integration DeepLabv3+ applied to RGB images and vegetation indices for nitrogen status in cereal–legume intercropping system
No full textInternational audienceThis study presents a low-cost, non-invasive approach to monitor the nitrogen status of Triticale in a Triticale–Faba bean intercropping system, an agroecological strategy to avoid chemical nitrogen inputs, using consumer-grade smartphone RGB images and deep learning. Three smartphones (Samsung Galaxy A12, Xiaomi Redmi Note 4, and Redmi Note 11) were used to capture canopy images. A DeepLabV3+ model with a ResNet-50 backbone was trained to semantically segment Triticale pixels from mixed canopies. Training the model on patch-based image subsets, rather than full images, substantially enhanced segmentation accuracy (mIoU = 90.64%). The normalized Dark Green Color Index (nDGCI) derived from segmented images at the canopy scale, was evaluated as a proxy for nitrogen status against normalized SPAD (nSPAD) measurements, a tedious leaf scale method. Strong linear relationships were observed between nDGCI and nSPAD (pooled correlation across optical devices of R² ≈ 0.60 and optical device-specific ranging from R² = 0.69 to 0.87). Statistical analyses highlighted significant effects of cropping modality, phenological stage, and device on both indices, but the method reliably distinguished between nitrogen treatments. Device-specific calibration effectively corrected offsets, validating the feasibility of smartphone-based AI for detailed monitoring in intercropped systems. This approach offers a practical cost-effective alternative to conventional tools enabling precision agriculture in agroecological contexts
Critical material and regional inequality: Material demand under diverging decarbonization pathways in China’s power sector
No full textInternational audienceChina's power sector decarbonization is crucial for global climate goals. However, regional disparities in decarbonization pathways and material demands arise due to differences in resource endowment, economic development, and policy support. This study develops an integrated assessment model to evaluate critical material demand for decarbonizing China's power sector under four scenarios: Business-as-Usual (BAU), Renewable Energy (RE), Carbon Capture and Storage (CCS), and Advanced Nuclear (AN). The results show significant provincial variations, with eastern provinces favoring wind and solar, while western and coal-dependent regions rely on hydropower or CCS. Nationally, material demand peaks in the CCS scenario by 2060, especially for structural materials like copper (2250 Mt) and nickel (445 Mt). Functional materials such as silicon and indium see significant demand increases under PV-driven transitions, with silicon reaching 9300 kt and indium 14.2 Mt by 2060 in the RE scenario. These findings highlight the need for region-specific policies, long-term material supply planning, and addressing material demand imbalances for a sustainable energy transition
Se passer ou pas des néonicotinoïdes ?
No full textInternational audienceCet article vise à s’interroger sur la manière dont, aujourd’hui en France, les discours et les actions se structurent dans l’espace public national autour de l’usage des néonicotinoïdes par les producteurs de betterave. S’appuyant sur les régimes d’actions « tactique-stratégique » et « de la justification », il montre comment des coups et contrecoups se succèdent dans le temps, depuis plus d’une vingtaine d’années, entre les défenseurs et les contempteurs de cet usage, et comment les uns et les autres se réfèrent, pour ce faire, à des principes supérieurs communs différents. Les événements décrits tiennent plus de la guerre larvée, avec une succession d’opérations tactiques et de moments de paix armée, et rendent compte d’une certaine incapacité politique à établir des compromis à même de permettre la construction d’une autre réalité
Optimizing biodiversity, multifunctionality and yield when transitioning to organic farming
No full textInternational audienceAgricultural intensification increases crop production but often causes declines in soil biodiversity and functioning, thus threatening long-term environmental sustainability. To buffer these impacts, environmental policies aim to increase the amount of organic farming; however, this potentially compromises yield and nitrogen and phosphorus availability. Given such complexities, we evaluated the overall impacts of shifting agricultural management by comparing the effects of conventional versus organic farming on soil biodiversity (richness of 6 faunal and microbial groups), functioning (21 indicators) and crop yield on 179 global croplands across a wide range of ecological contexts, including contrasting levels of soil degradation. High crop yields did not necessarily trade off against soil biodiversity, ecosystem multifunctionality or nitrogen availability, with often positive correlations found between them. Yield, biodiversity and functioning variables showed a broad range of values within and between conventional and organic sites. Despite this large variation, we found that landscapes with 50% organic agriculture could optimize crop yields, biodiversity and multifunctionality. Our findings provide guidelines for sustainable agriculture, showing how prioritizing the transition to organic farming in moderately to highly degraded soils would maximize its benefits while minimizing yield loss
Weeds in a changing climate: Competitors or service plants?
No full textInternational audienceSocietal Impact Statement Reducing herbicide use and preparing agroecosystems for climate change are two top priorities on the global policy agenda. Here, we explore whether these two challenges can be tackled simultaneously. While weeds are generally considered a threat to crop production, we show that weeds can help overcome climate change challenges in agroecosystems. However, crop–weed interactions need to be carefully managed. Options for this were found to be greater in perennial than in annual systems. These findings provide a new perspective on weeds and call for more research on the appreciation of weeds as service plants, which ultimately may create new avenues for weed management and agricultural policy. Summary Sustainable agricultural production is at risk due to climate change, the increasing herbicide resistance of weeds and pressures to minimise herbicide use. Rather than solely considering weeds as part of the problem, we see this as an opportunity to investigate whether weeds can help overcome climate change challenges in agroecosystems. Using both ecological and agronomic perspectives, we assessed to what extent weeds can support the ecosystem functions water and climate regulation and whether their potential role as service plants would interfere with crop production. Based on ecological trait‐based analyses, we demonstrate that weeds are excellent candidates to support the delivery of water and climate regulation. Despite climate change‐induced shifts in weed communities, weeds continue to support these ecosystem functions. However, weed trait values that promote the ecosystem processes underlying water and climate regulation also tend to increase competition with crops. We show that confining weed–crop interactions is key to allow weeds to operate as service plants and that the spatial and temporal opportunities to manage these interactions vary among annual and perennial cropping systems. Overall, diversified management is recommended in both systems to avoid the selection of weed communities composed of just a few highly competitive weed species. We conclude that weeds could act as service plants in a changing climate rather than being considered a threat to agroecosystems. Weed management and research should thus prioritise the investigation and implementation of this new perspective
