Linking phytoplankton pigment composition and optical properties: A framework for developing remote-sensing metrics for monitoring cyanobacteria

International audienceThis study has been performed in the framework of a research program aiming to develop a low-cost aerial sensor for the monitoring of cyanobacteria in freshwater ecosystems that could be used for early detection. Several empirical and mechanistic remote-sensing tools have been already developed and tested at large scales and have proven useful in monitoring cyanobacterial blooms. However, the effectiveness of these tools for early detection is hard to assess because such work requires the detection of low concentrations of characteristic pigments amid complex ecosystems exhibiting several confounding factors (turbidity, blooms of other species, etc.). We developed a framework for performing high-throughput measurements of the absorbance and reflectance of small volumes (~= 20 mL) of controlled mixtures of phytoplankton species and studied the potential of this framework to validate remote-sensing proxies of cyanobacteria concentration. The absorption and reflectance spectra of single and multiple cultures carried a specific signal that allowed for the quantitative analysis of culture mixes. This specific signal was shown to be related to known pigment absorbance spectra. The concentrations of chlorophyll-a and -b, phycocyanin and phycoerythrin could be obtained from direct absorbance measurements and were correlated with the concentration obtained after pigment extraction (R2 ≥ 0.96 for all pigments). A systematic test of every possible two-band and three-band normalized difference between optical indices was then performed, and the coincidental correlation with chlorophyll-b (absent in cyanobacteria) was used as an indicator of non-specificity. Two-band indices were shown to suffer from non-specificity issues and could not yield strong and specific relationships with phycocyanin or phycoerythrin (maximum R2  0.8)

Designing cotton ideotypes for the future: Reducing risk of crop failure for low input rainfed conditions in Northern Cameroon

International audienceClimate change is threatening the ability to grow cotton (Gossypium hirsutum L.) under low input rainfed production areas in Sub-Saharan Africa. In Northern Cameroon, yield has been declining due to unsuitable cropping practices such as sub-optimal planting dates, along with an absence in genetic gain. The aim of this study was to use a cropping system model (DSSAT CSM-CROPGRO-Cotton) to identify the best cultivars (ideotypes) for Northern Cameroon that are adapted to low input rainfed productions systems for 2050 under RCP4.5 and RCP8.5. Calibration and evaluation of the CSM-CROPGRO-Cotton were performed with field observations for two cultivars (Allen Commun and L484). For RCP4.5 and RCP8.5, 50 replications for 2050 were generated based on an ensemble of 17 Global Circulating Models. In total, 3125 virtual cultivars representing existing genetic variability for phenology, morphology and photosynthesis were simulated. Thereafter, they were evaluated for performance under the projected future climate based on potential yield and the resilience of yield to suboptimal planting date. The widely cultivated cultivar L484 will be unsuitable under projected future climate, due to boll opening during the middle of the rainy season (median: 10/09 under RCP4.5 and 12/09 under RCP8.5). None of the ideotypes tested could optimize both yield and resilience (Pearson correlation < -0.82). However, compared to the current cultivar L484, two virtual ideotypes were identified: (a) "Ideo_sub" had a wide planting window, especially in the 10 worst replications of 2050, up to +5 days in RCP8.5; (b) "Ideo_Pot" had a high potential yield trait with low resilience to sub-optimal planting date, in the 10 worst replications of 2050, +530 kg ha(-1) in RCP4.5 and + 591 kg ha(-1) in RCP8.5. Both ideotypes had an earlier anthesis date, a longer reproductive duration, and increase in the maximum photosynthetic rate. Therefore, breeding programs should consider these traits suggested by this system analysis using a crop simulation model for the identification of suitable cultivars under the projected future climate

Linking phytoplankton pigment composition and optical properties: A framework for developing remote-sensing metrics for monitoring cyanobacteria

International audienceThis study has been performed in the framework of a research program aiming to develop a low-cost aerial sensor for the monitoring of cyanobacteria in freshwater ecosystems that could be used for early detection. Several empirical and mechanistic remote-sensing tools have been already developed and tested at large scales and have proven useful in monitoring cyanobacterial blooms. However, the effectiveness of these tools for early detection is hard to assess because such work requires the detection of low concentrations of characteristic pigments amid complex ecosystems exhibiting several confounding factors (turbidity, blooms of other species, etc.). We developed a framework for performing high-throughput measurements of the absorbance and reflectance of small volumes (~= 20 mL) of controlled mixtures of phytoplankton species and studied the potential of this framework to validate remote-sensing proxies of cyanobacteria concentration. The absorption and reflectance spectra of single and multiple cultures carried a specific signal that allowed for the quantitative analysis of culture mixes. This specific signal was shown to be related to known pigment absorbance spectra. The concentrations of chlorophyll-a and -b, phycocyanin and phycoerythrin could be obtained from direct absorbance measurements and were correlated with the concentration obtained after pigment extraction (R2 ≥ 0.96 for all pigments). A systematic test of every possible two-band and three-band normalized difference between optical indices was then performed, and the coincidental correlation with chlorophyll-b (absent in cyanobacteria) was used as an indicator of non-specificity. Two-band indices were shown to suffer from non-specificity issues and could not yield strong and specific relationships with phycocyanin or phycoerythrin (maximum R2  0.8)

Combining UAV and Sentinel-2 Imagery for Estimating Millet FCover in a Heterogeneous Agricultural Landscape of Senegal

International audienceIn recent decades, remote sensing has been shown to be useful for crop cover monitoring over smallholder agricultural landscapes, such as agroforestry parklands. However, the fraction of green vegetation cover (FCover) has received little attention. Indeed, the collection of FCover ground data representative of the within-field heterogeneity is time-consuming. Thus, this article aims to bridge this gap by proposing an original methodological framework combining FCover data derived from unmanned aerial vehicle (UAV) and Sentinel-2 (S2) images for estimating millet FCover at the landscape scale in an agroforestry parkland of the groundnut basin of Senegal during the 2021 and 2022 cropping seasons. UAV-based FCover was computed over a 3 m x 3 m grid using a thresholding approach for six dates over the cropping seasons and then used as ground observation for the upscaling of millet FCover at the landscape scale with S2 data. Various spectral vegetation indices and textural features were derived from S2, and several modeling approaches based on machine learning algorithms were benchmarked. Our results showed that the modeling approach using the full-time series in combination with a random forest algorithm was able to explain 73% (root mean square error = 12.13%) of the UAV-FCover variability after validation in 2021 and 2022. In addition, UAV images are suitable for consistent monitoring of millet FCover over heterogeneous agricultural landscapes by training S2 satellite images. To further check its robustness, this approach should be tested for different crops and practices across a variety of agricultural landscapes in sub-Saharan Africa

Unmanned aerial vehicle for the assessment of woody and herbaceous phytomass in Sahelian savanna

La phytomasse des plantes herbacées et ligneuses est la principale source d’alimentation du bétail pastoral dans les savanes sahéliennes. L’évaluation de la matière première disponible joue un rôle clé dans les politiques nationales d’élevage et nécessite généralement de nombreux relevés de mesures de terrain des plantes herbacées et ligneuses. Dans cette étude, nous avons testé la possibilité d’utiliser un drone à bandes spectrales rouge-vert-bleu (RGB) pour évaluer la phytomasse des espèces ligneuses et herbacées. Avec un drone Dji Spark nous avons ainsi cartographié 38 parcelles d’un hectare dans le nord du Sénégal. La phytomasse herbacée a été mesurée au sol. Pour les communautés ligneuses, nous avons évalué la phytomasse foliaire en utilisant des paramètres dendrométriques associés à des équations allométriques. Nous avons effectué des régressions des moindres carrés partiels entre les indices (en trois dimensions et couleurs) obtenus par drone et la phytomasse. Les résultats ont montré un Q² (résultats de validation croisée pour chaque variable de réponse) de 0,57 pour la phytomasse des ligneux, 0,68 pour la masse sèche des herbacées, et 0,76 pour leur masse fraîche. Cette étude a confirmé la pertinence de l’utilisation d’un drone RGB à faible coût pour l’évaluation de la phytomasse des savanes

How far does the tree affect the crop in agroforestry? New spatial analysis methods in a Faidherbia parkland

The trees in agroforestry plots create spatial heterogeneity of high interest for adaptation, mitigation, and the provision of ecosystem services. But to what distance, exactly, from the tree? We tested a novel approach, based upon geostatistics and Unmanned Aerial Vehicle (UAV) sensing, to infer the distance at which a single agroforestry tree affects the surrounding under-crop, to map yield, litter (i.e. stover) and compute crop-partial Land Equivalent Ratio (LERcp) at the whole-plot level.In an agro-silvo-pastoral parkland of semi-arid western Africa dominated by the multi-purpose tree Faidherbia albida, we harvested the pearl-millet under-crop at the whole-plot scale (ca. 1 ha) and also in subplot transects, at three distances from the trunks. We observed that the yield was three times higher below the tree crown (135.6 g m(-2)) than at a distance of five tree-crown radii from the trunk (47.7 g m(-2)). Through geostatistical analysis of multi-spectral, centimetric-resolution images obtained from an UAV overflight of the entire plot, we determined that the 'Range' parameter of the semi-variogram (assumed to be the distance of influence of the trees on the Normalized difference vegetation index (NDVI)) was 17 m. We correlated the yield (r(2) = 0.41; RRMSE = 48 %) and litter production (r(2) = 0.46; RRMSE = 35 %) in subplots with NDVI, and generated yield and litter maps at the whole-plot scale. The measured whole-plot yield (0.73 t ha(-1)) differed from the one estimated via the UAV mapping by only 20 %, thereby validating the overall approach. The litter was estimated similarly at 1.05 tC ha(-1) yr(-1) and mapped. Using a geostatistical proxy for the sole crop, LERcp was estimated 1.16, despite the low tree density.This new method to handle heterogeneity in agroforestry systems is a first application. We also propose strategies for extension to the landscape level

Arbuscular mycorrhizal fungus Rhizophagus irregularis expresses an outwardly Shaker-like channel involved in potassium nutrition of rice ( Oryza sativa L.)

Abstract Potassium (K + ) plays crucial roles in many physiological, molecular and cellular processes in plants. Direct uptake of this nutrient by root cells has been extensively investigated, however, indirect uptake of K + mediated by the interactions of the roots with fungi in the frame of a mutualistic symbiosis, also called mycorrhizal nutrient uptake pathway, is much less known. We identified an ion channel in the arbuscular mycorrhizal (AM) fungus Rhizophagus irregularis . This channel exhibits the canonical features of Shaker-like channel shared in other living kingdoms and is named RiSKC3. Transcriptionally expressed in hyphae and in arbuscules of colonized rice roots, RiSKC3 has been shown to be located in the plasma membrane. Voltage-clamp functional characterization in Xenopus oocytes revealed that RiSKC3 is endowed with outwardly-rectifying voltage-gated activity with a high selectivity for K + over sodium ions. RiSKC3 may have a role in the AM K + pathway for rice nutrition in normal and salt stress conditions. The current working model proposes that K + ions taken up by peripheral hyphae of R. irregularis are secreted towards the host root into periarbuscular space by RiSKC3. Significance Statement Mutualistic symbiosis with arbuscular mycorrhizal (AM) fungi are beneficial for about 80% of land plants thanks to an exchange of nutrients. The AM pathway responsible for potassium (K + ) nutrition of the plant is not known. Here we uncovered a key step of this phenomenon, by functionally characterizing the first transport system in the AM fungus Rhizophagus irregularis , and we univocally demonstrated that RiSKC3 is an K + outwardly-rectifying voltage-gated Shaker-like channel

Innovative tools and methods for toxicity testing within PARC work package 5 on hazard assessment

New approach methodologies (NAMs) have the potential to become a major component of regulatory risk assessment, however, their actual implementation is challenging. The European Partnership for the Assessment of Risks from Chemicals (PARC) was designed to address many of the challenges that exist for the development and implementation of NAMs in modern chemical risk assessment. PARC's proximity to national and European regulatory agencies is envisioned to ensure that all the research and innovation projects that are initiated within PARC agree with actual regulatory needs. One of the main aims of PARC is to develop innovative methodologies that will directly aid chemical hazard identification, risk assessment, and regulation/policy. This will facilitate the development of NAMs for use in risk assessment, as well as the transition from an endpoint-based animal testing strategy to a more mechanistic-based NAMs testing strategy, as foreseen by the Tox21 and the EU Chemical's Strategy for Sustainability. This work falls under work package 5 (WP5) of the PARC initiative. There are three different tasks within WP5, and this paper is a general overview of the five main projects in the Task 5.2 'Innovative Tools and methods for Toxicity Testing,' with a focus on Human Health. This task will bridge essential regulatory data gaps pertaining to the assessment of toxicological prioritized endpoints such as non-genotoxic carcinogenicity, immunotoxicity, endocrine disruption (mainly thyroid), metabolic disruption, and (developmental and adult) neurotoxicity, thereby leveraging OECD's and PARC's AOP frameworks. This is intended to provide regulatory risk assessors and industry stakeholders with relevant, affordable and reliable assessment tools that will ultimately contribute to the application of next-generation risk assessment (NGRA) in Europe and worldwide