Productivity and radiation use efficiency of lettuces grown in the partial shade of photovoltaic panels

Combining photovoltaic panels (PVPs) and crops on the same land unit were recently proposed as an alternative to the conversion of cropland into photovoltaic plants. This could alleviate the increasing competition for land between food and energy production. In such agrivoltaic systems, an upper layer of PVPs partially shades crops at ground level. The aim of this work was to (i) assess the effect on crop yield of two PVPs densities, resulting in two shade levels equal to 50% and 70% of the incoming radiation and (ii) identify morphological and physiological determinants of the plant response to shade. Experiments were conducted on four varieties of lettuces (two crisphead lettuces and two cutting lettuces), during two seasons. In all cases, the relative lettuce yield at harvest was equal or higher than the available relative radiation. Lettuce yield was maintained through an improved Radiation Interception Efficiency (RIE) in the shade, while Radiation Conversion Efficiency (RCE) did not change significantly. Enhanced RIE was explained by (i) an increase in the total leaf area per plant, despite a decrease in the number of leaves and (ii) a different distribution of leaf area among the pool of leaves, the maximal size of leaves increasing in the shade. Our result provides a framework for the selection of adapted varieties according to their morphological traits and physiological responses to PVP shade, in order to optimize agrivoltaic systems

A comparison of empirical and mechanistic models for wheat yield prediction at field level in Moroccan rainfed areas

peer reviewedIn the context of climate change, in-season and longer-term yield predictions are needed to anticipate local and regional food crises and propose adaptations to farmers’ practices. Mechanistic models and machine learning are two modelling options to consider in this perspective. In this study, regression (MR) and Random Forest (RF) models were calibrated for wheat yield prediction in Morocco, using data collected from 125 farmers’ wheat fields. Additionally , MR and RF models were calibrated both with or without remotely-sensed leaf area index (LAI), while considering all farmers’ fields, or specifically to agroecological zoning in Morocco. The same farmers’ fields were simulated using a mechanistic model (APSIM-wheat). We compared the predictive performances of the empirical models and APSIM-wheat. Results showed that both MR and RF showed rather good predictive quality (NRMSEs below 35%), but were always outperformed by APSIM model. Both RF and MR selected remotely-sensed LAI at heading, climate variables (maximal temperatures at emergence and tillering), and fertilization practices (amount of nitrogen applied at heading) as major yield predictors. Integration of remotely-sensed LAI in the calibration process reduced NRMSE of 4.5% and 1.8 % on average for MR and RF models respectively. Calibration of region specific models did not significantly improve the predictive. These findings lead to the conclusion that mechanistic models are better at capturing the impacts of in-season climate variability and would be preferred to support short term tactical adjustments to farmers’ practices, while machine learning models are easier to use in the perspective of mid-term regional prediction.SoilPhorLife-Projet

Relevance of soil fertility spatial databases for parameterizing APSIM-wheat crop model in Moroccan rainfed areas

peer reviewedCrop models have evolved over the past decade to incorporate more soil-related processes. While this may open avenues to support farmers regarding fertilization practices, it also widens the pitfalls related to model parametrization. Open-access georeferenced soil databases are often a solution for modelers to derive soil parameters. However, they can potentially add to model uncertainty depending on database resolution and the variability of the characteristics it contains. Fertimap is an online spatial database recently released in Morocco. In this study, we aim at assessing how Fertimap could support the use of crop model in the rainfed wheat production areas of Morocco. Data including local soil analysis, farmers’ practices, wheat biomass, and yield were collected on 126 farmers’ fields distributed across the rainfed wheat production area in Morocco from 2018 to 2020. Data were first used to parameterize, calibrate, and assess the model, using site-specific data to infer soil parameters. Then, the impact of soil data source on model uncertainty was assessed by rerunning the simulations while using alternatively locally measured soil inputs or inputs extracted from Fertimap. To disentangle the effect of data source from model sensitivity on model outputs, the model’s sensitivity to labile phosphorus, pH, and organic carbon parameters was also tested. The APSIM-wheat model was found to reasonably simulate wheat phenological stages, biomass, and yield. The comparison of model outputs using one or another source of soil data indicated that using Fertimap had no significant effect on the model’s outputs. This study provides the first assessment of the APSIM-wheat model for simulation of widely used wheat cultivars in Moroccan rainfed areas. It is also the first proof of the practical utility of Fertimap database for modeling purposes in Morocco. This preliminary study delivers a robust basis for model-assisted agricultural advising to take off in Morocco

Grain legume production in Europe for food, feed and meat-substitution

Partial shifts from animal-based to plant-based proteins in human diets could reduce environmental pressure from food systems and serve human health. Grain legumes can play an important role here. They are one of the few agricultural commodities for which Europe is not nearly self-sufficient. Here, we assessed area expansion and yield increases needed for European self-sufficiency of faba bean, pea and soybean. We show that such production could use substantially less cropland (4–8%) and reduce GHG emissions (7–22% current meat production) when substituting for animal-derived food proteins. We discuss changes required in food and agricultural systems to make grain legumes competitive with cereals for farmers and how their cultivation can help to increase sustainability of European cropping systems.</p

Cereal yield gaps across Europe

peer-reviewedEurope accounts for around 20% of the global cereal production and is a net exporter of ca. 15% of that production. Increasing global demand for cereals justifies questions as to where and by how much Europe’s production can be increased to meet future global market demands, and how much additional nitrogen (N) crops would require. The latter is important as environmental concern and legislation are equally important as production aims in Europe. Here, we used a country-by-country, bottom-up approach to establish statistical estimates of actual grain yield, and compare these to modelled estimates of potential yields for either irrigated or rainfed conditions. In this way, we identified the yield gaps and the opportunities for increased cereal production for wheat, barley and maize, which represent 90% of the cereals grown in Europe. The combined mean annual yield gap of wheat, barley, maize was 239 Mt, or 42% of the yield potential. The national yield gaps ranged between 10 and 70%, with small gaps in many north-western European countries, and large gaps in eastern and south-western Europe. Yield gaps for rainfed and irrigated maize were consistently lower than those of wheat and barley. If the yield gaps of maize, wheat and barley would be reduced from 42% to 20% of potential yields, this would increase annual cereal production by 128 Mt (39%). Potential for higher cereal production exists predominantly in Eastern Europe, and half of Europe’s potential increase is located in Ukraine, Romania and Poland. Unlocking the identified potential for production growth requires a substantial increase of the crop N uptake of 4.8 Mt. Across Europe, the average N uptake gaps, to achieve 80% of the yield potential, were 87, 77 and 43 kg N ha−1 for wheat, barley and maize, respectively. Emphasis on increasing the N use efficiency is necessary to minimize the need for additional N inputs. Whether yield gap reduction is desirable and feasible is a matter of balancing Europe’s role in global food security, farm economic objectives and environmental targets.We received financial contributions from the strategic investment funds (IPOP) of Wageningen University & Research, Bill & Melinda Gates Foundation, MACSUR under EU FACCE-JPI which was funded through several national contributions, and TempAg (http://tempag.net/)

Maladies du bois de la vigne : étude des facteurs environnementaux et techniques favorisant l’expression des symptômes dans le vignoble bordelais

Diplôme : Maste

How can lettuce maintain high productivity in the shade of solar panels?

How can lettuce maintain high productivity in the shade of solar panels? . ASA, CSSA and SSSA Annual Meeting

Etude des facteurs environnementaux et techniques favorisant l’expression des symptômes des maladies du bois de la vigne (Esca et Black Dead Arm), dans le vignoble bordelais

Diplôme : Maste