Wheat–chickpea intercrops are not well studied, despite the importance of these two species in increasing agricultural profitability and ensuring nutritional and food security. The present study aims to assess the intercropping arable system’s services under contrasting field management and climate conditions. Simultaneously, this assessment focuses on the most agronomic and ecological indices widely used in the literature. Durum wheat (Triticum turgidum durum L.cv. VITRON) and chickpea (Cicer arietinum L.cv. FLIP 90/13 C) were cultivated, both in sole crop and intercrop during the 2018/2019 growing season. A field experiment was carried out under controlled conditions at three contrasting pedoclimatic sites and under three levels of N fertilization. Both grain and N yield of mixture crop were significantly higher (+11%) when chickpea and durum wheat were grown together under either low or moderate N application. Soil N availability as compared to the critical level increased by more than 19% from flowering to harvest stage for intercropped wheat under low N application (N-30 and N-60), while it decreased significantly for intercropped chickpea. In rich N soils and under low rainfall conditions (site 1 and 3), intercropping was generally more advantageous for yield (+14%), N yield (+23%), and land use (103 and 119.5% for grain and N yield, respectively) only with reduced N fertilization as assessed using both land equivalent ratio (LER) and land-use efficiency (LUE). Competition dominance was directly affected by changes in climatic conditions over sites; intercropped wheat was more competitive than their respective chickpea under low rainfall conditions. These findings illustrate the crucial role of competitive index assessment in intercropping to promise a robust method for crop N and yield diagnosis during fertilization decision-making.

It is well known that multiple interactions can occur between nitrogen and water use, depending on climate, soil and crop characteristics, in crop growth and yield development. However, little is known about the simultaneous change in both water and N use efficiency (WUE and NUE) and their possible interactions in cereal–-legume intercropping systems. In order to advance our knowledge on the N and water facilitation mechanisms involved in the intercropping responses of N and water input co-limitations, we investigated, via four experiment years, the simultaneous optimization of water and N-fertilizer inputs, as well as its possible effects on growth, yield, N acquisition, and the NUE and WUE in intercropped species. The results indicated that intercropping increases the leaf area index by more than +0.14 and +1.03 units when compared to durum wheat and chickpea monoculture systems, respectively. This increase is particularly noticeable under higher rainfalls during the crop period (i.e., as can be seen in the 2022, 2020, and 2019 seasons). Moderate N-application enhanced both the grain yield and protein accumulation in the mixed crops by more than 0.22 t ha⁻¹ and 57 kg ha⁻¹, respectively. Conversely, intercropping significantly decreased the mixed grain yield when compared to durum wheat monocultures. Intercropping advantages in terms of biomass (ranged from 1 to 44%) and N-acquisition (2 to 91%) was confirmed in either low- (2021) or high- (2019 and 2022) rainfall growing periods, but only under low and moderate N-applications. Improving N nutrition under both rainfall and drought growth periods was confirmed only for the mixed crops under all applied N-fertilizer doses. Such improvements in growth, N acquisition, and yield quality were most likely achieved by positive interactions (r² = 0.73, p ≤ 0.001) between the NUE and WUE for the chickpea–wheat intercropping. Thus, 0.62 kg m⁻³ of WUE promotes a significant increase of 1 kg kg⁻¹ in NUE by mixing chickpea-durum wheat. Rain-fed chickpea-durum wheat intercropping provides a higher performance in growth and yield quality compared to sole cropping systems; this may occur from the simultaneous optimizations of both water and N fertilizer inputs in low-N soil under semiarid conditions.

Phosphorus (P) is known as a major limiting factor of crop yields at the global scale. Previous estimates of the global P limitation are either based on statistical approaches or on complex global gridded crop models. Both failed to distinguish between P and the other limiting factors. Global gridded crop models, despite their complexities, omitted key mechanisms such as soil P dynamics or plant adjustments to P limitation (e.g., change in root:shoot ratio or in shoot P concentration). Thus, current approaches fail to quantify the contribution of P limitation to the global yield gap. Here, we developed a simple but mechanistic model (called GPCROP) that simulates the interactions between plant growth and soil P at a daily time step, all other factors being assumed non‐limiting. The model explicitly represents key mechanisms such as the replenishment of the soil P solution by more stable soil P pools, the diffusion of P in soil, and plant adjustments to P limitation. We found that soil available P greatly limits the global maize potential production, even when that limitation was strongly alleviated by plant adjustment mechanisms. With and without these adjustments, maize global production would decrease by 78.9% (std = 17.3) and 92.7% (std = 7.4), respectively, compared to its potential production. We also found that the beginning of the growing season is a key period for P limitation as roots, not yet developed, cannot sustain the plant P demand. This suggests that earlier studies based on a comparison between annual averages of soil supply versus plant demand are not appropriate for assessing P limitation. Considerable uncertainties remain in our approach, and we especially stress the need to use global datasets of soil iron and aluminum (hydr)oxides, currently in development, to constrain the spatial variation of some key parameters driving the P concentration of the soil solution.

Phosphorus (P) is one of the key limitations to crop yields. However, the relationship between soil P and yield is far to be understood at the global scale, given some difficulties in global soil P mapping [Helfenstein et al., 2024], complexities to model soil P dynamics and spatially variable interactions between P and other sources of yield gap (nitrogen, water, pest and diseases).To better understand the P limitation of crop yield at the global scale, we developed here a simple but mechanistic approach (called GPCROP) to simulate the interaction between plant and soil P at daily time-step for one year. The model assumes no other limitation (water, N), and thus allows quantifying the P limitation of potential yield by the current soil P. Simulations are performed for maize at half-degree latitude x longitude spatial resolution.GPCROP combines and builds on four previously developed models that we here combined: a model of potential growth for maize (SIM, [Ringeval et al., 2021]), a model describing the soil P dynamics (GPASOIL, [Ringeval et al., 2024]), a parametrization for the P supply by root (following [Kvakic et al., 2018]), and a model describing the allocation of C and P among plant organs, inspired of [Kvakic et al., 2020]. In particular, the soil P dynamics model allows us to represent the resplenishment of the soil P solution by more stable soil P pools, the parametrization for the P supply by root allows us to represent the diffusion of P in soil and the allocation model, based on an optimization procedure, allows us to represent plant adjustments to P limitation such as change in root:shoot ratio and change in leaf P concentration.Thanks to GPCROP, we quantified the limitation of potential yield by P at the global scale. An uncertainty related to key model parameters and model input was also provided. Simulations underlined the importance of the begin of the growing season when roots are poorly developped in the magnitude of the limitation on final yield. Plant adjustements do particularly matter at that moment of the growing season as they allow (at least partly) to alleviate the P limitation, and we estimated their contribution in the reduction of the global P limitation.References:Helfenstein et al., 2024 : Understanding soil phosphorus cycling for sustainable development: A review. One Earth, S2590332224003737.Kvakic et al., 2018 : Quantifying the Limitation to World Cereal Production Due To Soil Phosphorus Status. Global Biogeochemical Cycles, https://doi.org/10.1002/2017GB005754.Kvakic et al., 2020 : Carbon and Phosphorus Allocation in Annual Plants: An Optimal Functioning Approach. Frontiers in Plant Science, 11:149, https://doi.org/10.3389/fpls.2020.00149.Ringeval et al., 2021 : Potential yield simulated by global gridded crop models: using a process-based emulator to explain their differences. Geoscientific Model Development, 14(3):1639–1656, https://doi.org/10.5194/gmd-14-1639-2021, 2021.Ringeval et al., 2024 : A global dataset on phosphorus in agricultural soils. Scientific Data, 11(1):17, https://doi.org/10.1038/s41597-023-02751-6.