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Crop models are the primary means by which agricultural scientists assess climate change impacts on crop production. Site-based and high-quality weather and climate data is essential for agronomically and physiologically sound crop simulations under historical and future climate scenarios. Here, we describe a bias-corrected dataset of daily agro-meteorological data for 109 reference weather stations distributed across key production areas of maize, millet, sorghum, and wheat in ten sub-Saharan African countries. The dataset leverages extensive ground observations from the Global Yield Gap Atlas (GYGA), an existing climate change projections dataset from the Inter-Sectoral Model Intercomparison Project (ISIMIP), and a calibrated crop simulation model (the WOrld FOod Studies –WOFOST). The weather data were bias-corrected using the delta method, which is widely used in climate change impact studies. The bias-corrected dataset encompasses daily values of maximum and minimum temperature, precipitation rate, and global radiation obtained from five models participating in the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), as well as simulated daily growth variables for the four crops. The data covers three periods: historical (1995–2014), 2030 (2020–2039), and 2050 (2040–2059). The simulation of daily growth dynamics for maize, millet, sorghum, and wheat growth was performed using the daily weather data and the WOFOST crop model, under potential and water-limited potential conditions. The crop simulation outputs were evaluated using national agronomic expertise. The presented datasets, including the weather dataset and daily simulated crop growth outputs, hold substantial potential for further use in the investigation of future climate change impacts in sub-Saharan Africa. The daily weather data can be used as an input into other modelling frameworks for crops or other sectors (e.g., hydrology). The weather and crop growth data can provide key insights a

Dealing with heterogeneity in leaf canopies when calculating light interception per species in a mixed canopy is a challenge. Goudriaan developed a computationally simple, though conceptually sophisticated, model for light interception in strip canopies, which can be reasonably represented as “blocks”, such as vineyards and crop rows. This model is widely used, but there is no independent verification of the model. Hence, we developed a comparison of light interception calculations with Goudriaan’s model and with detailed spatially explicit three-dimensional functional-structural plant models (FSPM) of maize in which plant architecture can be represented explicitly. Two models were developed, one with small randomly oriented leaves in blocks, similar to Goudriaan’s assumption, which we refer to as the intermediate model (IM), and another with a realistic representation of individual plants with stems and leaves having shape, orientation, etc, referred as FSPM. In IM and FSPM, light interception was calculated using ray tracing. In Goudriaan’s model, the light extinction coefficient (k), including both its daily and seasonal average values, was generated using the FSPM. Correspondence between the three models was excellent in terms of light capture for different levels of crop height, leaf area and uniformity, with the difference less than 3.3%. The results are strong support for the use of Goudriaan's summary model for calculating light interception in strip canopies.

Chloroplasts movement within mesophyll cells in C4 plants is hypothesized to enhance the CO2 concentrating mechanism, but this is difficult to verify experimentally. A three-dimensional (3D) leaf model can help analyse how chloroplast movement influences the operation of the CO2 concentrating mechanism. The first volumetric reaction-diffusion model of C4 photosynthesis that incorporates detailed 3D leaf anatomy, light propagation, ATP and NADPH production, and CO2, O2 and bicarbonate concentration driven by diffusional and assimilation/emission processes was developed. It was implemented for maize leaves to simulate various chloroplast movement scenarios within mesophyll cells: the movement of all mesophyll chloroplasts towards bundle sheath cells (aggregative movement) and movement of only those of interveinal mesophyll cells towards bundle sheath cells (avoidance movement). Light absorbed by bundle sheath chloroplasts relative to mesophyll chloroplasts increased in both cases. Avoidance movement decreased light absorption by mesophyll chloroplasts considerably. Consequently, total ATP and NADPH production and net photosynthetic rate increased for aggregative movement and decreased for avoidance movement compared with the default case of no chloroplast movement at high light intensities. Leakiness increased in both chloroplast movement scenarios due to the imbalance in energy production and demand in mesophyll and bundle sheath cells. These results suggest the need to design strategies for coordinated increases in electron transport and Rubisco activities for an efficient CO2 concentrating mechanism at very high light intensities.

Chloroplasts movement within mesophyll cells in C4 plants is hypothesized to enhance the CO2 concentrating mechanism, but this is difficult to verify experimentally. A three-dimensional (3D) leaf model can help analyse how chloroplast movement influences the operation of the CO2 concentrating mechanism. The first volumetric reaction–diffusion model of C4 photosynthesis that incorporates detailed 3D leaf anatomy, light propagation, ATP and NADPH production, and CO2, O2 and bicarbonate concentration driven by diffusional and assimilation/emission processes was developed. It was implemented for maize leaves to simulate various chloroplast movement scenarios within mesophyll cells: the movement of all mesophyll chloroplasts towards bundle sheath cells (aggregative movement) and movement of only those of interveinal mesophyll cells towards bundle sheath cells (avoidance movement). Light absorbed by bundle sheath chloroplasts relative to mesophyll chloroplasts increased in both cases. Avoidance movement decreased light absorption by mesophyll chloroplasts considerably. Consequently, total ATP and NADPH production and net photosynthetic rate increased for aggregative movement and decreased for avoidance movement compared with the default case of no chloroplast movement at high light intensities. Leakiness increased in both chloroplast movement scenarios due to the imbalance in energy production and demand in mesophyll and bundle sheath cells. These results suggest the need to design strategies for coordinated increases in electron transport and Rubisco activities for an efficient CO2 concentrating mechanism at very high light intensities.

Cereal-legume intercropping can increase yields, reduce fertilizer input and improve soil quality compared with pure culture. Designing intercropping systems requires the integration of plant species trait selection with choice of crop configuration and management. Crop growth models can facilitate the understanding and prediction of the interactions between plant traits, crop configuration and management. However, currently no existing crop growth model has been calibrated and tested for cereal-legume intercrops throughout Europea. We calibrated the Agricultural Production Systems sIMulator (APSIM) for pure cultures of wheat and faba bean using data from Dutch field trials, and determined the phenological parameters to simulate pure cultures and intercrops from seven field experiments across Europe. APSIM successfully reproduced aboveground dry matters and, for wheat only, grain yields in pure cultures. In intercrops, APSIM systematically overestimated the aboveground dry matter and grain yield of faba bean and underestimated those of wheat. APSIM was reasonably capable of simulating plant heights in pure cultures, but respectively overestimated and underestimated the height of faba bean and wheat in intercrops. In order to simulate wheat-faba bean intercrops better, APSIM should be improved regarding the calculation of biomass partitioning to grains in faba bean and of height growth in both species.

This deliverable reports on the work conducted within WP3, based on two existing crop growth models, APSIM and DAISY. The objective of deliverable 3.1 is to identify the key traits and mechanisms underpinning beneficial plant associations, by calibrating, validating and running APSIM and DAISY. For each model, this report presents in detail i) the data used for model calibration and validation, and the rationale for their choice; ii) the calibration and validation process; iii) the results of simulation runs and comparison with field trial data across pedoclimatic conditions; and iv) a discussion of the key aspects driving the performance of each model and the key plant traits defining the output, with particular reference to intercropped systems. In addition, the report also presents an evaluation of resource use efficiencies in support of the modelling work. On the basis of the calibration and validation results, the two models are also contrasted. APSIM and DAISY showed some promising results for the simulation of spring wheat-faba bean and spring barley-field pea systems, towards the identification of the key traits and mechanisms driving the interaction of cereals and legumes in field conditions and across different pedoclimatic regions. Further steps are discussed towards the improvement of the model capabilities, in particular pertaining intercropped systems, also exploiting some additional experimental results relative to plant nutrient use efficiency. (PDF) Summary report on mechanisms underpinning beneficial plant associations based on APSIM and DAISY. Available from: https://www.researchgate.net/publication/342410836_Summary_report_on_mechanisms_underpinning_beneficial_plant_associations_based_on_APSIM_and_DAISY?channel=doi&linkId=5ef3009ea6fdcc158d2605eb&showFulltext=true [accessed Oct 22 2021]., This deliverable reports on the work conducted within WP3, based on two existing crop growth models, APSIM and DAISY. The objective of deliverable 3.1 is to identify the key traits and mechanisms underpinning beneficial plant associations, by calibrating, validating and running APSIM and DAISY. For each model, this report presents in detail i) the data used for model calibration and validation, and the rationale for their choice; ii) the calibration and validation process; iii) the results of simulation runs and comparison with field trial data across pedoclimatic conditions; and iv) a discussion of the key aspects driving the performance of each model and the key plant traits defining the output, with particular reference to intercropped systems. In addition, the report also presents an evaluation of resource use efficiencies in support of the modelling work. On the basis of the calibration and validation results, the two models are also contrasted. APSIM and DAISY showed some promising results for the simulation of spring wheat-faba bean and spring barley-field pea systems, towards the identification of the key traits and mechanisms driving the interaction of cereals and legumes in field conditions and across different pedoclimatic regions. Further steps are discussed towards the improvement of the model capabilities, in particular pertaining intercropped systems, also exploiting some additional experimental results relative to plant nutrient use efficiency.

The rate of photosynthesis depends on the CO2 partial pressure near Rubisco, Cc, which is commonly calculated by models using the overall mesophyll resistance. Such models do not explain the difference between the CO2 level in the intercellular air space and Cc mechanistically. This problem can be overcome by reaction-diffusion models for CO2 transport, production and fixation in leaves. However, most reaction-diffusion models are complex and unattractive for procedures that require a large number of runs, like parameter optimisation. This study provides a simpler reaction-diffusion model. It is parameterized by both leaf physiological and leaf anatomical data. The anatomical data consisted of the thickness of the cell wall, cytosol and stroma, and the area ratios of mesophyll exposed to the intercellular air space to leaf surfaces and exposed chloroplast to exposed mesophyll surfaces. The model was used directly to estimate photosynthetic parameters from a subset of the measured light and CO2 response curves; the remaining data were used for validation. The model predicted light and CO2 response curves reasonably well for 15 days old tomato (cv. Admiro) leaves, if (photo)respiratory CO2 release was assumed to take place in the inner cytosol or in the gaps between the chloroplasts. The model was also used to calculate the fraction of CO2 produced by (photo)respiration that is re-assimilated in the stroma, and this fraction ranged from 56 to 76%. In future research, the model should be further validated to better understand how the re-assimilation of (photo)respired CO2 is affected by environmental conditions and physiological parameters.