Diels, J. | Search bioRxiv

bioRxiv2024

Pear (Pyrus communis L. cv. Conference) has shade-tolerant features allowing for consistent agrivoltaic crop yield

Transitioning to a fossil fuel free society requires an increase in solar energy production. However, expanding solar power to farmland competes with food production. Additionally, climate change threatens food security and leads increasingly to yield losses. Agrivoltaics (AV) systems produce solar energy and food on the same field, while sheltering crops. In AV systems, crops grow in a modified environment with reduced solar irradiance, a tempered microclimate and a potential physical cover protecting against hail damage. This research describes pear production under an AV pilot with 24% light reduction for 3 consecutive seasons. AV pear trees yielded 14% less than the reference. Flowering and fruit set was unchanged while AV reduced leaf flavonoid levels. The leaf photosynthetic light response was identical, yet a delayed leaf senescence under AV suggests an adaptation to the modified environment. AV impacted fruit shape, as there was an increase in the number of bottle shaped pears and a reduction in caliber. Other fruit quality traits were broadly unaffected, yet postharvest ethylene production was higher for AV fruit in 2022 than for the control. This study demonstrates that AV systems hold potential for pear production under temperate climates and highlights plant adaptations that make this possible. HighlightPear cultivation in agrivoltaic systems integrates renewable energy and sustainable fruit production. This study provides insights into crop yield, fruit quality, and plant adaptation towards an agrivoltaic environment.

plant biology↗

bioRxiv2018

Options for calibrating CERES-maize genotype specific parameters under data-scarce environments

Most crop simulation models require the use of Genotype Specific Parameters (GSPs) which provide the Genotype component of GxExM interactions. Estimation of GSPs is the most difficult aspect of most modelling exercises because it requires expensive and time-consuming field experiments. GSPs could also be estimated using multi-year and multi locational data from breeder evaluation experiments. This research was set up with the following objectives: i) to determine GSPs of 10 newly released maize varieties for the Nigerian Savannas using data from both calibration experiments and by using existing data from breeder varietal evaluation trials; ii) to compare the accuracy of the GSPs generated using experimental and breeder data; and iii) to evaluate CERES-Maize model to simulate grain and tissue nitrogen contents. For experimental evaluation, 8 different experiments were conducted during the rainy and dry seasons of 2016 across the Nigerian Savanna. Breeder evaluation data was also collected for 2 years and 7 locations. The calibrated GSPs were evaluated using data from a 4 year experiment conducted under varying nitrogen rates (0, 60 and 120kg N ha-1). For the model calibration using experimental data, calculated model efficiency (EF) values ranged between 0.86-0.92 and coefficient of determination (d-index) between 0.92-0.98. Calibration of time-series data produced nRMSE below 7% while all prediction deviations were below 10% of the mean. For breeder experiments, EF (0.52-0.81) and d-index (0.46-0.83) ranges were lower. Prediction deviations were below 17% of the means for all measured variables. Model evaluation using both experimental and breeder trials resulted in good agreement (low RMSE, high EF and d-index values) between observed and simulated grain yields, and tissue and grain nitrogen contents. We conclude that higher calibration accuracy of CERES-Maize model is achieved from detailed experiments. If unavailable, data from breeder experimental trials collected from many locations and planting dates can be used with lower but acceptable accuracy.

scientific communication and education↗