Biology subjects

Iizumi, T.

Publications and source records attributed to Iizumi, T..

3 recordsLinked to original sources

bioRxiv2025

Optimization of Crop Rotation Calendar to Maximize System-Level Productivity under Climate Change

Crop rotation offers multifaceted benefits for climate adaptation and mitigation. As rising temperatures accelerate crop development, it is necessary to adjust the rotation order and sowing dates of crops in a rotation system. Such an adjustment can enhance agricultural productivity at the whole rotation system level even under warmer conditions. Here, we present a computational approach to identify the crop rotation calendar (the order and sowing dates of rotation crops) that maximizes total crop output with available climatic resources. In this study, the rotation order indicates the cyclical sequence of crop species without intercropping, cover crop and fallow. This approach involves two steps: (1) generating crop windows (the timing and length of crop duration from sowing to harvest) and corresponding outputs (production per unit land area per harvest) for the rotation crops using a crop growth model with daily weather inputs; and (2) applying an optimization algorithm to identify a single subset of crop windows of rotation crops that maximizes the total crop output while satisfying agronomic constraints. We applied this method to a four-year, four-crop rotation system in northern Japan, with historical and projected climates from 2000 to 2100. The results revealed that adjusting crop windows would reduce the time to complete all rotation crops in the system (shortened rotation cycle) and enhance the system-level annual productivity [kgDW ha-1 year-1] with time. The increase in this productivity is approximately 0.5 % per year under high warming of the Shared Socioeconomic Pathway 5-8.5. Optimizing the rotation order in addition to the rotation crops sowing dates showed the changes in the most productive rotation orders, demonstrating the dynamic nature of rotation planning under climate change. Our methodology offers a flexible, scalable means of designing cropping system to harness the positive effect of climate change on long-term food security.

plant biology↗

bioRxiv2023

Assessing climate change risks associated with precipitation at unfavorable times in winter wheat using an improved crop calendar model incorporating vernalization and winter survival

Crop phenology calendars are necessary for designing breeding goals and for developing effective management practices. Winter wheat is a representative biennial, the cultivation schedule of which is constrained by winter climate conditions, particularly the processes of vernalization and winter survival. Here, we present improvements to a rule-based crop phenology model by incorporating these factors so that it can be used to accurately estimate the phenological events of winter wheat from daily meteorological data. We tested the improved model in Hokkaido, the northernmost Japanese island, which is characterized by seasonal snow cover and a wet summer. The results confirmed that implementing these factors contributed to accurate estimates of peak occurrence dates of winter wheat phenological events. Furthermore, we applied the improved model to simulate wheat phenology under 2 K and 4 K warmer scenarios. The results showed a delayed sowing period up to approximately one month and slight advancements in both flowering and harvesting, leading to a shorter growth period. While this shortened period may be largely compensated by a decrease in the snow-covered period, the shifts in the vegetative and reproductive phases may have a significant influence on sink-source balance of wheat. We also assessed the risks of pollination failure and preharvest sprouting, both of which are associated with the timing of precipitation, based on the number of rainy days around flowering, and the incidence of precipitation over two consecutive days around the time of harvesting. Our simulations suggested increased risk of pollination failure and reduced risk of preharvest sprouting, leading to an increase in the probability of crop failure. These findings underscore the importance of implementing adaptive measures to mitigate precipitation-related risk under future climate scenarios. Further, the findings provide valuable insights for winter wheat breeders and agronomists, thereby facilitating crop production adaptation strategies.

plant biology↗

bioRxiv2020

Data-driven yield projections suggest large opportunities to improve Europe's soybean self-sufficiency under climate change

Currently, demand for soybean in Europe is mostly fulfilled by imports. However, soybean-growing areas across Europe have been rapidly increasing in response to a rising demand for locally-produced, non-GM soybean in recent years. This raises questions about the suitability of European agro-climatic conditions for soybean production. We used data-driven relationships between climate and soybean yield derived from machine-learning techniques to make yield projections under current and future climate with moderate (RCP 4.5) to intense (RCP 8.5) warming, up to the 2050s and 2090s time horizons. Results suggest that a self-sufficiency level of 50% (100%) would be achievable in Europe under historical and future climate if 4-5% (9-12%) of the current European cropland is dedicated to soybean production. The associated increase in soybean area in Europe would bring environmental benefits, with a potential decrease of nitrogen fertilizer use in Europe by 5-8% (13-18%) and a possible reduction of deforestation in biodiversity hotspots in South America. However, it would also lead to an important reduction in the production of other cultivated species in Europe (e.g. cereals) and a potential increase in the use of irrigation water.

plant biology↗