SUMMARY: Cultivar selection is a dominant factor in crop production to obtain high yield. While previous studies have evaluated a range of impacts and adaptation of climate change (CC) on crop yield, few studies have focused on evaluating the effectiveness of changing cultivars with different vernalization requirements as an adaptation. In the present study, mean and inter-annual variability of yield were quantified for three winter wheat cultivar types at three ecological sites (Shangzhuang in Beijing, Quzhou in Hebei and Huangfanqu in Henan) in the North China Plain, by linking a crop model and the outputs of Providing Regional Climates for Impacts Studies (PRECIS) for both the baseline (1961–90) and future SRES scenarios A2 and B2 (2070–2100). The results showed that a warming trend prolonged the length of the vegetative growth period of local cultivars through reduced vernalization, generally leading to a negative impact on yield. However, the introduction of cultivars with relatively lower vernalization demands from warmer southern to cooler northern regions could be an effective adaptation strategy to offset the negative impact of climatic change. Adjustment in cultivars increased yield at Shangzhuang and maintained it at Quzhou and Huangfanqu. Elevated CO₂would significantly increase yield in the future with or without considering the sensitivities of the selected cultivars. The inter-annual variability of yield generally increased in the A2 scenario, but decreased in the B2 scenario. Overall, winter wheat with semi-winter types or weak-winter types would grow preferentially, while cultivars with winter types would probably be reduced in future.

Chemical fertiliser nitrogen addition will inhibit biological nitrogen fixation (BNF) for soybean (Glycine max [L.] Merr) growth. The optimal balance of these two nitrogen input sources has been a key issue for sustainable development in Northeast China. We used the data collected from a four-year experiment with varied irrigation and fertiliser treatments from 2007 to 2010 to evaluate the SPACSYS (Soil-Plant-Atmosphere Continuum SYStem) model. The validated model was run to investigate the responses to different management practices in seed yield, BNF, protein yield and soil nitrogen budgets. Scenario testing showed average yield increase of 2.4–5.2% with additional 50–100 kg N/ha application. Irrigation at the reproductive stage improved seed yield in drier years with an increase of 12–33% compared with the rain-fed treatment. BNF was suppressed by fertiliser nitrogen application and drought stress with a decrease of 6–33% and 8–34%, respectively. The average nitrogen budget without fertilization indicated a deficit of 39 kg N/ha. To attain higher seed yield, applying fertiliser at 25–30 and 15–20 kg N/ha before sowing is advised in drier and wetter years, respectively. To achieve a higher seed nitrogen content, an application rate of 55–60 and 45–50 kg N/ha is recommended for drier and wetter years, respectively.

Southwestern China (SWC), one of the major rain-fed wheat production zones in China, has become vulnerable to drought in recent years under global climate change. To quantify drought severity during the wheat growing season and its impact on yield loss, we selected the Agricultural Production Systems sIMulator (APSIM) model to simulate wheat growth between 1961 and 2010 in SWC. A new drought index was developed considering different weighting factors of drought for yield loss in three growing phases. The index was shown to be reliable in assessing drought severity in the region. On average, an abnormal drought mainly occurred in mid-west Guizhou with a frequency of 10–30%. Central SWC was subjected to moderate drought with a frequency of 10–30%, whereas severe drought often occurred in Southern Sichuan and the middle of Yunnan with a frequency >50%. Temporally, drought severity fluctuated before 1990, but increased significantly afterwards. Our assessment suggested that irrigation during the period from floral initiation to flowering would help to ameliorate the effects of water stress under climatic variability in the region.

Winter wheat (Triticum aestivum L.) is a crucial crop that guarantees food supply in the North China Plain (NCP). As the frequency of extreme cold events increases, it is necessary to explore the freezing resistance of different wheat varieties in order to clarify planting boundaries and help with risk assessment. In this study, 2-year controlled experiments were conducted to explore the effect of freezing temperatures (T_air) and freezing durations on three winterness types. A set of indexes were used to characterize the subfreezing stress on wheat tiller, leaf, and final yield. Logistical regressions were used to quantify the temperature threshold for 10%, 30%, and 50% of freezing injury. The results showed that the lower temperature threshold of tiller (LT) varied from −9.6 to −15.9°C, −10.7 to −19.1°C and −11.4 to −21.2°C for LT₁₀, LT₃₀, and LT₅₀, respectively. The difference between LT and yield loss (YL) indexes reduced with decreased winterness types and was −0.1 to 3.4°C, −0.7 to 2.1°C, and 0.3 to 0.9°C higher compared with YL thresholds for winterness, semi-winterness, and weak-winterness types, respectively. The average minimum soil temperature was 7.5, 4.8, and 4.2°C higher than T_air for 1-, 2-, and 3-day treatment, respectively. Soil effective negative accumulated temperature hours (TSE_h) ranged from 6.9 to 12.0, 48.4 to 6.9, and 84.7 to 106.9°C·h for 10%, 30%, and 50% tiller mortality, respectively. Freezing treatment with T_air < −12, −9, and −8°C obviously decreased leaf Fv/Fm for the three varieties and Fv/Fm declined obviously after 5 days of recovery under field conditions. Our results provided multiple indexes for quantifying subfreezing damage in practical wheat production and could shed light on future risk assessment.

The Cucumber Productivity Simulation Model (CPSM) was developed to precisely predict the dynamic process of cucumber productivity in a solar greenhouse. This research conducted a variety of sowing experiments and collected data on cucumber productivity and meteorological conditions from 2013 to 2015 and 2018 to 2020. Employing the principles of least squares, the relationship between cucumber productivity indicators and effective accumulated temperature (EAT) was fitted, determining key crop parameters and constructing the CPSM. Validation of the model was conducted using independent experimental data, evaluating its simulation accuracy. The results indicate that (1) CPSM can dynamically and meticulously simulate the formation process of different productivity indicators in cucumber. Normalized root mean square errors (NRMSE) ranged from 0.44% to 19.64%, and mean relative errors (MRE) ranged from 0.31% to 17.23% across different productivity indicator models. The models for organ water content, maximum root length, specific leaf area, and organ fresh weight distribution index demonstrated high simulation accuracy, while others showed relatively high accuracy. (2) Simulation accuracy varied with indicators and varieties. 19 indicators (34.55%) exhibited high simulation accuracy and 30 indicators (54.55%) showed relatively high accuracy. The JY35 variety (10.44 ± 8.49%) outperformed the JS206 variety (13.44 ± 8.50%) in terms of simulation accuracy. The JY35 variety had 39 superior productivity indicators (70.91%) while the JS206 variety had sixteen (29.09%). CPSM utilizes easily accessible temperature data as its input, allowing for precise and detailed simulation of productivity indicators for cucumber production in solar greenhouses. This research lays a theoretical foundation and provides technical support for guiding intelligent production management, efficient utilization of agricultural resources, and climate change productivity assessment in solar greenhouse cucumber production.