This in-depth analysis of the rise in farm yield (FY) of irrigated wheat in the Yaqui Valley of north-west Mexico, from around 2 to 7 t/ha between 1960 and 2019, begins by highlighting a weather component overlooked in modelling and other thinking about wheat and climate change, namely the dominant role of natural annual variation in minimum temperature (Tmin). Year to year fluctuations around the increasing yield trend were substantial (st.dev. 591 kg/ha) and were highly correlated negatively with annual fluctuations in the average Tmin January to March (Tmin J-M) which ranged from 5.0 to 11.5 ^oC in this period lasting from mid tillering to early-mid grain fill. Dividing the 60-year period into three consecutive 20-year periods and using multiple linear regression improved the accuracy of estimates of FY as a linear function of time in each period (responding inter alia to better technology including breeding and agronomy), with slopes of 4.5%, 0.6%, and 1.8% p.a. for 1960–79, 1980–99, and 2000–19, respectively. Tmin J-M coefficients were −218, −413, −406 kg/ha/^oC, or −5.9, −8.1, −6.6%/^oC, respectively, with R² always close to 0.9. Combining results, the FY response to Tmin J-M was close to −7%/^oC, such that over the 60-year period the Tmin J-M increase of 1.0 ^oC contributed a 7% reduction in FY at constant CO2. The improved estimate of FY slopes with respect to time revealed novel variation across the 60 year period to be dissected in a following paper. Annual fluctuations in Tmax J-M were not correlated with variation in Tmin J-M nor with variation in FY. Crop simulation modelling of potential yield (PY) corroborated the negative effect of increased Tmin J-M on yield and suggested that increased Tmin J-M primarily decreased days to anthesis, biomass and number of grains (/m2). Measurements retrieved from long term well-managed experiments in the Valley under constant agronomy and cultivars confirmed all the above predicted responses to Tmin J-M. Our results align with the few published studies increasing crop night temperature in the critical period of around 30 days up to the end of anthesis when grains/m², and hence yield, was inversely related to rate of development. In the Yaqui Valley this was strongly associated with Tmin variation. This phenomenon, and the roles of Tmax and solar radiation (Rs) variation, are discussed in detail.

这项对墨西哥西北部亚基河谷灌溉小麦农场产量 (FY) 增长的深入分析，从 1960 年到 2019 年间从 2 吨/公顷增加到 7 吨/公顷，首先强调了建模和关于小麦和气候变化的其他思考，即最低温度 (Tmin) 的自然年度变化的主导作用。围绕产量增加趋势的逐年波动很大（st.dev. 591 kg/ha），并且与 1 月至 3 月平均 Tmin (Tmin JM) 的年度波动高度负相关，其范围为 5.0 至 11.5  ^oC 在此期间从分蘖中期到早中期籽粒灌浆。将 60 年期划分为三个连续的 20 年期并使用多元线性回归提高了 FY 估计的准确性，作为每个时期的时间线性函数（尤其是对包括育种和农学在内的更好技术的响应），斜率为1960-79、1980-99 和 2000-19 年分别为 4.5%、0.6% 和 1.8%。Tmin JM 系数分别为 -218、-413、-406 kg/ha/ ^o C 或 -5.9、-8.1、-6.6%/ ^o C，R ²始终接近 0.9。综合结果，FY 对 Tmin JM 的响应接近 -7%/ ^o C，因此在 60 年期间，Tmin JM 增加了 1.0  ^o在 CO2 不变的情况下，C 使 FY 减少了 7%。FY 斜率相对于时间的改进估计揭示了 60 年间的新变化，将在下一篇论文中剖析。Tmax JM 的年度波动与 Tmin JM 的变化无关，也与 FY 的变化无关。潜在产量 (PY) 的作物模拟模型证实了 Tmin JM 增加对产量的负面影响，并表明 Tmin JM 增加主要减少开花天数、生物量和籽粒数 (/m2)。在恒定的农学和栽培品种下，从山谷中长期管理良好的实验中检索到的测量结果证实了上述所有对 Tmin JM 的预测响应。²，因此产量，与发展速度成反比。在亚基河谷，这与 Tmin 变化密切相关。详细讨论了这种现象以及 Tmax 和太阳辐射 (Rs) 变化的作用。