Differential Mechanisms of Potato Yield Loss Induced by High Day and Night Temperatures During Tuber Initiation and Bulking: Photosynthesis and Tuber Growth

The tuber yield of potatoes is vulnerable to high temperature and is challenged by the asymmetric increase in day and night temperatures. This study aimed to evaluate photosynthesis, biomass growth, tuber mass distribution, and dry tuber yield in early harvested potatoes that were field-grown under high day and night temperature conditions during different growth stages. Potatoes were exposed to ambient (control), high night temperature (HNT; 19:00–7:00), high day temperature (HDT; 7:00–19:00), and high day/night temperature (HDNT; all day) for 14 days during tuber initiation (TI) or tuber bulking (TB) using portable, temperature-controlled plastic houses that were controlled to increase the temperature by 4.0°C. During TI, HNT delayed tuber development, thus altering tuber mass distribution by reducing the yield proportion of large tubers of >100 g (-53.7%) and lowering early harvest index (-16.1%), causing a significant yield loss (-17.2%) without interfering with photosynthesis. In contrast, HDT decreased early tuber yield (-18.1%) by reducing photosynthetic sources, which was probably attributed to decreased photosynthetic efficiency through a feedback inhibition. However, HDT altered neither tuber mass distribution nor early harvest index. HDNT during TI exhibited all the aforementioned effects of HNT and HDT (i.e., cumulative effects): reduced yield proportion of large tubers (-46.7%), decreased early harvest index (-23.7%), and reduced photosynthetic rate; thus, HDNT caused the highest yield loss (-30.3%). During TB, when the tubers were fully developed, the thermal effects decreased because most of the effects were either directly or indirectly linked to tuber development. These results provide comprehensive insight to the differential mechanisms of potato yield loss under high day and night temperatures and show that further field experiments should be conducted to cope with the threat of global warming on potato production

Potato Yield Gaps in North Korea and Strategies to Close the Gaps

Potato has become one of the staple crops to improve food security in North Korea since the late 1990s. However, the potato yield has been stagnated around 11–12 t ha−1 for several decades, and a food shortage is still a primary issue in North Korea. Yield gap analyses were carried out using the SUBSTOR-potato model to quantify the potato yield gaps and explore the potential ways to close the yield gaps in two different cropping seasons in North Korea (early- and main-season potatoes). Yield gaps were estimated to be around 80% for both early- and main-season potatoes. Early-season potato yield was substantially determined by water or nitrogen supplies, depending on the year’s weather condition (i.e., with or without spring drought). Irrigation during the vegetative stage could effectively reduce the year-to-year variation in yield as well as the yield gap (+7.0 t ha−1, +66.1%). Meanwhile, additional nitrogen fertilizer in the early-season potatoes was less effective compared to that in the main-season potatoes. For the main-season potatoes, where precipitation was sufficient, the primary limiting factor of yield was nitrogen supply. Since heavy rainfall aggravated nitrogen leaching, additional nitrogen fertilizer is recommended as a top dressing rather than a basal dressing. Additional top dressing at 50 days after planting with the current amount of nitrogen fertilizer was expected to increase the main-season potato yield by 42.0 t ha−1 (+191.4%). This study highlights that the primary limiting factor of potato yield may differ between the cropping seasons. Therefore, our findings suggest that different agronomic strategies should be applied for different cropping seasons to improve potato production in North Korea, where agronomic resources are limited

Accounting for Weather Variability in Farm Management Resource Allocation in Northern Ghana: An Integrated Modeling Approach

Smallholder farmers in Northern Ghana face challenges due to weather variability and market volatility, hindering their ability to invest in sustainable intensification options. Modeling can help understand the relationships between productivity, environmental, and economical aspects, but few models have explored the effects of weather variability on crop management and resource allocation. This study introduces an integrated modeling approach to optimize resource allocation for smallholder mixed crop and livestock farming systems in Northern Ghana. The model combines a process-based crop model, farm simulation model, and annual optimization model. Crop model simulations are driven by a large ensemble of weather time series for two scenarios: good and bad weather. The model accounts for the effects of climate risks on farm management decisions, which can help in supporting investments in sustainable intensification practices, thereby bringing smallholder farmers out of poverty traps. The model was simulated for three different farm types represented in the region. The results suggest that farmers could increase their income by allocating more than 80% of their land to cash crops such as rice, groundnut, and soybeans. The optimized cropping patterns have an over 50% probability of increasing farm income, particularly under bad weather scenarios, compared with current cropping systems

Wheat crop traits conferring high yield potential may also improve yield stability under climate change

Increasing genetic wheat yield potential is considered by many as critical to increasing global wheat yields and production, baring major changes in consumption patterns. Climate change challenges breeding by making target environments less predictable, altering regional productivity and potentially increasing yield variability. Here we used a crop simulation model solution in the SIMPLACE framework to explore yield sensitivity to select trait characteristics (radiation use efficiency [RUE], fruiting efficiency and light extinction coefficient) across 34 locations representing the world’s wheat-producing environments, determining their relationship to increasing yields, yield variability and cultivar performance. The magnitude of the yield increase was trait-dependent and differed between irrigated and rainfed environments. RUE had the most prominent marginal effect on yield, which increased by about 45 % and 33 % in irrigated and rainfed sites, respectively, between the minimum and maximum value of the trait. Altered values of light extinction coefficient had the least effect on yield levels. Higher yields from improved traits were generally associated with increased inter-annual yield variability (measured by standard deviation), but the relative yield variability (as coefficient of variation) remained largely unchanged between base and improved genotypes. This was true under both current and future climate scenarios. In this context, our study suggests higher wheat yields from these traits would not increase climate risk for farmers and the adoption of cultivars with these traits would not be associated with increased yield variability