Hot spots of wheat yield decline with rising temperatures

Abstract

Many of the irrigated spring wheat regions in the world are also regions with high poverty. The impacts of temperature increase on wheat yield in regions of high poverty are uncertain. A grain yield-temperature response function combined with a quantification of model uncertainty was constructed using a multimodel ensemble from two key irrigated spring wheat areas (India and Sudan) and applied to all irrigated spring wheat regions in the world. Southern Indian and southern Pakistani wheat-growing regions with large yield reductions from increasing temperatures coincided with high poverty headcounts, indicating these areas as future food security 'hot spots'. The multimodel simulations produced a linear absolute decline of yields with increasing temperature, with uncertainty varying with reference temperature at a location. As a consequence of the linear absolute yield decline, the relative yield reductions are larger in low-yielding environments (e.g., high reference temperature areas in southern India, southern Pakistan and all Sudan wheat-growing regions) and farmers in these regions will be hit hardest by increasing temperatures. However, as absolute yield declines are about the same in low- and high-yielding regions, the contributed deficit to national production caused by increasing temperatures is higher in high-yielding environments (e.g., northern India) because these environments contribute more to national wheat production. Although Sudan could potentially grow more wheat if irrigation is available, grain yields would be low due to high reference temperatures, with future increases in temperature further limiting production.

Evaluation of the Disintegrant Properties of Native Starches of Five New Cassava Varieties in Paracetamol Tablet Formulations

“…From Table 3, the DER of the tablets generally increased with increase in the concentration of cassava starch. This observation is in agreement with the results of a recent study in Nigeria [18]. The rank order of the DER values of tablets containing cassava starch was V40 > V50 > V20 > V60 > V30 >V10.…”

“…Cassava starch yield was affected by the cassava variety used. Other factors which are known to affect cassava starch yield include processing factors [16], the extraction method employed [17], and the season of harvest of the cassava crop [18]. The cassava starches were white in colour and odourless and had characteristic fine texture and bland taste which complied with the official organoleptic tests for starch [9].…”

“…Thus, tablets with high C t / F t values have strong mechanical strength [33]. The disintegration efficiency ratio (DER) is also a measure of the balance between the mechanical and disintegrant properties of tablets [18]. The DER provides a better measure of tablet quality than crushing strength/friability ratio as the DER assesses the mechanical strength of a tablet by taking into consideration the negative effects on disintegration time and weakness related to friability [34].…”

Closing the global ozone yield gap: Quantification and cobenefits for multistress tolerance

“…Our multistress analysis confirmed that heat stress is particularly important in this region (Lobell, Sibley, & Ortiz‐Monasterio, ). Site‐specific analysis of the effects of future increases in temperature in 2030–2040 indicated that heat stress is likely to continue to reduce yields in the Indo‐Gangetic Plain, especially under climate change (Asseng, Cammarano, & Basso, ). Given that from a food security perspective, it is crucial to reduce yield gaps in India, reducing ozone pollution and/or its effects could potentially provide beneficial additional yield in future climates.…”

Weather dataset choice introduces uncertainty to estimates of crop yield responses to climate variability and change

“…In this study, we address this knowledge gap by developing multiple statistical crop yield models for wheat and rice production in India using 50 unique combinations of weather datasets. Our study focuses on India due to the availability of comprehensive historical yield observation data, along with the widespread past use of statistical modelling approaches in India and South Asia as part of climate impact resear-ch (Lobell et al 2012, Duncan et al 2015, 2016, Asseng et al 2017, Jain et al 2017, Gilmont et al 2018. We hypothesise that weather dataset choice will have an impact on estimates of crop yield responses to weather shocks.…”