Accelerated Domestication of New Crops: Yield is Key

Sustainable agriculture in the future will depend on crops that are tolerant to biotic and abiotic stresses, require minimal input of water and nutrients and can be cultivated with a minimal carbon footprint. Wild plants that fulfill these requirements abound in nature but are typically low yielding. Thus, replacing current high-yielding crops with less productive but resilient species will require the intractable trade-off of increasing land area under cultivation to produce the same yield. Cultivating more land reduces natural resources, reduces biodiversity and increases our carbon footprint. Sustainable intensification can be achieved by increasing the yield of underutilized or wild plant species that are already resilient, but achieving this goal by conventional breeding programs may be a long-term prospect. De novo domestication of orphan or crop wild relatives using mutagenesis is an alternative and fast approach to achieve resilient crops with high yields. With new precise molecular techniques, it should be possible to reach economically sustainable yields in a much shorter period of time than ever before in the history of agriculture.

Perennials as Future Grain Crops: Opportunities and Challenges

Perennial grain crops could make a valuable addition to sustainable agriculture, potentially even as an alternative to their annual counterparts. The ability of perennials to grow year after year significantly reduces the number of agricultural inputs required, in terms of both planting and weed control, while reduced tillage improves soil health and on-farm biodiversity. Presently, perennial grain crops are not grown at large scale, mainly due to their early stages of domestication and current low yields. Narrowing the yield gap between perennial and annual grain crops will depend on characterizing differences in their life cycles, resource allocation, and reproductive strategies and understanding the trade-offs between annualism, perennialism, and yield. The genetic and biochemical pathways controlling plant growth, physiology, and senescence should be analyzed in perennial crop plants. This information could then be used to facilitate tailored genetic improvement of selected perennial grain crops to improve agronomic traits and enhance yield, while maintaining the benefits associated with perennialism.

Efficient Regulation of CO2 Assimilation Enables Greater Resilience to High Temperature and Drought in Maize

Increasing temperatures and extended drought episodes are among the major constraints affecting food production. Maize has a relatively high temperature optimum for photosynthesis compared to C₃ crops, however, the response of this important C₄ crop to the combination of heat and drought stress is poorly understood. Here, we hypothesized that resilience to high temperature combined with water deficit (WD) would require efficient regulation of the photosynthetic traits of maize, including the C₄-CO₂ concentrating mechanism (CCM). Two genotypes of maize with contrasting levels of drought and heat tolerance, B73 and P0023, were acclimatized at high temperature (38°C versus 25°C) under well-watered (WW) or WD conditions. The photosynthetic performance was evaluated by gas exchange and chlorophyll a fluorescence, and in vitro activities of key enzymes for carboxylation (phosphoenolpyruvate carboxylase), decarboxylation (NADP-malic enzyme), and carbon fixation (Rubisco). Both genotypes successfully acclimatized to the high temperature, although with different mechanisms: while B73 maintained the photosynthetic rates by increasing stomatal conductance (gs), P0023 maintained gs and showed limited transpiration. When WD was experienced in combination with high temperatures, limited transpiration allowed water-savings and acted as a drought stress avoidance mechanism. The photosynthetic efficiency in P0023 was sustained by higher phosphorylated PEPC and electron transport rate (ETR) near vascular tissues, supplying chemical energy for an effective CCM. These results suggest that the key traits for drought and heat tolerance in maize are limited transpiration rate, allied with a synchronized regulation of the carbon assimilation metabolism. These findings can be exploited in future breeding efforts aimed at improving maize resilience to climate change.

Antifungal and Anti-Inflammatory Potential of Bupleurum rigidum subsp. paniculatum (Brot.) H.Wolff Essential Oil

Fungal infections remain a major health concern with aromatic plants and their metabolites standing out as promising antifungal agents. The present study aims to assess, for the first time, the antifungal and anti-inflammatory potential of Bupleurum subsp. paniculatum (Brot.) H.Wolff essential oil from Portugal. The oil obtained by hydrodistillation and characterized by GC-MS, showed high amounts of monoterpene hydrocarbons, namely α-pinene (29.0-36.0%), β-pinene (26.1-30.7%) and limonene (10.5-13.5%). The antifungal potential was assessed, according to CLSI guidelines, against several clinical and collection strains. The essential oil showed a broad fungicidal effect being more potent against Cryptococcus neoformans and dermatophytes. Moreover, a significant germ tube inhibition was observed in Candida albicans as well as a disruption of mature biofilms, thus pointing out an effect of the oil against relevant virulent factors. Furthermore, fungal ultrastructural modifications were detected through transmission electron microscopy, highlighting the nefarious effect of the oil. Of relevance, the oil also evidenced anti-inflammatory activity through nitric oxide inhibition in macrophages activated with lipopolysaccharide. In addition, the essential oil's bioactive concentrations did not present toxicity towards macrophages. Overall, the present study confirmed the bioactive potential of B. rigidum subsp. paniculatum essential oil, thus paving the way for the development of effective drugs presenting concomitantly antifungal and anti-inflammatory properties.

High-throughput phenotyping of physiological traits for wheat resilience to high temperature and drought stress

Interannual and local fluctuations in wheat crop yield are mostly explained by abiotic constraints. Heatwaves and drought, which are among the top stressors, commonly co-occur, and their frequency is increasing with global climate change. High-throughput methods were optimized to phenotype wheat plants under controlled water deficit and high temperature, with the aim to identify phenotypic traits conferring adaptative stress responses. Wheat plants of 10 genotypes were grown in a fully automated plant facility under 25/18 °C day/night for 30 d, and then the temperature was increased for 7 d (38/31 °C day/night) while maintaining half of the plants well irrigated and half at 30% field capacity. Thermal and multispectral images and pot weights were registered twice daily. At the end of the experiment, key metabolites and enzyme activities from carbohydrate and antioxidant metabolism were quantified. Regression machine learning models were successfully established to predict plant biomass using image-extracted parameters. Evapotranspiration traits expressed significant genotype-environment interactions (G×E) when acclimatization to stress was continuously monitored. Consequently, transpiration efficiency was essential to maintain the balance between water-saving strategies and biomass production in wheat under water deficit and high temperature. Stress tolerance included changes in carbohydrate metabolism, particularly in the sucrolytic and glycolytic pathways, and in antioxidant metabolism. The observed genetic differences in sensitivity to high temperature and water deficit can be exploited in breeding programmes to improve wheat resilience to climate change.

Photoprotection and optimization of sucrose usage contribute to faster recovery of photosynthesis after water deficit at high temperatures in wheat

Plants are increasingly exposed to events of elevated temperature and water deficit, which threaten crop productivity. Understanding the ability to rapidly recover from abiotic stress, restoring carbon assimilation and biomass production, is important to unravel crop climate resilience. This study compared the photosynthetic performance of two Triticum aestivum L. cultivars, Sokoll and Paragon, adapted to the climate of Mexico and UK, respectively, exposed to 1-week water deficit and high temperatures, in isolation or combination. Measurements included photosynthetic assimilation rate, stomatal conductance, in vitro activities of Rubisco (EC 4.1.1.39) and invertase (INV, EC 3.2.1.26), antioxidant capacity and chlorophyll a fluorescence. In both genotypes, under elevated temperatures and water deficit (WD38°C), the photosynthetic limitations were mainly due to stomatal restrictions and to a decrease in the electron transport rate. Chlorophyll a fluorescence parameters clearly indicate differences between the two genotypes in the photoprotection when subjected to WD38°C and showed faster recovery of Paragon after stress relief. The activity of the cytosolic invertase (CytINV) under these stress conditions was strongly related to the fast photosynthesis recovery of Paragon. Taken together, the results suggest that optimal sucrose export/utilization and increased photoprotection of the electron transport machinery are important components to limit yield fluctuations due to water shortage and elevated temperatures.

De novo domestication: what about the weeds?

Most high-yielding crops are susceptible to abiotic and biotic stresses, making them particularly vulnerable to the potential effects of climate change. A possible alternative is to accelerate the domestication of wild plants that are already tolerant to harsh conditions and to increase their yields by methods such as gene editing. We foresee that crops' wild progenitors could potentially compete with the resulting de novo domesticated plants, reducing yields. To improve the recognition of weeds, we propose using gene editing techniques to introduce traits into de novo domesticated crops that will allow for visual recognition of the crops by weeding robots that have been trained by machine learning.