Extreme heat effects on perennial crops and strategies for sustaining future production

A variety-specific analysis of climate change effects on California winegrapes

California contains a broad geography over which climate conditions can be suitable for cultivating multiple varieties of winegrapes. However, climate change is projected to make winegrape cultivation more challenging across many of California's winegrowing regions. In order to understand the potential effects of climate change on winegrapes, this study models variety-specific phenology for six winegrape varieties and quantifies the change in phenology and viticulturally-important agroclimate metrics over 12 of California's American Viticultural Areas (AVAs) by the mid-21st century. Results show more rapid development for winegrapes with earlier budburst, flowering, veraison, and maturation across all varieties and AVAs. Cabernet Sauvignon shows the greatest change in phenology timing, while Chardonnay shows the least change. Likewise, the West Sonoma Coast AVA shows the greatest average change in phenology timing across varieties and development stages and Lodi AVA shows the least. Projected changes in agroclimatic metrics include an additional month of potentially damaging heat days (above 35 °C) in some AVAs, and decreases in frost days. These results have implications for numerous factors related to viticultural production, including water resources management and crop yield and quality, and underscore the need for California winegrape growers to improve their resilience to climate change by adopting strategies such as increasing soil health and water use efficiency and selecting cultivars suited for future climate conditions. By conducting climate effects analyses at the variety-specific and AVA scale, important information is provided to the winegrowing industry at a resolution that can support decision-making towards resilience.

Phloem anatomy predicts berry sugar accumulation across 13 wine-grape cultivars

Introduction

Climate change is impacting the wine industry by accelerating ripening processes due to warming temperatures, especially in areas of significant grape production like California. Increasing temperatures accelerate the rate of sugar accumulation (measured in ⁰Brix) in grapes, however this presents a problem to wine makers as flavor profiles may need more time to develop properly. To alleviate the mismatch between sugar accumulation and flavor compounds, growers may sync vine cultivars with climates that are most amenable to their distinct growing conditions. However, the traits which control such cultivar specific climate adaptation, especially for ⁰Brix accumulation rate, are poorly understood. Recent studies have shown that higher rates of fruit development and sugar accumulation are predicted by larger phloem areas in different organs of the plant.

Methods

Here we test this phloem area hypothesis using a common garden experiment in the Central Valley of Northern California using 18 cultivars of the common grapevine (Vitis vinifera) and assess the grape berry sugar accumulation rates as a function of phloem area in leaf and grape organs.

Results

We find that phloem area in the leaf petiole organ as well as the berry pedicel is a significant predictor of ⁰Brix accumulation rate across 13 cultivars and that grapes from warm climates overall have larger phloem areas than those from hot climates. In contrast, other physiological traits such as photosynthetic assimilation and leaf water potential did not predict berry accumulation rates.

Discussion

As hot climate cultivars have lower phloem areas which would slow down brix accumulation, growers may have inadvertently been selecting this trait to align flavor development with sugar accumulation across the common cultivars tested. This work highlights a new trait that can be easily phenotyped (i.e., petiole phloem area) and be used for growers to match cultivar more accurately with the temperature specific climate conditions of a growing region to obtain satisfactory sugar accumulation and flavor profiles.

Effects of Heat Stress on Plant-Nutrient Relations: An Update on Nutrient Uptake, Transport, and Assimilation

As a consequence of global climate change, the frequency, severity, and duration of heat stress are increasing, impacting plant growth, development, and reproduction. While several studies have focused on the physiological and molecular aspects of heat stress, there is growing concern that crop quality, particularly nutritional content and phytochemicals important for human health, is also negatively impacted. This comprehensive review aims to provide profound insights into the multifaceted effects of heat stress on plant-nutrient relationships, with a particular emphasis on tissue nutrient concentration, the pivotal nutrient-uptake proteins unique to both macro- and micronutrients, and the effects on dietary phytochemicals. Finally, we propose a new approach to investigate the response of plants to heat stress by exploring the possible role of plant peroxisomes in the context of heat stress and nutrient mobilization. Understanding these complex mechanisms is crucial for developing strategies to improve plant nutrition and resilience during heat stress.

Climate analogs can catalyze cross-regional dialogs for US specialty crop adaptation

Communication theory suggests that interactive dialog rather than information transmission is necessary for climate change action, especially for complex systems like agriculture. Climate analogs-locations whose current climate is similar to a target location's future climate-have garnered recent interest as transmitting more relatable information; however, they have unexplored potential in facilitating meaningful dialogs, and whether the way the analogs are developed could make a difference. We developed climate context-specific analogs based on agriculturally-relevant climate metrics for US specialty crop production, and explored their potential for facilitating dialogs on climate adaptation options. Over 80% of US specialty crop counties had acceptable US analogs for the mid-twenty-first century, especially in the West and Northeast which had greater similarities in the crops produced across target-analog pairs. Western counties generally had analogs to the south, and those in other regions had them to the west. A pilot dialog of target-analog pairs showed promise in eliciting actionable adaptation insights, indicating potential value in incorporating analog-driven dialogs more broadly in climate change communication.

Response of root and root hair phenotypes of cotton seedlings under high temperature revealed with RhizoPot

Driven by the increase in its frequency and duration, high temperature weather is increasingly seriously affecting crop development. High temperature inhibits the leaf development, flowering, and pollination of cotton, but its effects on the roots and root hair phenotypes and lifespans remain unclear. Thus, this study selected the two cotton varieties Nongda 601 (ND) and Guoxin 9 (GX) as materials and adopted the RhizoPot, an in situ root observation system, to investigate the effects of high temperature (38°C day and 32°C night) on the growth dynamics of the aboveground parts and root phenotypes of cotton at the seedling stage. The results showed that high temperature reduced the net photosynthetic rate and chlorophyll content, decreased the dry matter accumulation and transfer to the root, and lowered the root-shoot ratio (R/S ratio). The root phenotypes changed significantly under high temperature. After 7 d of high temperature stress, the root lengths of ND and GX decreased by 78.14 mm and 59.64 mm, respectively. Their specific root lengths increased by 79.60% and 66.11%, respectively. Their specific root surface areas increased by 418.70 cm²·g^-1 and 433.42 cm²·g^-1, respectively. Their proportions of very fine roots increased to 99.26% and 97.16%, respectively. After the removal of high temperature (RHT), their root lengths tended to increase, and their proportions of very fine roots continued to increase. The root hairs of ND and GX were also significantly affected by high temperature. In particular, the root hair densities of ND and GX decreased by 52.53% and 56.25%, respectively. Their average root hair lengths decreased by 96.62% and 74.29%, respectively. Their root hair lifespans decreased by 7 d and 10 d, respectively. After the RHT, their average root hair lengths failed to recover. A principal component analysis indicated that the root architectures were significantly affected by root hair density, average root hair length, specific root length, and specific root surface area under high temperatures. In summary, cotton adapts to high temperature environments by increasing the specific root length, specific root surface area, and the proportions of very fine roots, and reducing the lifespan of root hairs.

County-Level Irrigation Water Demand Estimation Using Machine Learning: Case Study of California

Irrigated agriculture is the largest consumer of freshwater globally. Despite the clarity of influential factors and deriving forces, estimation of the volumetric irrigation demand using biophysical models is prohibitively difficult. Data-driven models have proven their ability to predict geophysical and hydrological phenomena with only a handful of influential input variables; however, the lack of reliable input data in most agricultural regions of the world hinders the effectiveness of these approaches. Attempting to estimate the irrigation water demand, we first analyze the correlation of potential influencing variables with irrigation water. We develop machine learning models to predict California’s annual, county-level irrigation water demand based on the statistical analysis findings over an 18-year time span. Input variables are different combinations of deriving meteorological forces, geographical characteristics, cropped area, and crop category. After testing various regression machine learning approaches, the result shows that Gaussian process regression produces the best results. Our findings suggest that irrigated cropped area, air temperature, and vapor pressure deficit are the most significant variables in predicting irrigation water demand. This research also shows that Gaussian process regression can predict irrigation water demand with high accuracy (R2 higher than 0.97 and RMSE as low as 0.06 km3) with different input variable combinations. An accurate estimation of irrigation water use of various crop categories and areas can assist decision-making processes and improve water management strategies. The proposed model can help water policy makers evaluate climatological and agricultural scenarios and hence be used as a decision support tool for agricultural water management at a regional scale.

Dynamic linkages between climatic variables and agriculture production in Malaysia: a generalized method of moments approach

Climate change continues to pose a threat to the agricultural sectors worldwide, jeopardizing food and nutritional security, which is a critical component of the sustainable development agenda. Consequently, this study attempts to examine the impact of climatic variables (CO₂ emissions, energy resources, rainfall, temperature, fossil fuel consumption, and humidity) on agricultural production of rice, cereals, vegetables, coffee, and agriculture value added (as a percentage of GDP) in the Malaysian context. To this end, this study applied a generalized method of moments (GMM) estimator on the data obtained from the metrological station Malaysia, Department of Statistics Malaysia and World Development Indicators (WDI) spanning the period 1985-2016. The results revealed that temperature and energy consumption negatively and significantly affect rice and vegetable production, while the negative effect of rainfall, temperature, fossil fuel consumption, and humidity on cereal production is insignificant. The results also confirmed that CO₂ emissions have a negative and significant impact on coffee production. Likewise, temperature, energy consumption, and fossil fuel consumption exhibit a negative and significant influence on agriculture value added. These observations evidenced the adverse effect of climate change on various agricultural products in Malaysia. Therefore, in order to ensure robust and sustainable agricultural output in Malaysia, policymakers as well as environmentalists should work together to formulate appropriate adaptation strategies.

Creation and Use of Highly Adaptive Productive and Technological Red Currant Genotypes to Improve the Assortment and Introduction into Different Ecological and Geographical Zones

Global climate change with the cyclicity of natural and climatic processes in the growing season of berry plants, causes weakening at the defense system to (a)biotic stressors, which actualize the need for accelerated cultivar-improving breeding. A new hybrid red currant material was obtained and studied by the method of interspecific hybridization. Correlation analysis was used to assess the relationship between adaptively significant and economical and biological traits. To assess intergenotypic variability, hierarchical clustering was used according to the studied features, which allowed combining three standard methods of multidimensional data analysis. Genotypes adapted to different stressors were identified. The genotypes 271-58-24, 44-5-2, 261-65-19, and ‘Jonkheer van Tets’ were found to have a higher ratio of bound water to free water as compared with the others. Moreover, the genotypes of 271-58-24, 261-65-19, 77-1-47, and ‘Jonkheer van Tets’ were found to have less cold damage during the cold periods. The two most productive genotypes were found to be the genotypes 44-5-2, 143-23-35, and 1426-21-80. A dependence of yield on the beginning of differentiation of flower buds, which led to the abundance of flower inflorescences, was revealed. Rapid restoration of leaf hydration ensured successful adaptation of genotypes to the “temperature shock” of the growing season. The genotypes 271-58-24 and ‘Jonkheer van Tets’ were then observed to be far from the test traits and none of these traits were observed to characterize these two genotypes. The genotypes of 261-65-19 and 77-1-47 were then observed to be characterized by their high stability to Cecidophyopsis ribis scores. Genotypes 261-65-19 and 271-58-24, obtained with the participation of ‘Jonkheer van Tets’ as the maternal form, showed sufficient resistance to Pseudopeziza ribis and Cecidophyopsis ribis. Overall results suggested that the hydration recovery of red currant plants is significantly important for a yield improvement. A new cultivar ’Podarok Pobediteliam (genotype 44-5-2) was obtained that meets the requirements of intensive gardening and is characterized by high adaptability, productivity, and technological effectiveness.

Impacts of large-scale teleconnection indices on chill accumulation for specialty crops in California

Although the impacts of teleconnection indices on climate metrics such as precipitation and temperature in California have been widely studied, less attention has been given to the impact on integrated climate indices such as chill accumulation. This study investigates the linkages between large-scale teleconnections and winter chill accumulation for specialty crops in California, which may enable more effective and dynamic adaptation to in-season climate variability. Three large-scale teleconnection indices were selected: Oceanic Nino Index (ONI), Pacific-North American teleconnection pattern (PNA), and Pacific Decadal Oscillation (PDO) index to assess their effects on chill accumulation. The Chill Hours Model and Dynamic Model are adopted to calculate chill accumulation in Chill Hours (CH) and Chill Portions (CP) from November to January. Three major crop-producing regions, including the Central Coast, Sacramento Valley, and San Joaquin Valley, are used as the focused regions. Our results suggest CP generally has a stronger response to teleconnection patterns than CH in California. The correlations between chill accumulation and teleconnections are generally weaker during the summer than other seasons, and significant correlation can be observed 2-10 months before the start of the chill accumulation period. Among the three teleconnection indices, ONI is most weakly correlated to chill accumulation in focused regions, while PDO shows the strongest positive correlation and explains up to 39% variability of CP. PNA presents the most widespread negative correlation with chill accumulation. When aggregated to different teleconnection modes, +3.6 above-average CP is expected during ONI positive mode; +2.3 above-average CP is expected during PDO positive mode, while +2.1 above-average CP is expected during PNA negative mode. This study provides insights on early-season chill prediction and feasible management and adaptation strategies, and the methodology presented here can be used to develop decision support tools of risk control for agricultural producers and policymakers.

Hybrid coffee cultivars may enhance agroecosystem resilience to climate change

Anthropogenic climate change is predicted to cause shifts in temperature and precipitation patterns that will be detrimental for global agriculture. Developing comprehensive strategies for building climate resilient agroecosystems is critical for maintaining future crop production. Arabica coffee (Coffea arabica) is highly sensitive to the quantity and timing of precipitation, so alterations in precipitation patterns that are predicted under climate change are likely to be a major challenge for maintaining coffee agroecosystems. We assessed cultivar selection as a potential component of more resilient coffee agroecosystems by evaluating water stress responses among five Arabica coffee cultivars (clonal hybrids H10 and H1 and seedling lines Catuai 44, Catuai, and Villa Sarchi) using a precipitation reduction experiment in the highlands of Tarrazú, Costa Rica. During the first harvest (eighteen months after planting), plants under the rainout treatment had 211 % greater total fruit weight and over 50 % greater biomass than under the control treatment, potentially due to protection from unusually high rainfall during this period of our experiment. At the second harvest (30 months after planting), after a year of more typical rainfall, plants under rainout still produced 66 % more fruit by weight than under control. The magnitude of the responses varied among cultivars where, at the first harvest, H10 and H1 had approximately 92 % and 81 % greater fruit production and 18 % and 22 % greater biomass, respectively, and at the second harvest H10 had 60 % more fruit production than the overall average. Thus, our findings suggest that the hybrid lines H10 and H1 are more resilient than the other cultivars to the stress of high soil moisture. Overall, our results indicate that stress due to higher than average rainfall could impair coffee plant growth and production, and that cultivar selection is likely to be an important tool for maintaining the viability of coffee production, and the resilience of global agroecosystems more generally, under climate change.

Prunus Hexokinase 3 genes alter primary C-metabolism and promote drought and salt stress tolerance in Arabidopsis transgenic plants

Hexokinases (HXKs) and fructokinases (FRKs) are the only two families of enzymes in plants that have been identified as able to phosphorylate Glucose (Glc) and Fructose (Fru). Glc can only be phosphorylated in plants by HXKs, while Fru can be phosphorylated by either HXKs or FRKs. The various subcellular localizations of HXKs in plants indicate that they are involved in diverse functions, including anther dehiscence and pollen germination, stomatal closure in response to sugar levels, stomatal aperture and reducing transpiration. Its association with modulating programmed cell death, and responses to oxidative stress and pathogen infection (abiotic and biotic stresses) also have been reported. To extend our understanding about the function of HXK-like genes in the response of Prunus rootstocks to abiotic stress, we performed a detailed bioinformatic and functional analysis of hexokinase 3-like genes (HXK3s) from two Prunus rootstock genotypes, 'M.2624' (Prunus cerasifera Ehrh × P. munsoniana W.Wight & Hedrick) and 'M.F12/1' (P. avium L.), which are tolerant and sensitive to hypoxia stress, respectively. A previous large-scale transcriptome sequencing of roots of these rootstocks, showed that this HXK3-like gene that was highly induced in the tolerant genotype under hypoxia conditions. In silico analysis of gene promoters from M.2624 and M.F12/1 genotypes revealed regulatory elements that could explain differential transcriptional profiles of HXK3 genes. Subcellular localization was determinates by both bioinformatic prediction and expression of their protein fused to the green fluorescent protein (GFP) in protoplasts and transgenic plants of Arabidopsis. Both approaches showed that they are expressed in plastids. Metabolomics analysis of Arabidopsis plants ectopically expressing Prunus HXK3 genes revealed that content of several metabolites including phosphorylated sugars (G6P), starch and some metabolites associated with the TCA cycle were affected. These transgenic Arabidopsis plants showed improved tolerance to salt and drought stress under growth chamber conditions. Our results suggest that Prunus HXK3 is a potential candidate for enhancing tolerance to salt and drought stresses in stone fruit trees and other plants.