Bottlenecks and opportunities in field-based high-throughput phenotyping for heat and drought stress

Leveraging Multiomics Insights and Exploiting Wild Relatives' Potential for Drought and Heat Tolerance in Maize

Climate change, particularly drought and heat stress, may slash agricultural productivity by 25.7% by 2080, with maize being the hardest hit. Therefore, unraveling the molecular nature of plant responses to these stressors is vital for the development of climate-smart maize. This manuscript's primary objective was to examine how maize plants respond to these stresses, both individually and in combination. Additionally, the paper delved into harnessing the potential of maize wild relatives as a valuable genetic resource and leveraging AI-based technologies to boost maize resilience. The role of multiomics approaches particularly genomics and transcriptomics in dissecting the genetic basis of stress tolerance was also highlighted. The way forward was proposed to utilize a bunch of information obtained through omics technologies by an interdisciplinary state-of-the-art forward-looking big-data, cyberagriculture system, and AI-based approach to orchestrate the development of climate resilient maize genotypes.

Drought and heat stress: insights into tolerance mechanisms and breeding strategies for pigeonpea improvement

MAIN CONCLUSION

Pigeonpea has potential to foster sustainable agriculture and resilience in evolving climate change; understanding bio-physiological and molecular mechanisms of heat and drought stress tolerance is imperative to developing resilience cultivars. Pigeonpea is an important legume crop that has potential resilience in the face of evolving climate scenarios. However, compared to other legumes, there has been limited research on abiotic stress tolerance in pigeonpea, particularly towards drought stress (DS) and heat stress (HS). To address this gap, this review delves into the genetic, physiological, and molecular mechanisms that govern pigeonpea's response to DS and HS. It emphasizes the need to understand how this crop combats these stresses and exhibits different types of tolerance and adaptation mechanisms through component traits. The current article provides a comprehensive overview of the complex interplay of factors contributing to the resilience of pigeonpea under adverse environmental conditions. Furthermore, the review synthesizes information on major breeding techniques, encompassing both conventional methods and modern molecular omics-assisted tools and techniques. It highlights the potential of genomics and phenomics tools and their pivotal role in enhancing adaptability and resilience in pigeonpea. Despite the progress made in genomics, phenomics and big data analytics, the complexity of drought and heat tolerance in pigeonpea necessitate continuous exploration at multi-omic levels. High-throughput phenotyping (HTP) is crucial for gaining insights into perplexed interactions among genotype, environment, and management practices (GxExM). Thus, integration of advanced technologies in breeding programs is critical for developing pigeonpea varieties that can withstand the challenges posed by climate change. This review is expected to serve as a valuable resource for researchers, providing a deeper understanding of the mechanisms underlying abiotic stress tolerance in pigeonpea and offering insights into modern breeding strategies that can contribute to the development of resilient varieties suited for changing environmental conditions.

Deciphering temporal growth patterns in maize: integrative modeling of phenotype dynamics and underlying genomic variations

Quantifying the temporal or longitudinal growth dynamics of crops in diverse environmental conditions is crucial for understanding plant development, requiring further modeling techniques. In this study, we analyzed the growth patterns of two different maize (Zea mays L.) populations using high-throughput phenotyping with a maize population consisting of 515 recombinant inbred lines (RILs) grown in Texas and a hybrid population containing 1090 hybrids grown in Missouri. Two models, Gaussian peak and functional principal component analysis (FPCA), were employed to study the Normalized Green-Red Difference Index (NGRDI) scores. The Gaussian peak model showed strong correlations (c. 0.94 for RILs and c. 0.97 for hybrids) between modeled and non-modeled temporal trajectories. Functional principal component analysis differentiated NGRDI trajectories in RILs under different conditions, capturing substantial variability (75%, 20%, and 5% for RILs; 88% and 12% for hybrids). By comparing these models with conventional BLUP values, common quantitative trait loci (QTLs) were identified, containing candidate genes of brd1, pin11, zcn8 and rap2. The harmony between these loci's additive effects and growing degree days, as well as the differentiation of RIL haplotypes across growth stages, underscores the significant interplay of these loci in driving plant development. These findings contribute to advancing understanding of plant-environment interactions and have implications for crop improvement strategies.

Hybrid Rice Production: A Worldwide Review of Floral Traits and Breeding Technology, with Special Emphasis on China

Rice is an important diet source for the majority of the world's population, and meeting the growing need for rice requires significant improvements at the production level. Hybrid rice production has been a significant breakthrough in this regard, and the floral traits play a major role in the development of hybrid rice. In grass species, rice has structural units called florets and spikelets and contains different floret organs such as lemma, palea, style length, anther, and stigma exsertion. These floral organs are crucial in enhancing rice production and uplifting rice cultivation at a broader level. Recent advances in breeding techniques also provide knowledge about different floral organs and how they can be improved by using biotechnological techniques for better production of rice. The rice flower holds immense significance and is the primary focal point for researchers working on rice molecular biology. Furthermore, the unique genetics of rice play a significant role in maintaining its floral structure. However, to improve rice varieties further, we need to identify the genomic regions through mapping of QTLs (quantitative trait loci) or by using GWAS (genome-wide association studies) and their validation should be performed by developing user-friendly molecular markers, such as Kompetitive allele-specific PCR (KASP). This review outlines the role of different floral traits and the benefits of using modern biotechnological approaches to improve hybrid rice production. It focuses on how floral traits are interrelated and their possible contribution to hybrid rice production to satisfy future rice demand. We discuss the significance of different floral traits, techniques, and breeding approaches in hybrid rice production. We provide a historical perspective of hybrid rice production and its current status and outline the challenges and opportunities in this field.

The potential of UAV and very high-resolution satellite imagery for yellow and stem rust detection and phenotyping in Ethiopia

Very high (spatial and temporal) resolution satellite (VHRS) and high-resolution unmanned aerial vehicle (UAV) imagery provides the opportunity to develop new crop disease detection methods at early growth stages with utility for early warning systems. The capability of multispectral UAV, SkySat and Pleiades imagery as a high throughput phenotyping (HTP) and rapid disease detection tool for wheat rusts is assessed. In a randomized trial with and without fungicide control, six bread wheat varieties with differing rust resistance were monitored using UAV and VHRS. In total, 18 spectral features served as predictors for stem and yellow rust disease progression and associated yield loss. Several spectral features demonstrated strong predictive power for the detection of combined wheat rust diseases and the estimation of varieties' response to disease stress and grain yield. Visible spectral (VIS) bands (Green, Red) were more useful at booting, shifting to VIS-NIR (near-infrared) vegetation indices (e.g., NDVI, RVI) at heading. The top-performing spectral features for disease progression and grain yield were the Red band and UAV-derived RVI and NDVI. Our findings provide valuable insight into the upscaling capability of multispectral sensors for disease detection, demonstrating the possibility of upscaling disease detection from plot to regional scales at early growth stages.

Multitraits evaluation of a Solanum pennellii introgression tomato line challenged by combined abiotic stress

Rising daily temperatures and water shortage are two of the major concerns in agriculture. In this work, we analysed the tolerance traits in a tomato line carrying a small region of the Solanum pennellii wild genome (IL12-4-SL) when grown under prolonged conditions of single and combined high temperature and water stress. When exposed to stress, IL12-4-SL showed higher heat tolerance than the cultivated line M82 at morphological, physiological, and biochemical levels. Moreover, under stress IL12-4-SL produced more flowers than M82, also characterized by higher pollen viability. In both lines, water stress negatively affected photosynthesis more than heat alone, whereas the combined stress did not further exacerbate the negative impacts of drought on this trait. Despite an observed decrease in carbon fixation, the quantum yield of PSII linear electron transport in IL12-4-SL was not affected by stress, thereby indicating that photochemical processes other than CO₂ fixation acted to maintain the electron chain in oxidized state and prevent photodamage. The ability of IL12-4-SL to tolerate abiotic stress was also related to the intrinsic ability of this line to accumulate ascorbic acid. The data collected in this study clearly indicate improved tolerance to single and combined abiotic stress for IL12-4-SL, making this line a promising one for cultivation in a climate scenario characterized by frequent and long-lasting heatwaves and low rainfall.

Monitoring Drought Stress in Common Bean Using Chlorophyll Fluorescence and Multispectral Imaging

Drought is a significant constraint in bean production. In this study, we used high-throughput phenotyping methods (chlorophyll fluorescence imaging, multispectral imaging, 3D multispectral scanning) to monitor the development of drought-induced morphological and physiological symptoms at an early stage of development of the common bean. This study aimed to select the plant phenotypic traits which were most sensitive to drought. Plants were grown in an irrigated control (C) and under three drought treatments: D70, D50, and D30 (irrigated with 70, 50, and 30 mL distilled water, respectively). Measurements were performed on five consecutive days, starting on the first day after the onset of treatments (1 DAT-5 DAT), with an additional measurement taken on the eighth day (8 DAT) after the onset of treatments. Earliest detected changes were found at 3 DAT when compared to the control. D30 caused a decrease in leaf area index (of 40%), total leaf area (28%), reflectance in specific green (13%), saturation (9%), and green leaf index (9%), and an increase in the anthocyanin index (23%) and reflectance in blue (7%). The selected phenotypic traits could be used to monitor drought stress and to screen for tolerant genotypes in breeding programs.

The era of cultivating smart rice with high light efficiency and heat tolerance has come of age

How to improve the yield of crops has always been the focus of breeding research. Due to the population growth and global climate change, the demand for food has increased sharply, which has brought great challenges to agricultural production. In order to make up for the limitation of global cultivated land area, it is necessary to further improve the output of crops. Photosynthesis is the main source of plant assimilate accumulation, which has a profound impact on the formation of its yield. This review focuses on the cultivation of high light efficiency plants, introduces the main technical means and research progress in improving the photosynthetic efficiency of plants, and discusses the main problems and difficulties faced by the cultivation of high light efficiency plants. At the same time, in view of the frequent occurrence of high-temperature disasters caused by global warming, which seriously threatened plant normal production, we reviewed the response mechanism of plants to heat stress, introduced the methods and strategies of how to cultivate heat tolerant crops, especially rice, and briefly reviewed the progress of heat tolerant research at present. Given big progress in these area, the era of cultivating smart rice with high light efficiency and heat tolerance has come of age.

Crop breeding for a changing climate in the Pannonian region: towards integration of modern phenotyping tools

The Pannonian Plain, as the most productive region of Southeast Europe, has a long tradition of agronomic production as well as agronomic research and plant breeding. Many research institutions from the agri-food sector of this region have a significant impact on agriculture. Their well-developed and fruitful breeding programmes resulted in productive crop varieties highly adapted to the specific regional environmental conditions. Rapid climatic changes that occurred during the last decades led to even more investigations of complex interactions between plants and their environments and the creation of climate-smart and resilient crops. Plant phenotyping is an essential part of botanical, biological, agronomic, physiological, biochemical, genetic, and other omics approaches. Phenotyping tools and applied methods differ among these disciplines, but all of them are used to evaluate and measure complex traits related to growth, yield, quality, and adaptation to different environmental stresses (biotic and abiotic). During almost a century-long period of plant breeding in the Pannonian region, plant phenotyping methods have changed, from simple measurements in the field to modern plant phenotyping and high-throughput non-invasive and digital technologies. In this review, we present a short historical background and the most recent developments in the field of plant phenotyping, as well as the results accomplished so far in Croatia, Hungary, and Serbia. Current status and perspectives for further simultaneous regional development and modernization of plant phenotyping are also discussed.

Phenotyping to dissect the biostimulant action of a protein hydrolysate in tomato plants under combined abiotic stress

Drought and heat stresses are the main constrains to agricultural crop production worldwide. Precise and efficient phenotyping is essential to understand the complexity of plant responses to abiotic stresses and to identify the best management strategies to increase plant tolerance. In the present study, two phenotyping platforms were used to investigate the effects of a protein hydrolysate-based biostimulant on the physiological response of two tomato genotypes ('E42' and 'LA3120') subjected to heat, drought, or combined stress. The free amino acids in the biostimulant, or other molecules, stimulated growth in treated plants subjected to combined stress, probably promoting endogenous phytohormonal biosynthesis. Moreover, biostimulant application increased the net photosynthetic rate and maximal efficiency of PSII photochemistry under drought, possibly related to the presence of glycine betaine and aspartic acid in the protein hydrolysate. Increased antioxidant content and a decreased accumulation of hydrogen peroxide, proline, and soluble sugars in treated plants under drought and combined stress further demonstrated that the biostimulant application mitigated the negative effects of abiotic stresses. Generally, the response to biostimulant in plants had a genotype-dependent effect, with 'E42' showing a stronger response to protein hydrolysate application than 'LA3120'. Altogether, in this study a fine and multilevel phenotyping revealed increased plant performances under water-limited conditions and elevated temperatures induced by a protein hydrolysate, thus highlighting the great potential biostimulants have in improving plant resilience to abiotic stresses.

Response and tolerance mechanism of food crops under high temperature stress: a review

High temperature stress events are critical factors inhibiting crop yield. Meanwhile, world population is growing very rapidly and will be reached up to 9 billion by 2050. To feed increasing world population, it is challenging task to increase about 70% global food productions. Food crops have significant contribution toward global food demand and food security. However, consequences from increasing heat stress events are demolishing their abilities to survive and sustain yield when subjected to extreme high temperature stress. Therefore, there is dire need to better understand response and tolerance mechanism of food crops following exposure to heat stress. Here, we aimed to provide recent update on impact of high temperature stress on crop yield of food crops, pollination, pollinators, and novel strategies for improving tolerance of food crop under high temperature stress. Importantly, development of heat-resistant transgenic food crops can grant food security through transformation of superior genes into current germplasm, which are associated with various signaling pathways as well as epigenetic regulation in response to extreme high temperature stress.

Harnessing Chlorophyll Fluorescence for Phenotyping Analysis of Wild and Cultivated Tomato for High Photochemical Efficiency under Water Deficit for Climate Change Resilience

Fluctuations of the weather conditions, due to global climate change, greatly influence plant growth and development, eventually affecting crop yield and quality, but also plant survival. Since water shortage is one of the key risks for the future of agriculture, exploring the capability of crop species to grow with limited water is therefore fundamental. By using chlorophyll fluorescence analysis, we evaluated the responses of wild tomato accession Solanum pennellii LA0716, Solanum lycopersicum cv. Μ82, the introgression line IL12-4 (from cv. M82 Χ LA0716), and the Greek tomato cultivars cv. Santorini and cv. Zakinthos, to moderate drought stress (MoDS) and severe drought stress (SDS), in order to identify the minimum irrigation level for efficient photosynthetic performance. Agronomic traits (plant height, number of leaves and root/shoot biomass), relative water content (RWC), and lipid peroxidation, were also measured. Under almost 50% deficit irrigation, S. pennellii exhibited an enhanced photosynthetic function by displaying a hormetic response of electron transport rate (ETR), due to an increased fraction of open reaction centers, it is suggested to be activated by the low increase of reactive oxygen species (ROS). A low increase of ROS is regarded to be beneficial by stimulating defense responses and also triggering a more oxidized redox state of quinone A (QA), corresponding in S. pennellii under 50% deficit irrigation, to the lowest stomatal opening, resulting in reduction of water loss. Solanumpennellii was the most tolerant to drought, as it was expected, and could manage to have an adequate photochemical function with almost 30% water regime of well-watered plants. With 50% deficit irrigation, cv. Μ82 and cv. Santorini did not show any difference in photochemical efficiency to control plants and are recommended to be cultivated under deficit irrigation as an effective strategy to enhance agricultural sustainability under a global climate change. We conclude that instead of the previously used Fv/Fm ratio, the redox state of QA, as it can be estimated by the chlorophyll fluorescence parameter 1 - qL, is a better indicator to evaluate photosynthetic efficiency and select drought tolerant cultivars under deficit irrigation.

Alternative models for transgenerational epigenetic inheritance: Molecular psychiatry beyond mice and man

Mental illness remains the greatest chronic health burden globally with few in-roads having been made despite significant advances in genomic knowledge in recent decades. The field of psychiatry is constantly challenged to bring new approaches and tools to address and treat the needs of vulnerable individuals and subpopulations, and that has to be supported by a continuous growth in knowledge. The majority of neuropsychiatric symptoms reflect complex gene-environment interactions, with epigenetics bridging the gap between genetic susceptibility and environmental stressors that trigger disease onset and drive the advancement of symptoms. It has more recently been demonstrated in preclinical models that epigenetics underpins the transgenerational inheritance of stress-related behavioural phenotypes in both paternal and maternal lineages, providing further supporting evidence for heritability in humans. However, unbiased prospective studies of this nature are practically impossible to conduct in humans so preclinical models remain our best option for researching the molecular pathophysiologies underlying many neuropsychiatric conditions. While rodents will remain the dominant model system for preclinical studies (especially for addressing complex behavioural phenotypes), there is scope to expand current research of the molecular and epigenetic pathologies by using invertebrate models. Here, we will discuss the utility and advantages of two alternative model organisms–Caenorhabditis elegans and Drosophila melanogaster–and summarise the compelling insights of the epigenetic regulation of transgenerational inheritance that are potentially relevant to human psychiatry.

Scaling up high-throughput phenotyping for abiotic stress selection in the field

High-throughput phenotyping (HTP) is in its infancy for deployment in large-scale breeding programmes. With the ability to measure correlated traits associated with physiological ideotypes, in-field phenotyping methods are available for screening of abiotic stress responses. As cropping environments become more hostile and unpredictable due to the effects of climate change, the need to characterise variability across spatial and temporal scales will become increasingly important. The sensor technologies that have enabled HTP from macroscopic through to satellite sensors may also be utilised here to complement spatial characterisation using envirotyping, which can improve estimations of genotypic performance across environments by better accounting for variation at the plot, trial and inter-trial levels. Climate change is leading to increased variation at all physical and temporal scales in the cropping environment. Maintaining yield stability under circumstances with greater levels of abiotic stress while capitalising upon yield potential in good years, requires approaches to plant breeding that target the physiological limitations to crop performance in specific environments. This requires dynamic modelling of conditions within target populations of environments, GxExM predictions, clustering of environments so breeding trajectories can be defined, and the development of screens that enable selection for genetic gain to occur. High-throughput phenotyping (HTP), combined with related technologies used for envirotyping, can help to address these challenges. Non-destructive analysis of the morphological, biochemical and physiological qualities of plant canopies using HTP has great potential to complement whole-genome selection, which is becoming increasingly common in breeding programmes. A range of novel analytic techniques, such as machine learning and deep learning, combined with a widening range of sensors, allow rapid assessment of large breeding populations that are repeatable and objective. Secondary traits underlying radiation use efficiency and water use efficiency can be screened with HTP for selection at the early stages of a breeding programme. HTP and envirotyping technologies can also characterise spatial variability at trial and within-plot levels, which can be used to correct for spatial variations that confound measurements of genotypic values. This review explores HTP for abiotic stress selection through a physiological trait lens and additionally investigates the use of envirotyping and EC to characterise spatial variability at all physical scales in METs.