List of major and stable QTL for heat tolerance-related traits in wheat.
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It is extensively grown in Asia particularly in China and India. In India its production is enhances after the green revolution of late 1960s followed by another green evolution during 1980s. During these two green revolutions, the rate of annual growth in wheat production globally was ~3%, but in recent years it is declined to <0.9% due to appearance of new biotic and abiotic stresses. Although currently, the global wheat production has been able to meet the current demand and consumption, but we will have to enhance production and achieve the targets of at least ~858 Mt to meet the demand in 2050, as against current global production of 763 Mt. It comprises amounts to at least ~15% desired increase in global wheat production (1.5% annual increase) during the next three decades to feed the global human population, which is estimated to reach ~9.7 billion in 2050 (
Abiotic stress adaptive mechanism and their associated traits in plants heat stress tolerance.
High temperature-induced heat stress is expressed as the rise in air temperature beyond a threshold level for a particular period which is sufficient to cause injury or irremediable damage of crop plants in general [3]. The heat stress situation is become more intense when soil temperature increases due to increase in air temperature associated with decline in soil moisture. It negatively affects the yield attributing traits and ultimately results in reduction in wheat productivity. Some indicators of heat stress effects in wheat are illustrated in Figure 2. Wheat is very sensitive to heat stress particularly in some physiological growth stages. It has been estimated that reduction in global wheat yield falls by 6% for each 1°C of further temperature rise [4]. The low latitudes showed a distinct increase in simulated yield variability with higher temperature than that observed at high latitudes. This greater relative yield decline was due to the higher reference temperature [5]. The effects of heat stress on plants are very complex resulting in alteration of growth and development, changes in physiological functions, and reduced grain formation and yield.
Major effects of heat stress on plants growth and development. Pn, Rs, and Ci indicate photosynthesis, stomatal conductance, and intercellular CO2 concentration respectively.
Heat stress leads to changes in plant water relations, reduction of photosynthetic capacity, decreases of metabolic activities and changes of hormones, production of oxidative reactive species, promotion of ethylene production, reduction of pollen tube development, and increases of pollen mortality [1] in wheat. During the period from 1880 to 2012, the Earth’s system warmed by 0.85°C [6]. This warming period will be continue and is predicted to rise between the range of 1.5–4.0°C in the future [7]. The changes in climatic factors like temperature, precipitation, CO2, weather variability, and soil moisture deficit would have positive or negative effects on crop system which will appears in its production level. The deleterious impacts of climate change on crop production are challenging the food security of the world and it is predicted that sustaining wheat production will be impacted more by increasing temperature. High temperature affects crops in different ways including poor germination and plant establishment, reduced photosynthesis, leaf senescence, decreased pollen viability, and consequently production of less grain with smaller grain size. Degree of such effect varies depending on the crops, cultivars, phenological stages, sowing dates and management practices. Some other adaptation measures are related to surface cooling by irrigation, antioxidants defense [8] and osmoprotectants [3, 5] minimizes the effects of heat stress. However, development of heat-tolerant wheat varieties and generation of improved pre-breeding materials for any breeding program in future is crucial in meeting the food security [9]. Proteomic and transcriptomic data are important to identifying genes and proteins that respond to environment, and affects yield and quality of wheat.
Breeding is a strategy for genetic manipulation of crop and its adaptation response under changing environment. Therefore, it requires the evaluation of genetic diversity of existing germplasm for the selection and induction of stress inducible genes/QTLs of genetic resources for developing new varieties in the production systems.
Recent advances in molecular science play an important role to understand the complexity of stress response mechanisms under heat stress conditions and emphasized on the knowledge of molecular pathways and protective mechanisms to breed heat stress tolerant plants. Heat tolerance is obviously a polygenic trait, and the molecular techniques also help in analyzing the genetic basis of plant thermo tolerance. QTL mapping and subsequent marker-assisted selection made it possible to better understanding the heat tolerance in plants [10]. Recently several QTLs for different yield component traits have been identified which can be used for developing heat tolerance in wheat. For example, QTLs for heat tolerance has been identified for grain weight and grain-filling duration, senescence-related traits and canopy temperature. Besides others recognized QTLs present on chromosomes 2B, 5B and 4A in wheat under heat stress conditions [11]. The electrolyte leakage is an indication of reduced cell membrane thermo stability (CMT) which reflects the performance of wheat genotypes under heat shock. Genotypes generating heat shock proteins (HSPs) can withstand heat stress as they protect proteins from heat-induced damage. It has been also suggested that the abundance of small heat shock protein and superoxide dismutase during milky-dough stage plays a vital role in the biosynthesis of starch granule, and this will help to develop heat-tolerant wheat cultivars containing high grain quality. A large number major and stable QTLs were reported (Table 1), which included for agronomic traits and for physiological traits showing ≥20% phenotypic variances. These QTLs may prove useful for improvement of such traits using marker assisted selection (MAS).
Sl. no. | Traits/QTL | Phenotypic variance (%) | Linked marker (position in cM) | Physical position (Mbp)d | References |
---|---|---|---|---|---|
I. Agronomic traits | |||||
1. Grain yield | |||||
a. Q .Yld.aww-3B-2 | 22 | XWPT8021-Xgwm0114B (190.7) | 802.3 | — | |
2. Thousand grain weight | |||||
a. Qtgw.iiwbr-2A | 23.7 | Xgwm12280.8 | (174.41) | — | |
b. QHthsitgw.bhu-7B | 20.3 | Xgwm1025–Xgwm745 (144.1) | ND | [12] | |
c. 2A (36.1)c | 224,948|F|0-9:T > A-9:T > A-kukri_c22235_1549 (21–24) | ND | [13, 14] | ||
3. Grain weight per spike | |||||
a. Qtgws.iiwbr-2A | 28.9 | Xgwm497.1 (41.61) | 684 | — | |
b. Qgws.iiwbr-2A | 19.9 | Xgwm122 (171.41) | 80.8 | — | |
4. Grain number per spike | |||||
a. Qlgns.iiwbr-2A | 23.16 | Xgwm372 (149.01) | 203.3 | — | |
b. Qgns.iiwbr-2A | 20.04 | Xgwm448 (166.51) | 154.4 | — | |
5. Kernel number per spike | |||||
a. QHknm.tam-2B | 21.6 | Xgwm111.2 (36.9) | 786.6 | [15] | |
6. Kernel weight per main spike | |||||
a. QHkwm.tam-3B | 19 | Xwmc527 (89.8) 540.2 | [15] | ||
b. QHkwm.tam-3B | 21.2 | Xwmc326 (123.6) | 778.7 | [15] | |
7. Single kernel weight of main spike | |||||
a. QHskm.tam-1A | 22.6 | Xcfa2129 (43.2) | 513.7 | [15] | |
b. QHskm.tam-2A | 21 | Xgwm356 (129.5) | 670.6 | [15] | |
II. Physiological traits | |||||
1. Grain filling duration | |||||
a. QHgfd.iiwbr-5A | 22 | X1079678|F|0 (107.5) | ND | [16] | |
b. QHthsigfd.bhu-2B | 20.2 | Xgwm935–Xgwm1273 (385.3) | ND | [12] | |
2. Ear emergence time | |||||
a. Q .Eet.aww-7A-2 | 39 | XPPDD1-XWPT0330 (35) | 63.5 | — | |
3. Canopy temperature: grain filling | |||||
a. Q .Ctgf.aww-3B | 21 | XWPT-8021–Xgwm0114B (192.7) | 802.3 | — | |
4. Canopy temperature depression | |||||
a. QHtctd.bhu-7B | 19.8 | Xgwm1025–Xgwm745 (144.1) | ND | [12] |
List of major and stable QTL for heat tolerance-related traits in wheat.
Genetic engineering and transgenic approaches can diminish the adverse effects of heat stress by improving heat tolerance mechanisms [17]. It involves the incorporation of genes for heat tolerance into the desired plants [18]. However, the complexity of the genomic pattern makes it difficult to research for genetic modification in wheat. Prolong exposes to heat stress leads to increases in production of protein synthesis elongation factor (EF-Tu) in chloroplast which is associated with heat tolerance in wheat. The constitutive expression of EF-Tu in transgenic wheat protected leaf proteins against thermal aggregation, reduced thylakoid membranes disruption, enhanced photosynthetic capability, and resisted pathogenic microbes infection [19], hence the wheat genotypes having more EF-Tu showed better tolerance to heat stress as compared to genotypes with less EF-Tu [20]. Recently, it have been found that many transcription factors (TFs) involved in various abiotic stresses and engineered to improve stress tolerance in crops [21].
Drought stress can be simply defined as a scarcity of water which leads to dramatic changes in morphological, biochemical, physiological, and molecular features [22]. All of these changes hamper plant growth and crop production. Negative impact of drought stress appears at any growth stage and level of adverse effects depends on stage specific stresses and local environment. Therefore, genotypes may be tested for their drought tolerance at different particular growth stages. Severity of drought induced damage on plants depending on plant genotype and growth stage. Some genotypes may show tolerance to drought at germination or seedling stage, but these may be very sensitive to drought at the flowering stage or vice versa. Globally, more than 50% of the wheat cultivated land is exposed to periodic drought which causes losses up to 9–10% in production. Furthermore, decrease in precipitation and increasing evaporation as a consequence of global warming may expected to increase in frequency of drought and its severity in the future. Therefore, understanding the drought induced damages in wheat plants and approaches to improve drought tolerance is crucial to increase wheat productivity. Drought stress imposes damaging effects on several plants physiological processes occur in its different growth stages such as germination, vegetative growth, reproductive, and maturity. Under such stress conditions plant restricts the photosynthesis, respiration, transpiration, uptake and transportation of water and nutrient and translocation of assimilates. Drought stress damages the cell membrane structure, disorganization of ultra-structural cellular components and disruption of its properties, enzyme activities and anion and cationic imbalance are some of the major reasons for disturbing plant physiological processes. Drought stress usually leads to the production of reactive oxygen species (ROS). Hydrogen peroxide (H2O2), superoxide (O2−), singlet oxygen (1O2), and hydroxyl radicals (OH−) are the most common species which are generated due to iron-catalyzed Fenton reaction due to the activities of lipoxygenases, peroxidases (POX), NADPH oxidase, and xanthine oxidase. The ROS in any form causes substantial damage to cell components and can cause cell death [23]. Plants have a very much evolved antioxidant defense system to rummage and keep up a reasonable degree of ROS to keep cells from oxidative harm. Under cell antioxidant defense system, it have some nonenzymatic antioxidants (ascorbic acid, AsA; glutathione, GSH; phenolic compounds; alkaloids; non protein amino acids; and α-tocopherols) and some antioxidant enzymes (super oxide dismutase, SOD; catalase, CAT; ascorbate peroxidase, APX; glutathione reductase, GR; monodehydroascorbate reductase, MDHAR; dehydroascorbate reductase, DHAR; glutathione peroxidase, GPX; and glutathione-S-transferase, GST) which work coordinately to eliminate ROS in an efficient way. Biotechnological approaches also helpful in enhancing the antioxidant system to confer oxidative as well as abiotic stress tolerance. Performances of drought-affected plants are remarkably improved by exogenous application of osmolytes, hormones, antioxidants and signaling molecules.
Drought stress tolerance is a complex trait influenced by genetic with many quantitative trait loci (QTLs) and environmental factors. Genetic analyses of drought tolerance have been studied through the development of molecular markers and genome sequencing in wheat. Such analyses include several approaches, e.g., QTL-mapping, association-mapping, genome-wide analyses and expression analysis aim to identify QTL or gene-related traits for drought stress tolerance. Revealing the genetic basis underlying the drought tolerance in wheat requires a phenotypic and genetic variation of relevant traits in large populations with dense genetic maps. The genetic basis of drought tolerance is due to polygenic inheritance, where each gene has small effect with high GXE interaction, hence low-heritability. Furthermore, the genetic independence of drought tolerance at different developmental stages makes the detected QTL less useful in crop improvement. Therefore, several QTLs have been discovered for drought tolerance-related traits, but a limited number of QTLs are genetically characterized or cloned and incorporated in breeding programs. Identifying stable QTL with large-effect that controls many drought tolerances-related traits at different developmental stages would be a great effort for crop improvement, but has not been found.
Quantitative trait loci (QTL) are location from where some genes influence a phenotype of quantitatively inherited trait. Genetic variations of a crop can be clarified through QTL mapping (polygenes). Mapping of QTL allows the estimation of the places, quantity, level of effects for the phenotype, gene activity pattern and important genomic regions. Multi-environmental field conditions are commonly used to evaluate the genotype performance [24, 25] using a different type of bi-parental population, e.g., recombinant inbred line (RIL) population, doubled haploid (DH) population [26, 27] or advanced backcross [28]. Different DNA molecular markers have been used to genotype the populations and identify QTL [26, 29]. Recently, a high-density genetic SNP map [28] (SNP array or genotyping by sequencing (GBS)) have been used to genotype the population [27]. Numerous QTLs have been identified for grain yield on chromosomes one, three and six, grain number per spike on chromosome two, three and six and spikelet number for each spike on two, five and six. Such major QTL controlling grain yield can be utilized in marker-helped determination rearing for yield improvement under dry spell pressure. QTL studies using a biparental mapping population have also discovered the genetic factors of other physiological and adaptive traits (Table 2), e.g., leaf chlorophyll content, leaf waxiness and leaf rolling in wheat, transpiration efficiency, water-use efficiency, biomass, leaf area, and growth rate-related traits in wheat. Meta-QTL (MQTL) analysis on drought tolerance in wheat has revealed QTLs for, photosynthesis, soluble carbohydrates, water status, carbon isotope discrimination, canopy temperature, coleoptiles vigor and stay-green.
Traits | Chromosome | Reference |
---|---|---|
Grain yield | 1B, 1D, 3B, 4A, 6D, 7D | [30] |
Grain weight per spike | 1B, 1D | [31] |
Thousand grain weight | 1B, 1D, 2A, 2B, 3A, 3B,4A, 4D, 6A, 6D, 7B, 7D | [32] |
Grain number (m−2) | 1B, 5A, 5B, 7D | [33] |
Grain number per spike | 1A, 2A, 2B, 3A, 6B | [33, 34] |
Harvest index | 1B, 2D, 4BS, 5A | [32] |
Spike number per plant | 1A, 2A, 2B, 2D, 4B, 5A,7B | [32] |
Spikelet compactness | 1A, 1B, 2B, 5A, 5B, 6A,6B, 7A | [32] |
Spikelet number per spike | 1B, 1D, 2B, 3B, 4B, 5A, 6B, 7D | [32] |
Sterile spikelet number per spike | 7A | [32] |
Fertile spikelet spike per spike | 2A | [32] |
Spike length | 2B, 7A, 7B | [32] |
Biomass | 1B | [32] |
Shoot biomass | 4B | [35] |
Spike length | 2B, 7A, 7B | [32] |
Physiological traits | ||
Leaf area, growth rate, transpiration efficiency, water-use efficiency | 2A, 2D, 3A, 4B, 6A | [36] |
Stomatal density, index, aperture area, length; guard cell area and length | 2B, 4AS, 5AS, 7AL, 7BL;1BL, 4BS, 5BS, 7AS | — |
Stomatal conductance, net photosynthetic rate | 5A, 6B | [33] |
Root length | 2D, 4B, 5D, 6B | [35] |
Root biomass | 2D, 4BS | [35] |
Metabolite traits | ||
Abscisic acid (ABA) | 1B, 2A, 3A, 4D, 5A, 6D,7B | [37] |
Jasmonic acid (JA), salicylic acid (SA), ethylene | 6A | [38] |
The detected quantitative trait loci (QTLs) for agronomic, physiological and metabolite traits in wheat using bi-parental mapping populations.
QTL investigation is so basic to target characteristics and for doing this a couple of stages are required. Initially, phenotypic evaluation of reasonably huge population for markers which are polymorphic is required. Besides, genotyping of the population is noteworthy. Thirdly, there is a prerequisite for quantifiable examination to distinguish the loci that are influencing the target trait. Several studied has been done and recognized >1200 QTLs for various characteristics conveyed over every one of the 21 chromosomes engaged with dry season resilience. Most extreme number of QTLs has been accounted for agronomic attributes, trailed by physiological qualities and root characteristics. Among agronomic qualities, most extreme QTL are known for thousand grain weight (TGW) trailed by grain yield and different attributes recorded under dry season conditions just as should be expected conditions. Among physiological qualities, most extreme number of QTLs are accessible for SPAD/chlorophyll content (82 QTL) trailed by water-dissolvable starches (76 QTL), coleoptile length (68 QTL). Among the root characteristics, greatest number of QTL is known for root length. Just 70 of these detailed QTL are major (clarifying ~>20% PVE), and just 19 QTL (counting 14 QTL for agronomic qualities, 5 for physiological attributes) are steady QTL utilized for QTL examination. The root attributes display high QTL × environment interaction, which recommends non accessibility of stable QTL for these characteristics. Fourteen stable major QTL were accounted for five agronomic attributes, with phenotypic fluctuation for individual QTL extending from 19.60% (grain yield QTL qGYWD.3B.2) to 45.20% (1000-grain weight QTL on 3B). These QTL can be utilized for development of dry spell resistance utilizing marker assisted selection (MAS). Two of the five QTL for grain yield that respond to dry season/heat stress cover a specific Mega QTL; these two QTL are found one each on chromosomes 4A and 7A [39] in areas, which likewise harbor QTL for the accompanying 14 qualities, which add to seedling rise, grain yield and reception to dry spell conditions: (1) days to heading, (2) days to development, (3) remain green propensity, (4) biomass, (5) shelter temperature; (6) carbon isotope separation, (7) coleoptile energy, (8) grain filling, (9) plant stature, (10) portion number, (11) spike thickness, (12) 1000-bit weight, (13) water-solvent sugars and (14) grain yield. Two other QTL for kernel width/thickness proportion on chromosome 5A cover a MQTL on 5A which represent to QTL for plant stature, spike weight and TGW [39]. The four stable major QTL for dry spell resilience incorporate two QTL for grain yield and two QTL for kernel width/thickness proportion. In an ongoing report, after broad field tests directed under pressure conditions in India, Australia and Mexico, a fundamental impact yield QTL (QYld.aww-1B.2) was fine-mapped to 2.9-cM locale relating to 2.2-Mbp genomic area containing 39 predicted genes (Tura et al., 2020). This QTL could be exploited in wheat breeding. The QTL for TGW, which is a significant segment of grain yield and have high heritability as well as stability, can be exploited for development of grain yield under water stress. Four QTL for days to heading and days to maturity may likewise be exploited utilizing MAS. Five significant and stable QTL for three physiological characteristics (SPAD/chlorophyll content, stem save assembly and water-solvent starches) each clarified PV running from ~20 to ~60% (Table 3). These attributes add to grain filling/advancement and thus to grain yield. The markers related with QTL for these characteristics are additionally acceptable possibility for marker assisted selection (MAS).
Sl. no. | QTL/trait | PVE % | Linked marker (position in cM) | Physical position (Mbp) | References |
---|---|---|---|---|---|
I. Agronomic traits | |||||
1. Grain yield | |||||
a. qGYWD.3B.2 | 19.6 | Xgpw7774 (97.6) | 16.2 | — | |
b. 4A | 20 | Xwmc420 (90.4) | 538.2 | — | |
c. 4A-a | 23.9 | Xgwm397 (6) | 708.6 | [11] | |
d. Qyld.csdh.7AL | 20.0 | Xgwm332 (155.9) | 681.6 | [40] | |
e. 6D | 26.6 | 2,265,648|F|0-60:A>G-60:A>G-RAC875_c57371_238 (73) | ND | [14] | |
2. 1000 grain weight | |||||
a. 2A | 36.1 | 2,264,948|F|0-9:T > A-9:T > A-Kukri_c22235_1547 (21.0-24.0) | ND | [14] | |
b. 3B | 45.2 | Xbarc101 (86.1) | 34.3 | [41] | |
c. QTgw-7D-b | 21.9 | XC29-P13 (12.5) | ND | [42] | |
3. Days to heading | |||||
a. QDh-7D.b | 22.7 | XC29-P13 (12.5) | ND | [42] | |
b. QHd.idw-2A.2 | 32.2 | Xwmc177 (46.1) | 33.7 | [29] | |
c. 5D | 21.4 | 1,126,619|F|0-21:A > T-21:A > T-wsnp_Ex_c1278_2449191 (162) | ND | [43] | |
4. Kernel width/thickness ratio | |||||
a. qWTR-5A-1 | 33.09 | Xwmc74-Xgwm291 (61) | 702.5–698.1 | [44] | |
b. qWTR-5A-2 | 23.59 | Xgwm291-Xgwm410 (71) | 698.1 | — | |
5. Days to maturity | |||||
a. QDm-7D.b | 22.7 | X7D-acc/cat-10 (2.7) | ND | [29] | |
II. Physiological traits | |||||
1. Stem reserve mobilization | |||||
a. QSrm.ipk-2D | 42.2 | Xgwm249a (142) | 141.1 | [45] | |
b. QSrm.ipk-5D | 37.5 | Xfbb238b (19) | ND | [45] | |
c. QSrm.ipk-7D | 21 | Xfbb189b (338) | ND | [45] | |
2. Water-soluble carbohydrates | |||||
a. QWsc-c.aww-3A | 19 | Xwmc0388A (64.9) | 208 | — | |
3. SPAD/chlorophyll content | |||||
a. Qchl.ksu-3B | 59.1 | Xbarc68 (67.2) | 76.1 | [46] |
A list of major and stable QTL (PVE ranging from 19 to 59%) for agronomic and physiological traits identified under drought/water stress.
PVE shows phenotypic variation explained; c means position of linked flanking marker was given if either the second marker or its sequence was not available; ND explain the physical position of QTL could not be determined due to lack of linked marker sequence information.
As of late, genome-wide investigations fuse genome-wide association study (GWAS) and genomic selection (GS) has been used to grasp the inherited multifaceted nature and breed for drought tolerance. GWAS approaches can be utilized with huge quantities of SNPs that produce a high-thick guide in an enormous and various assortments that give an elective way to deal with distinguish explicit qualities while the GS can be utilized in both bi-parental and different populaces. A predetermined number of studies have concentrated on physiological attributes, e.g., leaf green region, leaf water substance and water-soluble carbohydrates with around 12 MTAs have been distinguished. Chromosome 1A was found to contain a significant genomic region for physiological attributes, for example, water-dissolvable starches. Recently, utilized the most recent wheat genome sequences to physically map the most consistent and significant genomic regions that related with numerous agronomic and physiological attributes under drought stress in wheat. For example, the physical region of 1A was as a highly significant region for grain weight, flag leaf area and flag leaf width.
Globally, over 20% of the cultivable land is influenced by salinity. Because of environmental change and anthropogenic exercises, the salt influenced region is tended to increase day by day. A saline soil is commonly characterized as one in which the electrical conductivity (EC) of the saturation extract in the root zone surpasses 4 dS m−1 (roughly 40 mM NaCl) at 25°C and has a exchangeable sodium of 15%. It has been assessed that overall 20% of all out developed and 33% of irrigated agricultural lands are influenced by high salinity. Salt affected soils currently constitute 6.74 million ha in various agro ecological regions, the zone is probably going to increment to 16.2 million ha by 2050. Abiotic stresses (including salinity) are responsible for more than 50% yield reduction [47]. In opposite, because of fast increment of worldwide population, food production ought to be expanded by over 70% by 2050 [48]. Wheat (Triticum spp.) positions first on the world’s grain production. Wheat is expended as staple food by over 36% of world population. Wheat gives almost 55% of the carbohydrates and 20% of the food calories consumed globally. The productivity of wheat is frequently unfavorably influenced by salt stress. The yield of wheat begins to decay at 6–8 dS m−1 [49].
In saline soil plant development is restrained by two reasons. To begin with, it decreases the plant’s capacity to take up water, and this prompts more slow development. This is the osmotic stress or water-deficiency impact of salinity. Second, it might enter the transpiration stream and in the end harm cells of leaves includes in the transpiration prompts further reducing development. This is the salt-specific or ion-excess effect of salinity. The two impacts give rise to a two-stage development response to salinity (Figure 3). The outline shows the development reaction to salt that is included step by step.
Schematic outline of the two-stage development reaction to salinity for genotypes that differ in the rate at which salt arrives at harmful levels in leaves. For annual species, the time scale is d or wk., depending upon species and salinity level. For perennial species, the timescale is months or yr. During stage 1, development of the two genotypes is decreased in light of the osmotic stress of the saline solution outside the roots. During stage 2, leaves in the more sensitive genotype die and decrease the photosynthetic limit of the plant. This applies an extra impact on development [50]. In the event that salt is included one stage, the development rate dives to zero or below and takes 1–24 h to recover to the new consistent rate, contingent upon the level of the osmotic shock [51].
Phase 1: The primary period of the development reaction results from the impact of salt present in the soil solution lessens leaf development and less significantly, root development [50]. The cell and metabolic processes included are in common to dry season influenced plants. Neither Na+ nor Cl– develops in developing tissues at concentrations that hinder development: meristematic tissues are taken care of to a great extent in the phloem, from which salt is viably avoided and quickly elongating cells can accommodate the salt that shows up in the xylem inside their extending vacuoles.
Phase 2: The second phase of the development reaction results from the toxic effect of salt inside the plant. The salt taken up by the plant moves in old leaves: proceeded with transport into transpiring leaves brings about extremely high Na+ and Cl– concentrations, and the leaves become die. The reason for injury is presumably the salt burden surpassing the capacity of cells to compartmentalize salts in the vacuole. Salts would then develop quickly in the cytoplasm and inhibit enzyme activity. On the other hand, they may develop in the cell walls and get dried out the cell. The rate of leaf death is crucial for survival of the plant. In the event that new leaves are ceaselessly created at a rate more prominent than that at which old leaves die, there will be sufficient photosynthesizing leaves for the plant to produce flowers and seeds, in spite of the fact that in decreased numbers. In any case, if old leaves die more rapidly than new ones create, the plant may not get by to produce seed. For an annual plant there is a competition against time to initiate flowers and form seeds, while the leaf region is as yet sufficient to supply the important photosynthates. For perennial species, there is a chance to enter a state like to dormancy and survive under the stress. Salt stress not just prompts the decrease of harvest yield yet it additionally influences the metabolic processes in plants through disability of water potential of cells, ion toxicity, take-up of fundamental mineral supplements, membrane integrity and function. NaCl is the most dissolvable and across the board salt and collection of sodium particle (Na+) in plant tissues is one of the most hindering impacts of saltiness. The take-up of fundamental micronutrients, for example, potassium (K+) and calcium (Ca+) from soil is restrained by higher centralization of Na+ [52]. K+ is required for development or improvement of plants and for keeping up high K+/Na+ ratio in shoot which is the significant technique received by plants to adapt up to salt stress. K+ and Na+ however having comparative compound properties, both have distinctive physiological effect on plant development. Under salt pressure, hyperosmotic and hyperionic (particle harmfulness) stresses happen because of low water potential of soil and abundance sodium particle amassing inside the plant. Ionic stress is additionally connected with nourishing irregularity. Salt stress additionally causes diminished germination rate, decreased development, altered reproductive behavior and diminished yield. Modified enzymatic movement, disturbed photosynthesis, oxidative pressure, disrupted biomembrane structure and function, harm of ultrastructural cell components, and hormonal imbalance are a few explanations behind diminishing generally speaking development and improvement of plants under salt pressure.
Salt tolerant is a polygenic trait directed by multiple factors/genes. There are various systems for salt resilience helps in decreasing Na+ gathering in the cytoplasm by restricting Na+ section into the cell, effectively moving Na+ out of the cell, and compartmentalizing Na+ into the vacuole. High-affinity potassium transporters (HKTs) are most active at level of plasma membrane and act as Na+/K+ symporters as well as Na+ particular uniporter. Significant two subfamilies of HKTs: HKT1 and HKT2 are being investigated phylogentically [53]. HKT1 are only permeable to Na+ but HKT2 are penetrable to both Na+ and K+. The group of HKTs having a place HKT/Trk/Ktr-type K+ transporter superfamily are found generally in microorganisms and plants. In numerous plants, Na+ and Cl− are avoided by roots and water is taken up from the soil. This avoidance at higher salinities is kept up by halophytes. For example, sea grain grass, Hordeum marinum, avoids both Na+ and Cl− until at least 450 mM NaCl. Receptive oxygen species (ROS), made during the stress causes chlorophyll degradation and membrane lipid peroxidation. Malondialdehyde (MDA) is one of the final products of peroxidation of polyunsaturated fatty acids in the cell layers. The increase in free-radicals causes the overproduction of MDA which is the most notable marker of the oxidative stress. Plants accumulate different kind of metabolites on introduction to stressful conditions. The enormous changes under abiotic stress are showed up by soluble sugar, proline, phenolic compounds, chlorophyll substance, K+/Na+, shoot-root biomass proportion, etc. Total soluble sugar is an essential part of carbohydrate metabolism. It shows a close connection among photosynthesis and plant productivity and reflects the ability of grains to use assimilates. Proline is the fundamental amino acid act as excellent osmolyte and besides fill in as metal chelator anti-oxidative defense molecule and signaling molecule.
Thereby it maintains concentration of ROS in normal range and prevent oxidative burst in plants. Phenolic compounds also show important role in neutralizing the free radicals, quenching singlet oxygen and decomposing peroxides. Different approaches have been adopted to improve plant performance under salt stress; introduction of genes, screening of better performing genotypes, and crop improvement through conventional breeding methods which are often not so successful and not suitable due to time consuming or reduction of plant vigor with the succession of time. Uses of exogenous phytoprotectants, seed priming, nutrient management, and application of plant hormones are convenient for improving plant performances. These approaches are being also popular for stress management practices including the salt stress.
In this manner it keeps up concentration of ROS in ordinary range and prevent oxidative burst in plants. Phenolic compounds additionally show significant job in neutralizing the free radicals, extinguishing singlet oxygen and breaking down peroxides. Various methodologies have been adopted to improve plant performance under salt stress; introduction of genes, screening of better performing genotypes and crop improvement through traditional breeding techniques which are frequently not all that fruitful and not reasonable because of tedious or decrease of plant vigor with the progression of time. Uses of exogenous phytoprotectants, seed priming, supplement management, and utilization of plant hormones are advantageous for improving plant exhibitions. These methodologies are being also popular for stress management practices including the salt stress.
Class 1HKT genes are involved in regulating transport of Na+ in higher plants. Several HKT1 genes including HKT1; 1/2-like, HKT1; 3-like, HKT1; 4-like, and HKT1; 5-like, have been identified and mapped to wheat homologous chromosome groups 2, 6, 2 and 4 respectively. Among these, Nax1 in chromosome 2AL co-segregated with sodium transporter gene HKT1; 4-A2, which was shown to control Na+ unloading from xylem in roots and sheaths. Nax2 was mapped to the distal region of chromosome 5AL that is homologous to a region on chromosome 4DL containing Kna1 [54]. Based on synteny and phylogeny analysis with Nax2, TmHKT1; 5-A significantly reduced leaf sodium content and increased durum wheat grain yield by 25% compared to lines without the Nax2 locus. Furthermore, decreased expression of TaHKT1; 5-D, which is homoeologous to TmHKT1; 5-A and underlies Kna1 locus in bread wheat, caused by target-specific RNA interference-induced silencing (RNAi) led to an accumulation of Na+ in leaves, strongly suggesting that TaHKT1; 5-D should be the candidate gene of Kna1.
Class 1HKT genes are engaged with managing transport of Na+ in higher plants. A few HKT1 genes including HKT1; 1/2-like, HKT1; 3-like, HKT1; 4-like, and HKT1; 5-like, have been recognized and mapped to wheat homologous chromosome groups 2, 6, 2 and 4 respectively. Among these, Nax1 in chromosome 2AL co-segregated with sodium transporter gene HKT1; 4-A2, which was appeared to control Na+ emptying from xylem in roots and sheaths. Nax2 was mapped to the distal region of chromosome 5AL that is homologous to an region on chromosome 4DL containing Kna1 [54]. In view of synteny and phylogeny investigation with Nax2, TmHKT1; 5-An altogether decreased leaf sodium content and expanded durum wheat grain yield by 25% contrasted with lines without the Nax2 locus. Besides, diminished articulation of TaHKT1; 5-D, which is homoeologous to TmHKT1; 5-An and underlies Kna1 locus in bread wheat, brought about by target-explicit RNA obstruction actuated hushing (RNAi) prompted a collection of Na+ in leaves, firmly proposing that TaHKT1; 5-D ought to be the applicant quality of Kna1. A major mechanism in salinity tolerance of wheat is Na+ exclusion mediated by HKT genes. AtHKT1 is regulated by small RNA and DNA methylation. Moreover, DNA methylation also participates in the response of TaHKT1; Transcription factors such as AtAB14 and OsMYBc were shown to regulate HKT genes in plants, offering more candidate targets for enhancing salinity tolerance.
When there is high concentration of salt in plant system, the activation of complex physiological responses such as phytohormone signaling pathways and developmental signals starts to adapt the stress; therefore it is essential to identify the environmental and developmental signals. First of all an attempt was performed by looking at phytohormones, as most phytohormones are regulatory factors of both developmental process and stress response. For example, the wheat gene TaAOC1, encoding cyclase involved in jasmonic acid synthesis, was induced by high salinity. Constitutive expression of TaAOC1 in both wheat and Arabidopsis restricted root growth, but enhanced salt tolerance and Jasmonic acid content. It indicates the different branches of metabolic pathway participate in a single process but controlled by different mechanisms. Light is an essential factor that positively affects the development and growth of plants. TaGBF1, a blue light specific responsive G-box binding factor, was prompted after exposure to salt. TaGBF1 caused salt affectability and advanced light blue interceded photomorphogenesis, indicating that it was a typical segment of the blue light and salt stress responsive signaling pathways. Curiously hereditary examination recommended that the job of TaGBF1 because of salt depended on AB15, a key part of ABA signaling pathway. The extensive studied has been done for the identification of salt tolerant QTLs. The available studies led to identification of ~500 QTL (excluding those involved in digenic epistatic interactions and QTL × treatment interactions); these QTL are spread over all the 21 wheat chromosomes and could prove useful resource for MAS intended at improving salt tolerance in wheat. The phenotypic variance (PV) explained by individual QTL ranged from 8.4% to 38.0%, and only a dozen major QTL have been reported (Table 4). The traits used for QTL analysis included Na+ exclusion/content, K+ content and K+/Na+ ratio, etc., both at the seedling and adult plant stages. Since several studies in different plant systems including wheat have demonstrated that Na+ concentration is not necessarily associated with salinity tolerance, other additional mechanisms (tissue tolerance and osmotic adjustment) may also be examined in future in order to breed for salinity tolerance in bread wheat. It has been studied that bread wheat exhibit low rates of Na+ transport, which leads to high K+/Na+ ratio in leaves. A high K+/Na+ discrimination provides tolerance to salinity stress. The extensive studied has been accomplished for the ID of salt open minded QTLs. The accessible examinations prompted identification of ~500 QTL (barring those associated with digenic epistatic collaborations and QTL × treatment communications); these QTL are spread over all the 21 wheat chromosomes and could demonstrate valuable asset for MAS expected at improving salt resilience in wheat. The phenotypic difference (PV) clarified by individual QTL extended from 8.4% to 38.0%, and just 12 significant QTL have been accounted (Table 4). The qualities utilized for QTL investigation included Na+ rejection/content, K+ substance and K+/Na+ proportion, and so forth., both at the seedling and grown-up plant stages. Since a few investigations in various plant frameworks including wheat have exhibited that Na+ fixation is not really connected with saltiness resilience, other extra components (tissue resistance and osmotic alteration) may likewise be analyzed in future so as to raise for saltiness resistance in bread wheat. It has been contemplated that bread wheat show low paces of Na+ transport, which prompts high K+/Na+ proportion in leaves. A high K+/Na+ segregation gives resilience to saltiness stress.
Sl. no. | Traits | QTL/locus | PVE % | Linked marker | Physical position (Mbp)a | References |
---|---|---|---|---|---|---|
Na+ exclusion | Kna1 | — | Xwg199, Xabc305, Xbcd.402, Xpsr567, Xpsr375 | 390.2 | [55] | |
Na+ exclusion | Nax1 | 38 | Xgwm312, Xwmc170 | 709.0–711.5 | [56] | |
Dry weight of plumule at germination | Qpdwg-4D.1 | 19.8 | Xfbb226–Xfba177 | ND | [57] | |
Na+ exclusion | QNax.aww-7AS | 41 | Xwmc083–Xcdo595 | 89.9 | [58] | |
Booting | QB.uabcs-2D | 23.6 | Xcdo1379 | [59] | ||
Ear emergence time | QEet.uabcs-2D | 27.1 | Xcdo1379 | ND | ||
Flowering | QFl.uabc-2D | 26.7 | Xbcd102a | ND | ||
Maturity | QM.uabc-2D | 28.9 | Xcdo137 | ND | ||
Ear length | QEl.uabc-2D | 21.5 | Xbcd102a | ND | ||
Seedling shoot fresh weight | 3B-1 | 19.2 | wPt-798,970-wPt-8303 | ND | ||
Na+ exclusion value | qSNAX.7 A.3 | 18.79 | AX-95248570–AX-95002995 | 700.6 | [60] | |
3rd leaf Na+ and K+ concentration and K+/Na+ ratio | 4B | 18, 20, 27 | Xm564 | 657.1 | [61] | |
3rd leaf Na+ concentration | 3B | 18 | Xm551 | 701.9 | ||
K+ μmol/g dry weight | QK.asl-5A | 28.2 | Vrn-A1 | 587.4 | [62] |
A list of major QTL/loci (PVE of ~>20%) for plant traits under salt stress condition in bread and durum wheat.
Position of one flanking marker was given if either the second marker or its sequence was not available.
PVE: phenotypic variation explained; “–“explain PVE% not available; ND shows physical position of QTL could not be determined due to lack of linked marker sequence information.
Germination of wheat inside the grain ear head before reap is called pre-gather sprouting (PHS). Exposure of prolonged precipitation and high humidity after the grain has matured and before it very well may be collected can prompts pre-harvest sprouting (PHS), which can be thought of as an premature germination. Germination can start as a wheat seed retains moisture and swells. A noticeable sign of PHS incorporates kernel swelling, germ discoloration, seed-coat parting, and the root and shoot emergence.
Pre-collect growing in bread wheat (Triticum aestivum L.) is a setback that happens everywhere throughout the world to varying degrees. The issue happens when high humidity goes with precipitation on standing full grown wheat crops before harvest, and seeds in the spike sprout. As the outcome of this, wheat qualities as well as quantity are affected, diminishing healthy benefit and yield. Changes in sugar content, total protein and composition of amino acids joined by enzymatic activities are the explanations behind the degradation in quality and yield. Many early wheat scientists reported that pre-harvest sprouting is negatively correlated with yield, seed viability, seedling vigor, flour yield and baking quality. Pre-harvest sprouting results in lower yields due to decreased test weights, and it limits end-use applications for wheat due to decreased grain quality. Reduced grain quality, coupled with decreased yields, can result in substantial financial losses to farmers and food processors. Products made from germinated seeds can be spongy, soggy, off-color and of inferior quality [63]. Sprouted seed baked to Compact interior and smaller volume breads due to higher α-amylase activity results in starch degradation, hence producing lower quality of bread that is below the accepted standards of consumers. Numerous early wheat researchers revealed that pre-harvest sprouting is negatively correlated with yield, seed suitability, seedling force flour yield and preparing quality. Pre-harvest sprouting outcomes in lower yields because of diminished test weight and it limits end-use applications for wheat because of diminished grain quality. Diminished grain quality, combined with diminished yields, can bring about significant financial losses to farmers and food processors. Items produced using germinated seeds can be spongy, soggy, off-color and of inferior quality [63]. Germinated seed baked to Compact inside and smaller volume breads because of higher α-amylase activity brings about starch degradation, thus creating lower quality of bread that is underneath the acknowledged norms of customers.
Pre-harvest sprouting is controlled by genetic factors, environmental conditions and their interactions. The protection from germination is fundamentally connected with an adequate level of kernel dormancy. Pre-harvest sprouting depends significantly on (1) hereditary attributes like kernel coat, protecting structures of spike and straightness of spike, (2) natural conditions like temperature and precipitation, and (3) agronomic perspective like fertilization. The main considerations next to conditions influencing the resilience to PHS are seed dormancy, seed coat penetrability and color, α-amylase activities, endogenous hormones levels, genes and QTLs. Dormancy was seen as the fundamental internal factor which lead to the wheat resistance from PHS [64, 65, 66]. The seed coat permeability is the essential guaranteeing divider which could increase the wheat PHS resilience. The seed coat color additionally assumes a critical activity in PHS. All around, white wheat varieties have higher germination rates than the red ones [67]. Cultivars having red kernels are more impervious to growing than white ones. Accordingly, red kernel shading is consistently used as an indicator of sprouting resistance in wheat. The α-amylase viewed as one of the significant elements that influence wheat germination rate, cold versatility and production. Some extraordinary endogenous factors like gibberellic acid (GA), abscisic acid (ABA) and indole acidic acid (IAA) could in like manner impact PHS through a wide scope of ways. PHS is a quantitative characteristic compelled by various genes. Viviparous-1 (Vp-1) has been recognized as the main gene that coordinated seed germination and dormancy. Some different genes were also regarded to participate in embryos maturing, seed dormancy and germination through system guideline with Vp-1 to control PHS. QTLs for dormancy and PHS were found in different materials through molecular markers. During kernel development, the Vp-1 gene expressed in cytoplasm subsequent to flowering controlled seed dormancy at the transcriptional level, advanced the seed development and checked the outflow of germination-related genes [68]. There were numerous allelic variety of Vp-1 gene in various grain crops, however the anticipated protein of Vp-1 was monitored with four DNA binding regions A1, B1, B2, and B3. Three alleles Vp-1A, Vp-1B, Vp-1D of Vp-1, situated on 3A, 3B and 3D homologous chromosomes in wheat, separately, have been identified [66, 69]. Numerous investigations additionally centered on the allele’s variety of Vp-1 to clarify how Vp-1 managed the resistance to PHS. Six alleles of Vp-1A, namely Vp-1Aa, Vp-1Ab, Vp-1Ac, Vp-1Ad, Vp-1Ae and Vp-1Af, were found in 81 wheat cultivars and advanced lines [69]. Six alleles of Vp-1B named Vp-1Ba, Vp-1Bb, Vp-1Bc, Vp-1Bd, Vp-1Be and Vp-1Bf were likewise found in wheat [69, 70]. However, no alleles of Vp-1D were found in wheat. The wheat varieties with alleles of Vp-1Ab and Vp-1Ad were regarded to have low germination index (GI) and strong PHS tolerance [69]. However, the wheat varieties with the allele Vp-1Ba have higher germination index and more sensitive to PHS than the other five ones, which even positively influenced on the decrease of germination rate [69, 70]. More than 47 investigations on QTL interval mapping for PHS resistance and related characteristics including ~40 distinct population derived from bread wheat (including synthetic wheat), durum wheat and T. monococcum have so far been conducted. QTL for PHS tolerance have been recognized utilizing the following parameters: PHS index, grain color, falling number, germination index, seed dormancy and alpha amylase activity (Figure 4).
Number of QTL for five different traits associated with pre-harvest sprouting tolerance reported in the 47 studies in wheat.
Maximum numbers of QTL have been accounted for PHS index followed by seed dormancy, germination index, falling number, alpha amylase activity and grain color. About ~250 QTL were distinguished, among them just 29 QTL were major and stable across environments; these QTL are conveyed on 11 unique chromosomes (1B, 3A, 4A, 5A, 6A, 2B, 3B, 4B, 7B, 2D, 3D and 7D); the most noteworthy PV explained by an individual QTL range from 23% to 78.3%.
Chromosomes from homoeologous groups 3 and 4 together conveyed 17 of the 29 significant and stable QTL. The PHS and the germination index (a measure of dormancy) have regularly been utilized for estimation of tolerance against PHS. PHS indx is a simple to score parameter and reliable, with the goal that it has been widely used. The QTLs because of seed dormancy, which is characterized as the powerlessness of practical seeds to develop under conditions great for germination is additionally connected with PHS tolerance. The QTL for PHS tolerance, present on the long arms of chromosomes of homoeologous group 3, have regularly been accounted for to be related with genes for red grain color, which contributes to coat-imposed dormancy. A significant stable QTL for PHS (QPhs.ccsu-3A.1; 24.68–35.21% PV) was accounted [71, 72, 73, 74, 75, 76, 77, 78, 79, 80]. The utilization of markers related with this QTL in MAS brought about significant level of PHS tolerance, which was tragically connected with red grain color.
In wheat markets, especially in Southeast Asia and Middle East, Africa and North America, there is a consumer preference for white grain. Along these lines, endeavors were later made to deliver white-grained PHS-tolerant wheat genotypes; for this purpose, major and stable QTL on chromosomes of group 4 and different chromosomes were suggested. SSR markers are accessible for practically all major and stable QTL (Table 5); these SSR markers have been utilized for introgression of a QTL for PHS/dormancy to derive lines with high degree of PHS tolerance related with golden grains.
Sl. no. | Traits/QTL | PVE (%) | Linked marker | Physical position (Mbp)c | References |
---|---|---|---|---|---|
FN/5A | 26.4 | Xpsr1194–Xpsr918b | ND | [81] | |
α-AA/5A | 30.0 | Xpsr1194–Xpsr918b | ND | [81] | |
SD/4AL (33–77.2) | Xcdo795/Xpsr115 | [82] | |||
PHS/QPhs.ccsu-3A.1 (78.3) | Xwmc153–Xgwm155 | 701.7–702.9 | [71] | ||
SD/QPhs.ocs-3A.1 (23.0–44.8) | Xbarc310/Xbcd907 | 7.1 | |||
GI/QGi.crc-3B | 27.0 | Xbarc77–Xwmc307 | 430.1–783.5 | [83] | |
SI/QSi.crc-3B | 24.0 | Xbarc77–Xwmc307 | 430.1–783.5 | [83] | |
FN/QFn.crc-3B | 33.0 | Xbarc77–Xwmc307 | 430.1–783.5, | [83] | |
GI-14/QPhs.dpivic-3D.1 | 26.0–43.0 | Red Grain Color RGC -wms1200 | ND | [84] | |
VI/QPhs.dpivic-4A.1 | 21.0 | Xbarc170–Xgwm269c | 605.7–607.8 | [84] | |
11. | PHS/QPhs.pseru-3AS | 31.26–44.96 | Xbarc12–Xbarc321 | 11.7–15.4 | [85] |
QPhs.dpi.vic.4A.2 | 27.78–39.84 | Xgwm637–Xgwm937 | 617.4 | ||
PHS/2DS | 25.73–27.50 | Xgwm261–Xgwm484 | 19.6–48.1 | [86] | |
GI/QGI.crc-4B | 28.2–66.6 | Xwmc349 | 640.9 | [87] | |
PHS/QSI.crc-4B | 6.2–26.9 | Xwmc349 | 640.9 | [87] | |
PHS/QPhs.cnl-2B.1 | 24.0 | Xbarc55–Xwmc474 | 133.5–172.6 | — | |
GC/QGc.ccsu-3B.1 | 15.28–40.42 | Xgwm938–Xgwm980 | ND | [88] | |
PHS/QPhs.ccsu-6A.1 | 12.01–29.47 | Xgwm1296–Xgwm1150 | ND | [88] | |
PHS/QPhs.caas-3AS.1 | 11.8–27.7 | Xbarc294–Xbarc57 | 7.9–10.3 | [89] | |
GI/QGi.crc-4A | 27.6–58.1 | — | ND | [90] | |
PHS(SI)/QSi.crc-4A | 10.5–32.1 | — | ND | [90] | |
PHS(SI)/QSi.crc-7B | 11.8–20.5 | — | ND 1/2 | [90] | |
FN/QFn.crc-7D | 13.2–20.6 | — | ND | [90] | |
PHS, SD/Qphs.pseru-4A | 17.2–26.5 | GBS_212432–GBS_109947 | ND | [91] | |
QPhs.spa-4B | 35.0–60.0 | Xwmc617b–Xwmc48a | 15.7–98.7 | [92] | |
QPhs.spa-7D2 | 14.0–47.0 | Xbarc76–Xcfa2257a | 634.0 | [92] | |
GI/3AS | 21.6–41.0 | KASP-222 | 7.2 | [93] | |
qPHS.sicau-3D | 8.65–42.47 | AX-94415259 | 562.5–5 | [94] |
A summary of the major and stable QTL for pre-harvest sprouting/dormancy-related traits in wheat.
‘Emotional Finance’, as inaugurated by Richard Taffler and David Tuckett, received a warm reception in the early 2010s from regulators, the financial press, and investment management industry’s main professional body, the CFA Institute. Yet outside their immediate social and professional circles, the wider academic community largely ignored both Emotional Finance’s challenge to Behavioural Finance and its theoretical and methodological approach, which is, at its core, an application of Kleinian psychoanalysis to interpreting the individual psychology of traders and to describing the group psychology of financial markets. A decade after the financial crisis, industry professionals rarely talk about ‘Emotional Finance’ at all, except insofar as they see ‘emotional biases’ as a sub-species of behavioural biases, which hardly amounts to a successful challenge to Behavioural Finance [1]. Because Taffler and Tuckett’s approach is inherently interdisciplinary, few practicing psychoanalysts have felt equipped to comment upon their characterisation of financial markets, and yet fewer finance academics have the training or inclination to reckon with Taffler and Tuckett’s idiosyncratic handling of psychoanalytic theory.
Emotional Finance, as an intellectual project, rests on four related claims: first, that financial assets are categorically different from other kinds of commodities; second, that financial innovation peculiarly lends itself to being experienced as a ‘phantastic object’; third, that regulators can and should design institutional mechanisms that acknowledge the psychodynamics of the dealing room; and fourth, that the recent financial crisis ought to be handled in a manner similar to the post-Apartheid South African regime’s Truth and Reconciliation Commission. While agreeing that financial bubbles are banal and that emotional responses to the vicissitudes of the market are nothing remarkable, this chapter argues that financial assets are not categorically distinct; that the term ‘phantastic object’ is superfluous and its application is a variant of the ‘sharpshooter’ fallacy; that narrative causation is not formally equivalent to causality; that the relationship between group psychology and individual psychodynamics is under-theorised; and that financial instability is not the same as financial bubbles. Finally, there are other bigger threats to financial stability than those identified by the techniques employed by advocates of Emotional Finance, especially given the periods of relative calm in financial markets between the Great Financial Crisis (2007-2008) and its sequelae in the Eurozone Debt Crisis (2009-2012) and the recent crisis caused by the global coronavirus pandemic in Q2 2020.
By far the most problematic claim of Emotional Finance is that financial assets are somehow a special category. In Minding the Markets, Tuckett claims there are three characteristics of financial assets that make them unusually amenable to obtaining the status of a ‘phantastic object’: their volatility, their abstract quality, and the difficulty in determining whether or not a manager’s success was attributable to skill or luck ([2], p. xvii). Of these, the volatility argument is the most straightforward and also most peculiar. While it is certainly true that individual listed securities, futures contracts, or financial derivatives contracts may be highly volatile, financial markets themselves are notable for their lack of volatility. This is straightforward to demonstrate empirically because the volatility of the ‘S&P 500’ (as measured by the implied volatility of index options for the following 30 days) is itself a tradable index called the VIX or CBOE Volatility Index. Its performance since its inception in 1985 can be seen below in Figure 1.
CBOE Volatility Index (VIX) from December 1985 to October 2020 (daily closings). http://www.cboe.com/products/vix-index-volatility/vix-options-and-futures/vix-index/vix-historical-data (CBOE - Chicago Board Options Exchange).
For most of the last thirty-five years, the VIX has hovered around 15 to 25, with a high of 150 during the October 1987 ‘flash crash’. In the fourth quarter of 2008, after the Lehman collapse, it peaked at around 80. What does this mean? The VIX is a measure of volatility over a 30-day period, annualised, such that a VIX of 20 means that the market is expected to move up or down by 5.8% (or 20/√12) over the next 30 days. Even a VIX of 80 in means that the market is expected to move 23.12% up or down over the next 30 days, which most recently occurred in Q2 2020 with the outbreak of the COVID-19 pandemic. The daily volatility, by contrast, is calculated by dividing the number by √256, or the number of trading days in an average year, which for a VIX of 20, means that the market is expected to move up or down by 1.25% daily.
How does this compare to other commodities, say crude oil, or even to gold, that supposedly safe haven? Figure 2 answers this question. In the case of crude oil, the CBOE also publishes an Oil Volatility Index, which is markedly higher than the S&P 500, which compares favourably to a volatility index for gold over the thirty-year period from 1990-2020.
Comparison of Oil, Stocks, and Gold Volatility Indices 1990-2020. http://www.cboe.com/products/vix-index-volatility/volatility-on-etfs/cboe-crude-oil-etf-volatility-index-ovx (CBOE - Chicago Board Options Exchange); http://www.cboe.com/products/vix-index-volatility/volatility-on-etfs/cboe-gold-etf-volatility-index-gvz (CBOE - Chicago Board Options Exchange); http://www.cboe.com/products/vix-index-volatility/vix-options-and-futures/vix-index/vix-historical-data (CBOE - Chicago Board Options Exchange).
Some might complain that this is because oil and gold are exchange-traded and thus subject to added volatility, but, in fact, there is good evidence that exchange-based futures trading lowers volatility rather than amplifies it. We know this because of a natural experiment afforded by the Onion Futures Act of 1958, which banned futures trading in onions [3]. The price volatility of onions is considerably greater than that of either the S&P 500 or of crude oil. The charts in Figure 3 would not surprise economists or finance academics.
Onions vs Crude Oil, Onions vs S&P 500. (a and b) https://www.investing.com/indices/us-spx-500-historical-data (Investing.com Historical Data); https://www.indexmundi.com/commodities/?commodity=crude-oil&months=360 (Index Mundi data archive); https://usda.library.cornell.edu/concern/publications/k643b116n?locale=en (USDA Data Library); https://bsic.it/the-onion-paradox-or-why-futures-are-good-for-the-economy/ (Bocconi Student Investors Club Blog).
As acknowledged above, individual stocks may move more than the market as a whole, but most investment managers hedge this risk by holding a portfolio composed of a variety of different asset classes, let alone constituents among them. Retail investors, rather than professional money managers, may find themselves credit-constrained and forced to sell if a security falls quickly in value, but most fund managers have either automated stop-losses or the discretion with which to cut their losses. Moreover, over longer time horizons, financial assets are not particularly volatile compared to house prices in major markets in last fifteen years as shown in Figure 4.
Annual House Price Inflation Rates, 2006-2020. https://appsso.eurostat.ec.europa.eu/nui/setupDownloads.do (Eurostat Data Archive); https://apps.bea.gov/iTable/iTable.cfm?reqid=19&step=3&isuri=1&1921=survey&1903=11#reqid=19&step=3&isuri=1&1921=survey&1903=11 (BEA, National Data).
The volatility of the stock market against the risk-free rate is not especially significant even during the Dotcom Crashes. As many commentators noticed at the time of the Lehman collapse, the problem was that most fund managers had spent the majority of their career chasing returns and had little experience of market snaps of any kind. Additionally, market snaps of the kind experienced during the 2008 crash or even the Eurobond crisis of 2011-12 pale in comparison to economic shocks such as that experienced during the coronavirus pandemic in Q1-Q2 2020 as illustrated in Figure 5.
VIX to 10 yr. Treasury Note Yield Ratio, 1990-2020. https://www.macrotrends.net/2016/10-year-treasury-bond-rate-yield-chart (Macrotrends Data Archive); http://www.cboe.com/products/vix-index-volatility/vix-options-and-futures/vix-index/vix-historical-data (CBOE - Chicago Board Options Exchange).
This is why financial engineers worked so hard in the period from 2003 to 2006 to create instruments, like mortgage-backed securities and collateralised debt obligations, that gave investors leveraged access to a much more volatile housing market.
There is no reason to contest much of Tuckett’s characterisation of the problems with the ‘efficient-markets hypothesis’ except to say that it is was originally developed as a simplifying assumption that made certain classes of models tractable. The slippage that allowed it to become a (flawed) description of reality, let alone an operative ideal and normative regulatory goal, is ideological and not the consequence of the internal logic of the idea. Some markets are efficient and do not forecast prices reliably, as Holbrook Working discovered when he explored North American grain markets in the interwar period or securities in the postwar moment [4, 5].
The second quality of financial assets, identified by Tuckett, which makes them amenable to the psychodynamic processes that he describes is their putative ‘abstractness’. This is surely in the eyes of the beholder. As early as Adam Smith [6], economic writers identified two (or three) distinct forms of value: value-in-use and value-in-exchange. Value-in-use can be further distinguished as value-in-consumption or in the income generated by a particular asset, i.e. you could live in a house or rent it out, you could eat the produce of your garden or sell it, etc. Value-in-exchange is what it commands either on an open market or in a barter transaction. For financial assets, there is often little consumable ‘value-in-use’ except at the margins, insofar as some investors may buy Class A or B shares in Berkshire Hathaway in order to meet Warren Buffett at his annual junket in Omaha and other investors (especially aggressive hedge funds) may purchase shares in order to control a company, oust its leadership, merge it with another, or even liquidate it. Most often, however, financial assets either generate income (which Tuckett suggests is usually calculated through a capital asset pricing model) or are sold on for speculative gains or losses. Modern finance theory holds that efficient markets should arbitrage value-in-use (income) and value-in-exchange, so that the dividend is ‘priced into’ the share, but in practice many investors are driven by a combination of dividend income and capital gains, and the protection of the latter in the U.S. and UK tax codes has been distorting investment behaviour these last thirty years or so.
Yet, in practice, these instruments are not abstract to those who trade them. Bonds have par values, generate coupon payments, have interest rates and calculable yields based on their prices. Equities may or may not pay dividends, but can be valued on that basis or on the book value of the firm. A variety of options, including the right to buy or sell a security at a particular price, have been well known for over 500 years ([7], p. 2-3). More complex financial derivatives were not abstract so much as they were opaque, in that they were tied to underlying assets that were, themselves, difficult to value. But even if we were to call that ‘abstraction’, it is by no means obvious that this is the sort of abstraction that lends itself to phantasy. It is equally plausible that relatively simple, graspable items in everyday life are the stuff of phantasies. The very complexity of some of the more recent species of financial assets (especially collateralised debt obligations that were tied to securitised mortgages) made them difficult to value, but the problem was not that investment managers fantasised about them, but rather that rating agencies were put under pressure to score them more highly than they deserved.
Elsewhere Tuckett contrasts financial assets with a television set, where ‘a “rational” consumer can consult a range of information about the price and quality and on that basis make a decision’ ([2], p. 21). He goes on to argue that the buyer might notice he got a bad deal, might observe the prices of televisions fluctuates as models sell out quickly or not at all, or as new models appear, and he might have buyer’s remorse, and even sell it on the second-hand market. Yet Tuckett maintains that ‘with financial assets the situation is very different [from television sets] as they have no intrinsic value but one determined by ambiguous information and varying expectations about an uncertain future that plays out in time’ ([2], p. 21). This is simply untrue. Bonds represent claims, either preferential or subordinated, on the business revenue or tax revenue of the firm or sovereign that issued them, equities represent residual claims against the book value of a firm, whereas financial derivatives (swaps, options, etc) represent contractual arrangements that can, and have, been litigated. The fortunes made by vulture funds that purchased collateralised debt obligations composed of subprime mortgages or of junior Greek debt is an indication that these financial assets do have values that are calculable.
What is more difficult to calculate, and is indeed often uncertain, is the depth of the secondary market at a given time, and hence the liquidity risk. Tuckett commits the same error as proponents of the efficient-markets hypothesis do when he ignores what is known in the trade as “the limits of arbitrage”, in that he assumes that buyers are not credit constrained and only buy or sell because of their sense of the direction of the market. The reality is very different, in that people and institutions can be forced to sell for a range of reasons (to raise money to meet current obligations) and institutions, like pension funds, can be forced to purchase risky assets because they have to match their assets with their liabilities to generate the returns needed to meet obligations that are years away. Liquidity risk is particularly acute in a financial crisis where people are not buying or selling anything at any price, but anyone who has tried to sell a television set near the end of the month can tell you that the used market also depends on the proximity of the average consumer to a weekly or monthly pay day, depending on the price level. Sensitivity to liquidity risk is difficult to know ex-ante, but it is not analytically difficult to grasp.
Moreover, the distinction between risk and uncertainty in Tuckett’s account is problematic. Risk is calculable based on an ergodic assumption that the future will be like the past. To a surprising degree, this assumption holds in financial markets, as the ‘equity risk premium’ (the premium paid to investors for buying equities over government debt securities) has not changed much in 150 years, and, as the finance literature has decisively shown, has made owners of shares better off than those who eschew the risks attendant to them [8, 9].
Moreover, as Figure 6 illustrates, the majority of the ‘total return’ from stocks comes from dividends not from price appreciation, which belies the idea that shares do not have a ‘value-in-use’ or income component that is tangible and real.
Nominal and Real Returns from Stocks and the Stock Index, 1927-2020. (a) https://www.statista.com/statistics/1032048/value-us-dollar-since-1640/ (Statista archive); https://www.macrotrends.net/1333/historical-gold-prices-100-year-charthttps://onlygold.com/gold-prices/historical-gold-prices/ (Macrotrends); https://fred.stlouisfed.org/series/DGS20#0https://www.multpl.com/s-p-500-historical-prices/table/by-year (St Louis Federal Reserve Archive); https://seekingalpha.com/article/4311451-stocks-bonds-bills-and-inflation-returns-for-94-years-ending-december-2019 (Seeking Alpha Blog). (b) https://finance.yahoo.com/quote/%5EGSPC/history?period1=-1325635200&period2=1603238400&interval=1mo&filter=history&frequency=1mo&includeAdjustedClose=true; https://www.officialdata.org/us/stocks/s-p-500/1927?amount=100&endYear=2020 (Yahoo Finance); https://www.in2013dollars.com/us/inflation/1927#:~:text=In%20other%20words%2C%20%24100%20in,inflation%20rate%20was%20%2D1.69%25. (CPI Inflation Calculator).
The returns above are for U.S. equities as an asset class (i.e. they represent ‘beta’), and say nothing about particular securities or vintages. Yet it is precisely because retail investors and professional money managers can buy (and sell) index-funds that active managers have to try to ‘beat’ the market. That is where the pressure comes, to generate ‘alpha’, which Tuckett correctly notices is ephemeral, and, according to adherents of the efficient-markets hypothesis, at best idiosyncratic and at worst a statistical mirage. The money managers that Tuckett identified have an incentive to depict their performance as a result of their skill, but given the survivorship bias (firms that get unlucky fail and disappear), the charge that even the big winners are probably ‘lucky monkeys’ is not without some real plausibility.
So, yes, returns are ‘uncertain,’ but what does this mean? ‘Uncertainty’ refers to the ‘unknown unknowns’ of Knight and Keynes, but hardly matters much to the everyday operation of markets, which have remained remarkably continuous and well-funded in all but a handful of cases (some of the more exotic CDOs still do not trade at any price) through the last crisis. The reason that discussions of ‘uncertainty’ were back in vogue in the 2010s is that markets in 2003-2007 under-priced risk, because the models could not account for uncertainty. Once-in-a-lifetime events (the so-called Black Swans) are important to risk managers, but for Tuckett’s argument to work they have to be an everyday feature of markets, which they, by definition, are not. Tuckett is describing the life of an onion trader not a financial asset manager. This is precisely why more recent work on emotions in financial markets has eschewed the problematic articulated by Taffler and Tuckett in favour of understanding how emotions affect participants in markets under ordinary trading conditions [10].
While a middle class, middle-aged Londoner might indeed see a television as ordinary and mundane and a share as ‘exotic’ and ‘abstract’, but as seen in the London riots of 2011, ordinary people did risk their livelihoods, reputation (and a possible criminal record) and even lives to snatch televisions and trainers from shops. Before globalisation, not so long ago, consumers in emerging markets invested television sets with almost magical properties. If television sets are in the eye of the beholder, it is equally plausible that various financial instruments are mundane, familiar and more or less rationally estimable by people who trade them every day. Is financial innovation, in its first incarnation then, any different?
Tuckett thinks so. He cites tulips, subscription shares (in the South Sea Bubble), and a host of other items ([2], p. 18) as inherently generating outsized excitement because they represented ‘financial innovation’, but these assertions are not proven. In some cases, as with tulips and subscription shares, the characterisation of them as novel financial innovations is just wrong ([7], pp. 2-4), as futures trading in Baltic grain had preceded that in tulips by over half a century, and the Bank of England offered subscription shares to English investors decades before the South Sea Company directors did. In other cases, it is easier to explain the erratic valuations in terms of Akerlof’s lemon problem, which can be summarised as those who cannot tell good wine from bad will overpay for the latter and undervalue the former [11]. This is not to deny that bubbles form in financial markets or that they are further fuelled by fantastic narratives about the value of the assets, which are their focal point. But let us not forget that the ‘bubble’ in the early noughties was not in collateralised debt obligations, but rather in housing market where price rises were fuelled by the advent of subprime mortgages, which are neither especially abstract nor backed by something intangible. The trouble is not with the role of fantasies in bubbles, but rather with the theoretical formulation of these ‘phantastic objects.’ In short, there is nothing unique about financial assets.
The theoretical edifice of Emotional Finance equally depends on the usefulness of the term, ‘phantastic object’, as a plausible unit of analysis. Tuckett [2] gives his most recent definition of a phantastic object as ‘subjectively very attractive “objects” (people, ideas or things) which we find highly exciting and idealise, imagining (feeling rather than thinking) they can satisfy our deepest desires, the meaning of which we are only partially aware’ ([2], p. xi). According to Tuckett, he had ‘coined the term’ as an attempt to explain a situation where ‘a story gets told about an object of apparent desire (such as a dotcom share, a tulip bulb, or a complex financial derivative), which becomes capable of generating excitement in a situation where outcomes are inherently uncertain’ ([2], p. xiv). He reports that ‘the term conjoins “phantasy” as in unconscious phantasy and “object” as in representation.’ What does this mean? Tuckett further explains: ‘the phantasy stimulated is about more than just a story of getting rich. Rather it is a story about participation in an imagined object relationship in which the possessor of the desired object plays with the omnipotent phantasy of having permanent and exclusive access to it and all good things’ ([2], p. xiv). Although Freud and Klein both long ago recognised that all object relationships are ambivalent, Tuckett sees ambivalence (and with it a degree of abstraction, ambiguity and uncertainty) as necessary ingredients of this heady emotional stew [12, 13]. Yet the insistence on ambivalence, for emphasis, is hardly a cardinal sin.
The more serious problem arises, however, when we pick apart this notion of ‘phantasy.’ For Tuckett and Taffler, the usual citation is Freud’s meditation on creative writing and daydreaming [14]. Here Freud develops a theory, no longer accepted even in literary theory, that a child’s fantastical play is very similar to the creative writer, because both the child and the writer are able to distinguish their intensely rich libido-cathected worlds and the characters they create for them from external reality ([14], p. 142-3). Phantasies, both conscious and unconscious, come to replace play, for Freud, as ‘the growing child when he stops playing, gives up nothing but the link with real objects; instead of playing, he now phantasises’ ([14], p. 144). Adults populate their phantasies with their internal objects both in manifest and disguised forms. In that limited sense, Tuckett’s ‘phantastic object’ is simply any object that has found a place in an adult’s unconscious phantasy, or what Freud constructed as the ‘psychical reality’, which is unique to each individual. Exactly how ‘financial assets’ become the paradigmatic ‘phantastic object’ remains to be shown, unless what Tuckett really means is that financial assets evoke some memory of a part-object or maternal breast.
To complicate matters, Freud recognises that children rarely conceal their fantastical play, whereas ‘the adult, on the contrary, is ashamed of his phantasies and hides them from other people. He cherishes them as his most intimate possessions, and as a rule he would rather confess his misdeeds than tell anyone his phantasies ([14], p. 144). If so, it is all the more remarkable that the fund managers whom Tuckett interviewed were willing to tell their ‘phantasies’ to him, over the course of one meeting of 70 minutes or so, unless, if by analogy to Freud’s neurotic patient who hopes for a cure, they confess their phantasies to Tuckett in hopes of absolution for speculative excess ([14], p. 145).
Freud’s explanation of what causes adults to hide their phantasies in shame arises from the fact that they are ‘either ambitious wishes, which serve to elevate the subject’s personality; or they are exotic (sic) [erotic] ones’ ([14], p. 146). But he cautions, ‘we will not lay stress on the opposition between the two trends; we would rather emphasise the fact that they are often united’ and just as often reparative ([14], p. 146-7). Even the most overtly ‘ambitious, egotist wishes’ have some element of sexual gratification involved, if merely auto-erotic in the most narcissistic of states. Freud finishes by comparing ‘phantasies’ to ‘dreams’ and noting their quality of wish fulfilment ([14], p. 148). All of this is very familiar to psychoanalysts, but Tuckett’s neologism has lost the crucial sense, found in Freud, of erotic wish fulfilment, presumably because draining it of the erotic makes the concept more palatable to Tuckett’s audience. The Strachey translation’s tendency to render ‘fantasy’ as ‘phantasy’ (which is now the conventional usage in Britain) further reinforces the impression that it has little to do with sex, however alien the spelling may seem to American readers.
If we allow that conscious and unconscious narratives which adults weave about their internal objects are invested with libido and contain sexual gratification and conquest as elements of their function as wish fulfilment, then there is nothing unusual, let alone alarming, about a particular investment or set of investments acting as the vehicle, in such a fantasy, to unlimited wealth and with those resources the means to sexual conquest. Buyers of lottery tickets do this every day. To the extent that a particular object occupies a stereotyped place in such narratives, such that it becomes ‘very attractive’ and ‘idealised’ to an individual, let alone a group, then we have something closer to a ‘fetish’ or ‘an inanimate object worshipped … for its magical powers or as being inhabited by a spirit’ ([15], p. 57). Fetish objects also provoke the ‘divided states’ that Tuckett describes ([2], p. xi), possess ‘magical powers’ and lead to ‘potency the [fetishist may] otherwise lack’ ([15], p. 57). Whereas many sexual fetishes function by synecdoche (feet, hair, clothes, footwear, etc), others do so by metonymy, offering a substitute object ([16], p. 132). There are two further features that sharpen the similarities between ‘fetish object’ and ‘phantastic object’, namely ‘(a) the fetish has multiple meanings derived by condensation, displacement and symbolisation from other objects, and (b) the fetishist behaves as though [the fetish object] actually were these other objects and is no more disturbed by incongruity or absurdity than a dreamer is while dreaming’ ([15], p. 57). Ironically, Tuckett’s example of Aladdin’s lamp is usually explained as a fetish object rather than a phantastic one. The use of ‘pseudo-psychoanalytic’ language (‘phantastic object’ in place of ‘fetish object’) may be more acceptable to the audience, but it has the consequence of dislocating the concept within a wider psychoanalytic discourse.
Although Tuckett does not acknowledge this in his own discussion, the Emotional Finance presentation of ‘phantastic objects’ also depends on these meanings derived from ‘condensation, displacement and symbolisation’ ([15], p. 57). Before exploring that in detail, it is first worth considering the alternative source of ‘phantastic object’ as offered by Tuckett, namely in the definition of ‘phantasy’ offered by Laplanche and Pontalis in their rival to the Rycroft volume ([17], pp. 317-321), which invokes the principle that ‘the use of the term “phantasy” cannot fail to evoke the distinction between imagination and reality (perception). If this distinction is made into a major psycho-analytic axis of reference, we are brought to define phantasy as a purely illusory production which cannot be sustained when confronted with a correct apprehension of reality’ ([17], p. 315). As they note, ‘certain of Freud’s writings appear to back up this type of approach. Thus in “Formulations on the Two Principles of Mental Functioning” (1911b), Freud sets the internal world, tending towards satisfaction by means of illusion, against an outside world which gradually imposes the reality principle upon the subject through the mediation of the perceptual system’ ([17], p. 315).
For Taffler and Tuckett, the ‘reality’ of financial markets ultimately strips the ‘phantastic objects’ of their value if not their meaning, as the inevitable crash and de-idealisation leads to anger and revulsion [18]. As Laplanche and Pontalis also notice, modern psychoanalytic usage extends ‘phantasy’ to a range of conscious, preconscious and unconscious fantasies, thereby muddling the extent to which repression plays a role ([17], p. 315). They suggest, instead, distinguishing between day-dreams that serve as compromise-formations, common ‘unconscious phantasies’ that appear as precursors to neurotic symptoms, and unconscious fantasies that offer the seeds of wish fulfilment in dreams. With Tuckett’s formulation, the narratives about ‘phantastic objects’ appear to be mostly preconscious, in that the fund managers are not necessarily aware of them until prompted by their interlocutor, but then venture them freely. Whether or not this is plausible in a psychoanalytic sense remains debatable, as Tuckett’s formulation appears to ignore both the roles of secondary revision and of repression.
As with Freud, Laplanche and Pontalis also link phantasies to desire, which does not even merit an index entry in Tuckett [2]. In Laplanche and Portalis, they emphasise the extent to which wish fulfilment evokes the ‘hallucinatory memory of satisfaction’ (1973, p. 318), or the maternal breast, which is a kind of primordial ‘phantasy-object’. Yet they also acknowledge, ‘the relationship between phantasy and desire seems to us to be more complicated than that. Even in their least elaborate forms, phantasies do not appear to be reducible to an intentional aim on the part of the desiring subject …’, and crucially ‘it is not an object that the subject imagines and aims at, so to speak, but rather a sequence in which the subject has his own part to play and which the permutations of roles and attributions are possible’ ([17], p. 318). Read that way, Tuckett’s ‘phantastic object’ is, in effect, a contradiction in terms, in that it is not the object itself that the subject desires, but rather the outcome of the script, i.e. unbridled wealth, beautiful women (or men), and universal gratification. In other words, we’re back to ordinary explanations that turn on greed, lust, and gluttony.
As to the relationship between the internalisation of the so-called ‘phantastic object’ and the processes Rycroft alludes to of ‘condensation, displacement and symbolisation’, these are, in effect, what Tuckett evokes when he describes the ‘divided states’ of idealisation and de-idealisation that he postulates occur in the minds of traders. There may well be a value in thinking about how financial assets relate to Marxian and Freudian notions of ‘fetishism,’ but Tuckett forecloses this possibility with his neologism.
To summarise, there are two separate etymologies of ‘phantastic object’ in Tuckett’s writings with Taffler on the subject. The strain that depends most heavily on Freud is very hard to distinguish from more conventional uses of ‘fetish object’ while the version that depends strictly on Laplanche and Pontalis is oxymoronic. Either ‘phantastic objects’ are essentially fetish objects, denuded of the explicit eroticism, or they are an inherently self-contradictory attempt to bridge the gap between part-objects expressed in paranoid-schizoid states (where what the infant desires is the maternal breast) and vehicles for the realisation of erotic phantasies in less regressed states of mind. The love affair, in short, is not with the financial asset or the car or the suit, but rather still with idea of ‘getting the girl’ or ‘winning the game.’
The latter is simply an instance of superfluity and proliferation of neologisms, which in turn muddles the waters, whereas the former suggests something of the very problematic hermeneutic strategy employed by those who advocate for Emotional Finance.
Interpretation is not explanation; causation is not causality. In the social sciences, this is almost a cliché, but they are important caveats. Causality rests on the identification of a specific mechanism by which X has an effect on Y. Explanations can be realistic in the sense that they try to account for external reality, or epistemic (anti-realist) in the sense that they strive for the internal consistency of the empirical model. Much of Tuckett’s complaint with modern economics is that it strives for the latter, whereas the natural sciences present themselves as interested in the former, except perhaps in cosmology.
In finance, the movement of prices is easy to explain: they rise when there are more buyers than sellers, they fall when there are more sellers than buyers. The willingness to buy or sell is, indeed, partly influenced by individual expectations of future prices, such that for markets to function there has to be heterogeneity of belief. There is nothing at all surprising about that. Predicting the movement of prices is an occult science, whether practiced by ‘chartists’ who do ‘technical analysis’ or by punters who pontificate on the market outlook for a particular stock. Interpreting price behaviour (explaining why markets rose or fell) lies somewhere in between, though much of it depends on normative judgments about ‘value’. To imagine that you are in an asset-price bubble is to imagine that the current prices of an asset have diverged from some ‘rational’ judgement of fundamental value.
Tuckett retains that notion of ‘rationality’, though he attributes it to an uncertain, yet-to-be-experienced ‘objective reality’ rather than to the price discovery mechanisms of the market. Now he is by no means alone in that, as Behavioural Economics speaks of ‘bounded rationality,’ but the problem is whether or not any of this can be apprehended ex-ante. Tuckett identifies the ‘drowning out’ of naysayers as a feature of the euphoria he describes, yet some of these naysayers, like Nouriel Roubini, have successfully predicted ten out of the last three crises, whereas Warren Buffett made an even greater fortune on Berkshire Hathaway’s derivatives book, even as he preached about ‘weapons of mass destruction’. Some people are hypocrites, others are stereotyped market commentators, and even stopped clocks are right twice a day. It should not be forgotten that the people who made the most money in the Great Financial Crisis where those who shorted subprime mortgages, often against the interests of their own clients. The most successful currency trade in modern times, the Black Wednesday bear raid organised by Soros, was, in fact, a mean-reversion trade designed to force sterling out of the European Exchange Rate Mechanism. It just took two billion pounds to do it. In other words, the trick about shorting anything is timing it. To echo the line often mis-ascribed to Keynes, ‘markets can remain irrational longer than you can remain solvent.’
Tuckett [2] variously declaims any attempts at quantification, though his most recent work aims in that direction by attempting to exploit insights from Big Data [19, 20, 21, 22, 23]. Instead, what Tuckett’s approach is offering is an interpretative strategy, which serves mostly as an elaboration of the latter stages of the Minsky-Kindleberger model of an asset-price bubble [24], which identifies states of ‘displacement, new opportunities, boom, euphoria, dismissal, unease, panic, revulsion’ ([2], p. 16). What the Minsky-Kindleberger model describes is not a mechanism of causality but a causal chain. Psychoanalysis, with its roots in Aristotelian casuistry (with the assumption of a relationship, albeit a complex one, between infantile conflicts and adult neuroses), is especially well-suited to such an exercise. Moreover, psychoanalytic theories of causation are also multi-valent. Aristotle identified four cases: material, formal, efficient and final. Freudian psychoanalysis, on the other hand, tends to consider symptoms simultaneously in terms of ‘origins, genesis, function, meaning and expectation’ ([25], pp. 22-36). For example, your euphoria might well have its genesis in the rising price of a stock (or falling if you shorted it), might have its origins in an outpouring of enthusiasm for a new technology in which the particular firm has an advantage, might be a function of the fact that institutional investors have decided they need exposure to that sector, may mean that firms that rely on older technologies will experience hard times, might have been expected given the success of a similar technology in a more advanced country. None of these interpretations of your euphoria have anything to do with causality in any formal sense (that the number of buyers in the market started to outnumber the number of sellers); but rather this strategy reflects a mode of analysis of narrative causation that is liberating because it disrupts established narratives and opens up the possibilities of new ones. This is why Tuckett eventually became interested in ‘conviction narratives’, because that seemed to present a means of moving from causation to casuality [20, 22]. Unfortunately, this strategy creates a hermeneutic circle.
As post-structuralist literary critics subsequently noticed, these narratives generally are organised around one of four tropes: metaphor, metonymy, synecdoche, and irony, which correspond to the emplotments of romance, tragedy, comedy/farce and satire [26]. Tuckett’s case studies of investment managers do all follow similar trajectories, but figural causation is an artefact of the mimetic function of narrative not a feature of reality [27]. The reason that people have not learned from previous crises is because there is less to learn than some might imagine. To suggest otherwise is to suggest that there is some path dependent group psychological structuring of financial bubbles, such that they all have the same denouement, regardless of the particular asset at their core. To the extent that this is true, it is obvious (and just an elaboration of Minksy-Kindleberger), and to the extent that it is not obvious, it is wrong (in that the focal point of bubbles does matter) for reasons that should become clear in the next two sections.
As Tuckett explains, ‘groupfeel’ has replaced his earlier usage of ‘groupthink’ as a way of aggregating the individual emotion states of participants in a market. He is surely correct that groups display elements of ‘consensus seeking, group polarisation, out-group stereotyping, and the suppression of dissent’ ([2], p. 66-67), but what becomes harder to understand is why he sees financial markets as ‘groups’ in the sense that a notion of ‘groupfeel’ would apply. Financial markets are nothing if not competitive arenas, and despite the existence of social spaces in which collusion might occur (c.f. LIBOR-fixing), the notion that the market is subject to these dynamics is implausible. Individual firms may be, which is significant only insofar as some bulge-bracket firms become the dominant dealers in particular financial assets. Tuckett is likewise correct that the structure of the industry means individual managers may be more concerned with short-term performance than with longer-term results, but that has nothing to do with phantastic objects and everything to do with how compensation is structured. This is also one of the few areas in which the market does ‘zero-sum,’ as those managers who outperform the market benchmark are richly rewarded in fees, whereas those who underperform benchmarks get sacked. That said, zero-sum games are not especially known for displaying the sorts of group psychologies found elsewhere.
Behavioural Finance, instead, offers ‘herding’ as a heuristic that mangers use to main-chase the perceived ‘market leaders’. This is not necessarily an emotional response (as one might prefer to think oneself smarter than other traders), but rather a rational one of achieving safe but possibly sub-optimal returns. Even so, it is a simplification to suggest that risk-on/risk-off maps to divided states (paranoid-schizoid and depressive positions), unless one assumes that the ‘market norm’ is one of stagnation, which, at least in equities, is discredited by the data presented in Figure 6. What Tuckett has, in fact, done is taken a typical risk management heuristic of the directors of trading desks on dealing floors, which is to remove from the floor traders who are losing on a given day and to cap the winnings of those who appear to be ‘streaking’, and used it as a synecdoche for the market as a whole. That interpretative strategy makes very little sense, however, when you consider that the reason that the risk manager is pulling the trader is that the frustration and disappointment causes him to exaggerate risk, whereas the success encourages him to underrate risk vis-à-vis the market as a whole. Crucially, in Tuckett’s model, the problem is not the distance between the judgements of individuals and the group, but rather the distance between the phantasies of market participants and his notion of ‘reality’, which can only be apprehended ex-post, but seems in fact to be based upon some notion of equilibrium and rationality that hovers behind the precise notions that he and Taffler try to critique [28], hence the hermeneutic circle.
The final problem with Emotional Finance is the specification of the problem. Financial bubbles are nothing new. One recent work of economic theory written by a former practitioner called them ‘banal’ and ubiquitous [29]. Janeway suggests that problem is not with asset-price bubbles, per se, but rather that some of them are productive whereas others destructive. Asset-price bubbles that focus on ‘general purpose technologies’ or infrastructure (canals, steamships, railways, electrification, information computing technology, etc) tend to be socially beneficial. The rush of speculation generates a tolerance for Schumpterian waste. Once the music stops, individual firms may go bankrupt, but the roads, canals, bridges, and rail lines remain.
Debt-leveraged bubbles, particularly in real estate, can wipe out private wealth and cause contagion to other aspects of the economy, generating great hardship, but those are usually generated by central banks that use household balance sheets to smooth aggregate demand, as happened in the late 1990s and early 2000s. Tuckett’s analysis makes no distinction on the basis of the focal point of the bubble. Bubbles are all equally suspect, in that they are formed around ‘phantastic objects’ that promise fool’s gold. Underlying Tuckett’s work is the peculiar fantasy that it is possible to train regulators to identify asset-price bubbles based on their recognition of a kind of prodromal euphoric state as evidenced in the chatter of traders, particularly on the Bloomberg platform. The idea is then to install circuit-breakers, as a kind of market nanny decides ‘enough is enough.’ The problem with this is that it begs the regulatory equivalent of the Texas sharpshooter fallacy, whereby a gunman sprays the side of a barn with a shotgun and only then steps up to draw the bulls-eye. We can only guess at the number of ‘dangerous’ bubbles that will be so averted!
One final point remains to be made. Tuckett calls for a ‘Truth and Reconciliation’ Commission to investigate the financial crisis in the same manner as the Apartheid-era crimes in South Africa. Leaving aside the question of how successful the latter was, the former is hardly worthy of such an intellectual and moral project. The Great Financial Crisis was not the end of the world as we know it, particularly from the vantage point of 2020 when the effects of COVID-19 lockdowns are so much greater. If the Great Financial Crisis was a searing experience for the Millenial generation, it was not because of economic realities, but because of the political responses to the crisis. Austerity policies which produced widening inequality in the developed world are neither ‘necessary evils’ nor the product of the ‘inner logic of capitalism,’ but rather are ideological and political projects pursued with the blessings of the median-voter.
The most dangerous thing about Tuckett’s proposals for ‘minding markets’ is that they de-politicise the regulatory process, putting it in the realm of regulating human emotion, rather than in the sphere of political economy. For Tuckett, based in the United Kingdom, the irony of the financial crisis is that the neo-liberal experiment in ‘light touch’ regulation and low levels of taxation (especially on capital gains) happened under New Labour. The Tories came to power on the back of New Labour’s mistakes, and have followed the ‘tried and true’ strategy of austerity while blaming the ‘pain’ on their predecessors and on the European Union. The electoral calculus of such a strategy produced Brexit. The glee with which the political elite have pursued these aims and the docility of the electorate in the face them is a much worthier target of study via notions like ‘groupfeel’ and ‘phantasies’ that produce master narratives. Rather than minding impersonal markets, we’d do better to mind our own tendency to deny the damage done by those who used the financial crisis to justify policies that they fully intended to pursue anyway. If 9/11 was George Bush’s excuse for invading Iraq, the collapse of Lehman Brothers in its vicissitudes offered the Tories a pretext for dismantling the welfare state. In the era of COVID-19, the main challenge for regulators and central banks alike will be resisting pressure from politicians the world over to encourage bull markets deliberately in order to maintain consumer and investment confidence in the face of damage to the real economy and especially the attendant job losses. In addressing such questions, ‘Emotional Finance’ has little to offer, despite the sense of Déjà vu involved.
The author would like to acknowledge a number of people with whom she has discussed this subject over the years, including Professor Michelle Baddeley, Dr Stanley H. Shapiro, Dr Frederick Fisher, Dr Margot Waddell, and Dr David Bell, and the members of the London Consortium’s ‘Psychoanalytic Thought, History and Political Life Forum,’ which was where she gave a version of this paper as a seminar in June 2014. Special thanks to the organisers, Dr Shaul Bar-Haim, Dr Benjamin Poore, and Dr Helen Tyson, and particularly to Professor Daniel Pick, Professor Jacqueline Rose, Dr Matt ffytche, Dr Manuel Batsch, and Dr Akshi Singh for their comments. A version was also circulated in September 2015 at the New Imago Forum at Jesus College, Oxford where useful suggestions were made. The author would also like to thank her research assistant, Mr Eskil Välilä, for redrawing the graphs with updated data, which required considerable research, and for rendering them to suit the formatting guidelines for this publication.
The author declares no conflict of interest.
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