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June 2023

Authors:

Pablo Godínez

Autonomous University of Queretaro

Amanda Kim Rico Chávez

Autonomous University of Queretaro

Noelia Isabel Ferrusquía-Jiménez

Autonomous University of Queretaro

Ireri a Carbajal

Autonomous University of Queretaro

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Plant hormesis: Revising of the concepts of biostimulation, elicitation and

their application in a sustainable agricultural production

Pablo L. Godínez-Mendoza, Amanda K. Rico-Chávez, Noelia I. Ferrusquía-Jimenez, Ireri A. Carbajal-Valenzuela,

Ana L. Villagómez-Aranda, Irineo Torres-Pacheco ⁎,Ramon G. Guevara-González ⁎

Center of Applied Research in Biosystems (CARB-CIAB), School of Engineering, Autonomous University of Querétaro-Campus Amazcala, Carr. Amazcala-Chichimequillas Km 1.0, C.P 76265 El Marqués,

Querétaro, Mexico

HIGHLIGHTS GRAPHICAL ABSTRACT

•A big challenge in current plant produc-

tion is to cope with climate change.

•Environmental hormesismust be included

in plant science research.

•Plant biostimulants/elicitors are current

agrochemicals sometimes displaying

hormesis.

•Controlled elicitation strategies including

hormetic scenarios must be designed.

•Plant biostimulation using controlled

management of stressors is proposed as a

tool for sustainable agriculture.

ABSTRACTARTICLE INFO

Guest Editor: Evgenios Agathokleous

Keywords:

Agriculture

Plant defense

Epigenetics

Plant immunity

Stressors

Current research in basic and applied knowledge of plant science has aimed to unravel the role of the interaction be-

tween environmentalfactors and the genomein the physiology ofplants to confer the ability to overcome challenges in

a climate change scenario. Evidenceshows that factors causing environmental stress (stressors), whether of biological,

chemical, or physical origin, induce eustressing or distressing effects in plants depending on the dose. The latter sug-

gests the induction of the “hormesis”phenomenon. Sustainable crop production requires a better understanding of

hormesis, its basic concepts, andthe input variables tomake its managementfeasible. This implies that acknowledging

hormesis in plant research could allow specifying beneﬁcial effects to effectively manage environmental stressors ac-

cording to cultivation goals. Several factors have been useful in this regard, which at low doses show beneﬁcial

eustressing effects (biostimulant/elicitor), while at higher doses, they show distressing toxic effects. These insights

highlightbiostimulants/elicitors astools to be included inintegrated crop management strategies forreaching sustain-

ability in plant science and agriculturalstudies. In addition, compelling evidence on the inheritance of elicited traits in

plants unfolds the possibility of implementing stressors as a tool in plant breeding.

1. Introduction

Environmental stimuli might be considered as stress factors (alsocalled

“stressors”) that interact with plant genotypes, permanently shaping their

development considering the concept of allostasis. Contrary to homeostasis,

in allostasis an organism is said to not have ﬁxed physiological set points,

but ﬂuctuating according to demands made on the organism by the

Science of the Total Environment 894 (2023) 164883

⁎Corresponding authors.

E-mail addresses: irineo.torres@uaq.mx (I. Torres-Pacheco), ramon.guevara@uaq.mx

(R.G. Guevara-González).

http://dx.doi.org/10.1016/j.scitotenv.2023.164883

Received 15 March 2023; Received in revised form 11 June 2023; Accepted 12 June 2023

Available online xxxx

Contents lists available at ScienceDirect

Science of the Total Environment

journal homepage: www.elsevier.com/locate/scitotenv

environmental stressors (Sonmez et al., 2023). Plants possess several differ-

ent protein receptors that allow them to detect and respond to several

stressors (Liang and Zhang, 2022). Plant receptors directly sense some envi-

ronmental stressors, but most stressful conditions are sensed through en-

dogenous signals triggered by changes in the chemical environment

within the cell, such as reactive oxygen species (ROS) accumulation or pro-

tein denaturation (Lamers et al., 2020;Sonmez et al., 2023). Consequently,

the adaptive responses of plantsare not independent of each other; they are

part of a defensive system that responds through similar mechanisms to

stressors of different natures depending on the intensity of their incidence

(Erofeeva, 2022a).

Stressors application in plant science (i.e., pesticides, deﬁcit-regulated

irrigation, beneﬁcial microorganisms, hazardous compounds, UV radia-

tion, etc.) commonly displayed biostimulant and elicitor responses

(i.e., improving plant performance and immunity, respectively) or toxicity,

in a dose-dependent manner, recalling the concept of “hormesis”(Vazquez-

Hernandez et al., 2019a;Agathokleous et al., 2019b;Camilo dos Santos

et al., 2022;Valencia-Hernandez et al., 2022). The application of stressors

in agricultural studies has been conducted by evaluating a few numbers of

speciﬁc doses, even not always considering the role of phenological stage

and transgenerational inheritance of phenotypes (Belz and Duke, 2022a;

Desmedt et al., 2021;Villagomez-Aranda et al., 2021). Based on this evi-

dence, it is reasonable to state that the controlled application of stressors

during plant cultivation either at the greenhouse or open-ﬁeld level,

might be used as a tool in the future design of sustainable agricultural strat-

egies considering an integrated crop management. In greenhouse this pos-

sibility might be easier to be practical than in open-ﬁeld. This review aimed

to revise, within a hormetic context, several aspects surrounding the con-

cepts of biostimulation and elicitation that arise from plant science studies

and propose their application as a tool in the integrated crop management

for the development of sustainable plant production systems, an urgent

concern in the current worldwide climate change scenario.

2. Concepts of hormesis theory in plant stress adaptation: current

trends

In the 21st century, the efforts to study the effect of stressors on plants

have intensiﬁed due to the challenge climate change represents for agricul-

ture and the general maintenance of plants in diverse environments. The

stressors can be of biological origin (pathogens, beneﬁcial microorganisms,

pests, etc.) or non-biological (drought, salinity, extreme temperatures,

acoustic waves, etc.), and their impact will vary according to its dose

(Vazquez-Hernandez et al., 2019a). Depending on its dose, a stressor

might trigger in plants stimulant features such as increasing growth,

yield, production quality (i.e., biostimulation), increase stress tolerance

(i.e, elicitation), or toxic phenotypes. When a stressor triggers a stimulant

response, a positive stress or eustress occurs (i.e., the stressor is an

“eustressor”). On the contrary, if the response is toxic, either deleterious

or lethal, it is called negative stress or distress (i.e., the stressor is a

“distressor”)(Vazquez-Hernandez et al., 2019a;Sonmez et al., 2023).

This apparent duality of plant physiological responses to stressors re-

minds us of the phenomenon of hormesis, widelystudied in endocrinology

and toxicology but less studied in plant science (Agathokleous et al.,

2019a). Recently, the number of studies considering the dose-response

relationship in the deliberate exposure to chemical substances (usually

various agrochemicals) and physical treatments (temperature, soil mois-

ture, etc.)has constantly been increasing. These studies show that a speciﬁc

plant response depends on the stressor applied and the response variable

measured. Plants respond in such a way that ultra-low stressor doses do

not generate an observable phenotypic response (i.e. No-Observed-Effect-

Level, NOEL). Still, once this dose level is exceeded, the treatment can stim-

ulate response variables until reaching a Maximum Stimulation dose (“M”

dose), then the response diminish until a dose that generates toxicity once

the so-called No-Observed-Adverse-Effect-Level (NOAEL) is passed

(Fig. 1)(Agathokleous et al., 2019a).

The zone between the NOEL and NOAEL doses on a hormesis curve is

the zone of hormetic response to the stressor or “eustress zone”

(Vazquez-Hernandez et al., 2019b, a;Belz and Duke, 2022a;Sonmez

et al., 2023)(Fig. 1). Likewise, it is also possible to ﬁnd non-hormetic

responses for variables in dose-response studies (Agathokleous et al.,

2019a). Multiphasic responsesto allelopathic or allelochemical compounds

that depend on the duration of the stress application (An, 2005;Belz and

Duke, 2022a, 2022b) or the evaluated variable have been reported

(Erofeeva, 2020). Considering the feasibility of hormetic responses, it is

likely that some stressors are inherently considered toxic to plants, mainly

because they have not been studied on a hormetic scheme in speciﬁcdoses.

For example, the herbicide glyphosate has recently been demonstrated to

induce growth and stress tolerance in Chenopodium album (Belz, 2020),

LEA

LEO

Fig. 1. Crop biostimulation and priming(elicitation) in thecontext of the hormesismodel. The maximum stimulatory dose occurs at the “M”dose, while X1 and X 2 represent

the NOEL (No-Observed Effect Level) and NOAEL (No-Observed Adverse Effect Level), respectively. The eustress zone is characterized by the stimulation of growth and

productivity (biostimulation) and simultaneous activation of defense mechanisms (elicitation). If the NOAEL is exceeded, biostimulation ceases due to hormetic trade-

offs, but plant defense increase to toxic levels.

(Created with biorender.com.Figuremodiﬁed from Belz and Duke, 2022b.)

P.L. Godínez-Mendoza et al. Science of the Total Environment 894 (2023) 164883

and cadmium salts in the nutrient solution were reported to increase toler-

ance to Clavibacter michiganensis infection in tomato (Solanum lycopersicum

L.) (Valencia-Hernandez et al., 2022).

In plant science, the phenomenon of “priming”or elicitation has been

investigated and reported frequently (Martinez-Medina et al., 2016). It con-

sists of applying low doses of a stressor, making the plants activate their de-

fense system at a high and long-lasting level, and remain “conditioned”in

the face of future stress situations. In addition, the concept of priming in-

cludes that the progeny, as one of its characteristics, could inherit this

“super immunity”phenotype (Martinez-Medina et al., 2016). Priming or

elicitation is a phenomenon that favors channeling the energy of the plant

towards the induction of the defense system, thus causing energy

expenditure or sacriﬁce for the growth and development of the plant

(Martinez-Medina et al., 2016;Vazquez-Hernandez et al., 2019b). In addi-

tion, a relatively new type of agrochemicals known as “biostimulants”has

become currently used in agricultural practices because they enhance the

growth and development of plants (du Jardin, 2015). By deﬁnition, these

biostimulants are products of biological origin of variable composition

that, in low doses, favor phenotypes towards the growth and development

of plants (du Jardin, 2015;Vargas-Hernandez et al., 2017). It is also known

that some of these biostimulants, when used in higher doses, commonly

show a signiﬁcant increase in tolerance towards biotic or abiotic stressors

(i.e., there is an activation of plant immunity, that is,priming or elicitation

as mentioned above), which is associated with lower growth and develop-

ment and some of them can even be toxic for plants in higher doses asdem-

onstrated recently (Silva et al., 2020).

This latest evidence suggests that some biostimulants might induce

hormesis in some evaluated variables. Therefore, it can be hypothesized

that a biostimulant could improve phenotypical variables (i.e., growth

and development) and/or activate immunity sacriﬁcing growth and devel-

opment (i.e., they cause elicitation or priming) in a dose-dependent manner

while provoking toxicity at even higher doses, that is, causing distress. In

agriculture, biostimulation and elicitation or priming generates phenotypes

that can be considered favorable within a speciﬁcrangedependingonthe

variable that motivates crop production (these phenotypes fall within the

eustress zone in a hormetic curve; Fig. 2). It is noteworthy that according

to du Jardin (2015),thedeﬁnition of a biostimulant includes only biologi-

cal stressors. However, both chemical and physical stressors can also show

hormetic responses in the eustress zone in plants, suggesting that the

biostimulant concept should be reviewed based on current experimental

evidence (Valencia-Hernandez et al., 2022). Therefore, based on a potential

scenario of hormesis when applying a biological, chemical, or physical

stressor to plants, it is reasonable to expect eustressing effects, depending

on the dose and the variable evaluated; of course, distressing/toxic scenar-

ios could also occur at higher doses that should be explored (Fig. 2).

The following sections of this review examine empirical evidence of

physical, chemical, and biological stressors tested that induce hormesis in

plants. Additionally, the role of the phenological stage of the plant and

the inheritance of phenotypes of interest bred under controlled stress con-

ditions are also discussed, as well as future outlooks underlying hormesis

management as a tool for plant breeding.

3. Stressors management in plants searching for hormetic responses

3.1. Biological

Biological stressors are cell-derived components (Desmedt et al., 2021;

Vazquez-Hernandez et al., 2019a). These stressors are organic molecules

(for example, carbohydrates, proteins, and lipids), conserved in different

species, which have the property of activating plant defense mechanisms.

Activating plant defenses allows plants to perform better in response to

subsequent stressors (biotic or abiotic), allowing the accumulation of sec-

ondary metabolites, stomatal closure, phytohormone production, and acti-

vation of the antioxidant system and expression of defense-related genes

(Ferrusquía-Jiménez et al., 2021). Biological stressors can be divided into

1) exogenous stressors, non-plant molecules, also known as pathogen/

microbial/nematode/herbivore-associated molecular patterns (PAMP/

MAMP/NAMP/HAMP), and 2) endogenous stressors, which are molecules

released from plants in response to cell damage by pathogen attack or envi-

ronmental conditions, also called damage-associated molecular patterns

(DAMPs) (Zehra et al., 2021). Therefore, the plant can recognize molecules

from other organisms (pathogenic or beneﬁcial) or from itself. These com-

pounds are relevant for triggering plant immunity and protecting against

pathogens or adversesituations. In addition, it has been found that some bi-

ologicalstressors may havebiocidal or inhibitory activity againstpathogens

when applied in speciﬁc concentrations (Desmedt et al., 2021;Ferrusquía-

Jiménez et al., 2022a). Due to the great variety of effects found by using

stressors, tests arecarried out toevaluate the impact of different concentra-

tions of biological stressors on plants, which has contributed to the research

for new agricultural management alternatives.

There is an extensive list of reported biological stressors with great

potential for industrial use, some of which are shown in Table 1.

Fig. 2. Hormesis general model in crop science. The hypothetical dose-response curve (Calabrese and Mattson, 2011) applied to plant models illustrates how environmental

stressors can stimulate crops at low doses (eustress) while inhibiting performance and activating defensive responses at high doses (distress).

(Created with biorender.com.Figuremodiﬁed from Belz and Duke, 2022b.)

P.L. Godínez-Mendoza et al. Science of the Total Environment 894 (2023) 164883

Table 1

Examples of plant hormesis and eustress induced by biological, chemical, and physical stressors.

Stressor Tested doses and exposure time Plant species Outcomes Reference

Biological stressors

Yeast extract (MAMP) 100, 500, 1000, 3000, and 5000 mg L

−1

for

72 h

Huangqi (Astragalus

membranaceus)

1000 mg L

−1

: astragaloside (triterpenoid

saponins) content↑

3000–5000 mg L

−1

: astragaloside content↓

Park et al., 2021

Yeast extract (MAMP) 200, 500, and 1000 mg L

−1

for 24 h Flowering ﬂax (Linum

grandiﬂorum Desf.)

200–500 mg L

−1

: lipid peroxidation↓

500–1000 mg L

−1

: phenolic compounds↑

1000 mg L

−1

: lipid peroxidation↑

Goncharuk et al.,

2022b

Extracellular ATP

(DAMP)

55.1, 275.57, 551.14, 1377.85,

2755.7 mg L

−1

for 11 days

Mouse-ear cress

(Arabidopsis thaliana)

55.1–1377.85 mg L

−1

: seedling fresh weight↓,

seedling dry weight↓,R

↓

2755.7 mg L

−1

: plant growth↓

Shi et al., 2022

Extracellular ATP

(DAMP)

5.51, 27.56, and 110.23 mg L

−1

in three

applications

Maize (Zea mays L.) 5.51–27.56 mg L

−1

:Ch↑, seedling dry weight↑,

photosynthesis rate↑, lipid peroxidation↓under

Cd stress

110.23mg L

−1

: seedling dry weight↓,

photosynthesis rate↓, lipid peroxidation↑under

Cd stress

Deng et al., 2023

Chitosan

(PAMP/MAMP)

50, 100, and 200 mg L

−1

for 9 days Psammosilene (Psammosilene

tunicoides)

50 mg L

−1

:GR↑

100 mg L

-1:

nitric oxide↑, POD↑,

gypsogenin-3-O-β-D-glucopyranoside↑,GR↓

200 mg L

−1

: triterpenoid saponins↑, SOD↑,

POD↓, nitric oxide↓,GR↓,

gypsogenin-3-O-β-D-glucopyranoside↓at days 5

and 9

Qiu et al., 2021

Chitosan

(PAMP/MAMP)

1000, 2500, and 5000 mg L

−1

for 10 min Cucumber (Cucumis sativus L.) 2500 mg L

−1

: resistance against powdery

mildew disease↑, lignin↑, callose, H

↑,

germination percentage↑, seedling vigor↑

5000 mg L

−1

: seedling vigor↓

Jogaiah et al., 2020

Oligogalacturonides

(DAMP)

10, 50, 100, 200, and 400 mg L

−1

for

30 min

Beet (Beta vulgaris cv. NTG9903) 50 mg L

−1

: germination index↑, seedling

emergence↑, resistance to Rhizoctonia solani↑

10–400 mg L

−1

: growth inhibition of

Rhizoctonia solani in vitro↑

Zhao et al., 2022

Oligogalacturonides

(DAMP)

25, 50, 100, and 200 mg L

−1

in one

application

Mouse-ear cress

(Arabidopsis thaliana)

25 mg L

−1

: resistance against Pseudomonas

syringae pv. tomato↑, defense-related genes↑,

ROS↑, nitric oxide↑, jasmonic acid↑, salicylic

acid↑, bacterial growth↓

100–200 mg L

−1

: disease index by

Pseudomonas syringae pv. tomato↑

200 mg L

−1

: bacterial growth↑

Howlader et al., 2020

Harpin protein (Hpa1)

(PAMP)

10, 15, 20, 30, and 50 mg L

−1

in one

application

Crow-dipper (Pinellia ternata)15mgL

−1

: resistance against tobacco mosaic

virus↑, SOD↑, CAT↑, POD↑, PPO↑

10 and 50 mg L

−1

: protective and curative

effect against tobacco mosaic virus↓

Wang et al., 2020

Iturin A (MAMP) 64, 128, 256, and 512 mg L

−1

in one

application

Tomato (Solanum lycopersicum cv.

Cerasiforme)

512 mg L

−1

12–24 h after treatment: resistance against soft

rot disease caused by Rhizopus stolonifer↑,PAL↑,

POD↑,PPO↑,GLU↑,CHI↑,APX↑,SOD↑,CAT↑,

GR↑

36–48 h after treatment: PAL↓, POD↓, PPO↓,

GLU↓, CHI↑

Jiang et al., 2021

Chemical stressors

Humic acids 0, 0.1, 1, 10, 100, and 1000 mg L

−1

in one

application

Maize (Zea mays L.) 0.1–100 mg L

−1

↑, CAT↑, proline↑

1000 mg L

−1

↓, CAT↓, proline↓

Canellas et al., 2020

Brassica water extract Control, 0, 5, 10, 15, 20, 25, and 30 mL L

−1

in one foliar application

Wheat (Triticum aestivum L.) 20 mL L

−1

↑,R

↑,Ch↑, carotenoids↑,

SOD↑, CAT↑, POD↑,H

↓

30 mL L

−1

↓,R

↓

Khaliq et al., 2022

Wood vinegar from

Cunninghamia

lanceolata pyrolysis

0, 0.33, 0.50, 0.67, 0.80, 1.00, 1.33, and

2.00 mL L

−1

in one application

Wheat (Triticum sp.) 0.33–0.50 mL L

−1

: germination rate↑,R

↑,R

↑,

↑, malondialdehyde↓

0.67–2.00 mL L

−1

: germination rate↓,R

↓,R

↓,

↓, malondialdehyde↑

Lu et al., 2019

Moringa leaf extract Control, 0, 5, 10, 15, 20, 25, and 30 mL L

−1

in one application

Wheat (Triticum sp.) 15–20 mL L

−1

: emergence index↑,S

↑,

emergence time↓

25 mL L

−1

: emergence percentage↑,S

↑,R

↑,

↑, SOD↑, CAT↑, ascorbic acid↑,H

↓

30 mL L

−1

:Ch↑, carotenoids↑,S

↓,R

↓

Ibrahim et al., 2023b

Zinc (Zn) (essential

element)

Optimum: 0.33 mg L

−1

Zn (control) Excess:

58.84 mg L

−1

Zn for 0, 2, 3, and 8 days

Clary sage (Salvia sclarea) Day 2: photoprotective heat dissipation (Φ

NPQ)

↑

Day 3: PSII efﬁciency↑, photoprotective heat

dissipation (Φ

NPQ)

↓

Day 8: PSII efﬁciency↑, photoprotective heat

dissipation (Φ

NPQ)

↓

Moustakas et al.,

2022b

Silver nanoparticles

(AgNPs)

0, 5, 10, and 20 mg L

−1

for 20 days Tomato (Solanum lycopersicum L.) 5 mg L

−1

↓,R

↑,R

↑,S

↑,R

10 mg L

−1

↓,S

↓,R

↓

20 mg L

−1

↓,R

↑,S

↓,R

↑

Guzmán-Báez et al.,

2021

Titanium dioxide

nanoparticles

(TiO

NPs)

0, 50,100, 1000, and 2500 mg L

−1

for

3 weeks

Wild fennel (Nigella arvensis L.) ≤100 mg L

−1

↑,R

↑,S

↑, soluble

protein↑, soluble sugar↑, proline↑, SOD↑, APX↑,

CAT↑, POD↑

Chahardoli et al.,

2022

P.L. Godínez-Mendoza et al. Science of the Total Environment 894 (2023) 164883

Agronomically, biological stressors are classiﬁed into microbial extracts

(yeast extract), products containing entire cells, or speciﬁc molecules with

priming activity (Vazquez-Hernandez et al., 2019a). Within the speciﬁc

molecules with priming activity, we can ﬁnd those such as peptides,

proteins, carbohydrates, lipids, lipopeptides, nucleic acids (DNA and

RNA), phytohormones, and pheromones (Yang et al., 2022). A recent

study reported that applications of salicylic acid (SA), yeast extract (YE),

or pectin, in a concentration range from 50 to 100 mgL

−1

, increased the

Table 1 (continued)

Stressor Tested doses and exposure time Plant species Outcomes Reference

≥1000 mg L

−1

↓,R

↓,S

↓, soluble

protein↓, soluble sugar↓, proline↓,Ch↓,

carotenoids↓, iridoids↑, phenol↑,H

↑, SOD↑,

APX↑, CAT↑, POD↑

Sodium nitroprusside

(nitric oxide donor)

0, 2.97, 5.96, 8.94, 11.92, and 14.90 mg L

−1

for 45 days

Soybean (Glycine max (L.) cv.

Merrill)

2.97–8.94 mg L

−1

: explants responding↑,

shoots per explant↑,S

↑,R

↑, salt tolerance↑

11.92–14.90 mg L

−1

: explants responding↓,

shoots per explant↓,S

↓,R

↓, salt tolerance↓

Karthik et al., 2019

Silicon (Ca

Si)

(non-essential

element)

0, 60, 125, and 250 mg L

−1

for 7, 14, 21,

and 28 days

Pepper (Capsicum annuum L.) 60 mg L

−1

: free amino acids↑,R

↓

125 mg L

−1

: leaf area↑, leaf fresh and dry

weights↑,S

↑,S

↑,R

↑,P

↑,Ch↑,

soluble sugars↑,R

↓

250 mg L

−1

: stem diameter↓, free amino

acids↓, soluble sugars↓,Ch↓,R

↓

Trejo-Téllez et al.,

2020

Acephate (pesticide) 0, 150, 750, 3750 mg L

−1

for 14 days Tomato (Solanum lycopersicum L.) 150 mg L

−1

↑,S

↑,Ch↑, PSII efﬁciency↑,

SOD↑, POD↑, CAT↑, photosythesis-related

genes↑

750 mg L

−1

: cell death↑, SOD↑, CAT↑, POD↓,

photosynthesis-related genes↓

3750 mg L

−1

↑, CAT↑,P

↓,S

↓,Ch↓,

PSII efﬁciency↓, SOD↓

Xu et al., 2023

Cadmium (Cd),

chromium (Cr), and

lead (Pb) (pollutants)

Cd: 0, 0.06, 0.08, 0.11, 0.17, and

0.23 mg L

−1

Cr: 0,0.26, 0.52, 1.30, 2.60,

and 5.20 mg L

−1

; Pb: 0, 0.1, 0.2, 1.0, 1.6,

and 3.1 mg L

−1

for 4 weeks

Bittercress (Cardamine hirsuta L.),

annual meadow grass (Poa annua

L.), and chickweed (Stellaria media

L. cv. Vill.)

Cardamine hirsuta L. and Poa annua L.

0.08–0.11 mg L

−1

Cd: R

↑,S

↑, number of

nodes↑

0.23 mg L

−1

Cd: R

↓,S

↓, number of nodes↓

Cardamine hirsuta L., Poa annua L., and

Stellaria media L.

0.52–2.60 mg L

−1

Cr: R

↑,S

↑, number of

nodes↑

5.20 mg L

−1

Cr: R

↓,S

↓, number of nodes↓

Pb did not induce hormesis in the doses tested

Salinitro et al., 2021

Salt stress (NaCl) 0, 58.44, 584.4, 1168.8, and 1753.2 mg L

−1

Lettuce (Lactuca sativa L.) 584.4 mg L

−1

: cyanidin-malonyl glucoside↑

1168.8 mg L

−1

: chlorogenic acid↑,

caffeoylmalic acid↑, caffeoyltartaric acid↑,

cichoric acid↑,meso-di-O-caffeoyltartaric acid↑

1753.2 mg L

−1

: chlorogenic acid↓,

caffeoylmalic acid↓, caffeoyltartaric acid↓,

cichoric acid↓,meso-di-O-caffeoyltartaric acid↓,

cyanidin-malonyl glucoside↓

Corrado et al., 2021

Physical stressors

Electric ﬁeld with Cd

exposure

Cd: 0, 5, and 25 mg L

−1

0, 1, 2, and 3 V cm

−1

6 h per day for 1 week

Japanese honeysuckle (Lonicera

japonica Thunb.)

5mgL

−1

Cd: Rdw↑, leaf dry weight↑,Ch↑,

carotenoids↑

25 mg L

−1

Cd: Rdw↓, leaf dry weight↓,Ch↓,

carotenoids↓

2Vcm

−1

, 5 mg L

−1

Cd: Rdw↑, leaf dry

weight↑,Ch↑, carotenoids↑

3Vcm

−1

, 5 mg L

−1

Cd: Rdw↓, leaf dry

weight↓,Ch↓, carotenoids↓

Liu et al., 2023.

Ultraviolet- C (UV-C)

(electromagnetic

radiation)

0.4, 0.8, 1.2, and 1.6 kJ m

−2

four doses total

at 48-h intervals between the ﬁrst three

doses and 72 h for the last dose, 1 min per

dose of 0.4 kJ m

−2

Lettuce (Lactuca sativa L.) 1.6 kJ m

−2

: lesion area after inoculation with

Xanthomonas campestris pv. vitians↓,

differentially expressed genes involved in

growth and defense↑

Sidibé et al., 2022.

Ultraviolet- B (UV-B)

(electromagnetic

radiation)

0, 1.5, and 7.2 kJ m

−2

for 0–615 s Broccoli (Brassica oleracea) ﬂorets

(postharvest)

1.5 kJ m

−2

: color change in time↓, weight

loss↓, glucoraphanin↑, glucobrassicins↑,

phenylalanine N-hydroxylase expression↑

7.2 kJ m

−2

: color change in time↑, weight

loss↑, ORAC↑, glucoraphanin↑, phenylalanine

N-hydroxylase expression↓

Duarte-Sierra et al.,

2020.

γ-Radiation

(electromagnetic

radiation)

0, 5, 10, 15, 20, and 100 Gy at a 60 Gy per

hour rate

Barley (Hordeum vulgare L.) 5 Gy: S

↑,S

↑,R

↓,γ-aminobutyric acid

in roots↑

10 Gy: R

↓,S

↓

15 Gy: S

↑,S

↑,R

↓,γ-aminobutyric acid

in roots↓

20 Gy: R

↓,S

↓,γ-aminobutyric acid in roots↑

100 Gy: S

↓,S

↓,R

↓

Volkova et al., 2020b.

↑↓ Arrows indicate an increment or reduction of the variable in comparison to the previous dose cited or the control (for the ﬁrst dose cited).

Abbreviations: ATP, adenosine triphosphate; MAMP, microbial-associated molecular pattern; PAMP, pathogen-associated molecular pattern; DAMP, damage-associated mo-

lecular pattern; P

,plantheight;S

,shootlength;S

, shoot dry weight, S

, shoot fresh weight, R

, root length, R

, root dry weight; R

, root fresh weight; Ch, chlorophyll,

SOD, superoxide dismutase; CAT, catalase; POD, peroxidase; PAL, phenylalanineammonia-lyase; POD,peroxidase, PPO, polyphenol oxidase; GLU, glucanase; CHI, chitinase;

APX, ascorbate peroxidase; GR, glutathione reductase; H

, hydrogen peroxide; PSII, photosystem II; ORAC, oxygen radical absorbance capacity.

P.L. Godínez-Mendoza et al. Science of the Total Environment 894 (2023) 164883

total biomass and promoted the accumulation of secondary metabolites

with antioxidant activity in hassawi rice (Oryza sativa L.); nevertheless,

higher concentrations (200 mgL

−1

) of pectin had the opposite effect, de-

creasing the biomass and the content of total phenols and ﬂavonoids (El-

Beltagi et al., 2022). Zaman et al. (2022) demonstrated that the elicitation

of Ocimun basilicum with yeast extract, in a range of 1–400 mgL

−1

, pro-

moted the increase in biomass and the accumulation of ﬂavonoids and

total phenols, obtaining 100 mgL

−1

as the most efﬁcient concentration.

Chitosan, a polysaccharide stressor, at 0.5 gL

−1

has been shown to induce

the expression of defense-related genes and increase SA accumulation and

phenylalanine ammonia-lyase (PAL) activity, thereby reducing

Phytophthora infestans infection in potatoes (Zheng et al., 2021). Serrano-

Jamaica et al. (2021) reported that a mixture of fragmented DNA

(100 mgL

−1

) derived from the phytopathogens Phytophthora capsici L., Rhi-

zoctonia solani K., and Fusarium oxysporum S., increased the total content of

phenols and ﬂavonoids and the expression of defense-related genes; never-

theless, the highest concentration (100 mgL

−1

) caused a decrease in plant

height. Another study reported that fragmented DNA (2 mgL

−1

) derived

from the pathogen Phytophthora capsici increased total phenol and ﬂavo-

noid content and reduced disease severity in chili pepper plants; however,

fragmented DNA at 60 and 100 mgL

−1

did not show a protective effect

against Phytophthora capsici, on the contrary, it was observed a higher dis-

ease severity index and lower phenol and ﬂavonoid content in chili pepper

(Ferrusquía-Jiménez et al., 2022a).

The uses of whole cells comprise the application of plant growth-

promoting bacteria (PGPB) and plant growth-promoting fungi (PGPF).

PGPB and PGPF can trigger induced systemic resistance (ISR) and are also

called microbial bioagents (Naziya et al., 2020;Zehra et al., 2021). The

most relevant PGPB genera are Pseudomonas spp., Bacillus spp.,

Agrobacterium spp., Rhizobium spp., and Serratia spp. While the symbiotic

arbuscular mycorrhizal fungi, Trichoderma spp., Piriformospora indica,

Ampelomyces quisqualis,Penicillium simplicissimum,Gliocadium sp., and

Phoma sp., are some of the widely studied PGPFs (Nosheen et al., 2021).

Many studies report the beneﬁts obtained by introducing PGPB and PGPF

in agriculture. For example, one study reported that dual inoculation of

Bradyrhizobium liaoningense (rhizobia) and Ambispora leptoticha (arbuscular

mycorrhizal fungus) increased seed weight and dry biomass in soybean

under severe water stress (Ashwin et al., 2022). In addition, applying the

mycelium and cell-free culture ﬁltrate of the fungus Penicillium olsonii in-

creased biomass, height, leaf area, total chlorophyll content, and superox-

ide dismutase (SOD) and catalase (CAT) activities in tobacco (Tarroum

et al., 2022). The joint application of Trichoderma harzianum and

Trichoderma asperellum increased shikimic acid production and the activity

of defense-related enzymes in brinjal plants, improving tolerance to

Sclerotinia sclerotiorum (Pratap Singh et al., 2021).

Recent research has shown that the activity of microorganisms by bio-

logical and chemical stressors applied at different concentrations can be

modiﬁed (affected or elicited). For example, it has been reported that

using fragmented DNA (biological stressor) at 500 mgL

−1

of Phytophthora

capsici suppresses zoospore germination. In comparison, lower concentra-

tions (2 mgL

−1

) did not generate this effect but did promoteantioxidant ac-

tivity enzymes such as SOD and CAT in this pathogen in in vitro assays;

moreover, concentrations of 100 mgL

−1

increased Phytophthora capsici

pathogenicity (Ferrusquía-Jiménez et al., 2022a). In addition, different

studies report the elicitation of microorganisms using nanoparticles, a

chemical stressor (Ferrusquía-Jiménez et al., 2022b;de Moraes et al.,

2021;Boroumand et al., 2020;Tian et al., 2020). One study reported that

SiO

nanoparticles (NPs) at 100 mgL

−1

enhanced the role of a Bacillus ce-

reus strain as PGPB by enhancing its phosphate solubilization capacity, gib-

berellin production, and antioxidant enzyme activity (Ferrusquía-Jiménez

et al., 2022b). Another study shows that the in vitro application of nano-

silica at 0.07 mgL

−1

promoted the increase in the population of the

phosphate-solubilizing bacteria Mesorhizobium sp. and Pseudomonas stutzeri;

moreover, the joint application of nano-silica at 100 mgL

−1

and these same

strains beneﬁted the growth and development of watercress (Barbarea

verna)(Boroumand et al., 2020).

Previous reports showed the possibility of using different stressors to

improve PGPB yield in soil. These ﬁndings create a new scenario in

which it would be possible to apply different stressors in high or low

doses to plants and soil microorganisms to cooperate with the creation of

a sustainable biosystem that favors obtaining proﬁtable and quality crops

(Vazquez-Hernandez et al., 2019a;de Moraes et al., 2021). The discovery

of molecules with eliciting activity is a feasible strategy in the global trends

that pointtowards using innocuous molecules to generate positive hormetic

responses in crops of agricultural importance. The regulation of plant and

microbial hormesis through managing stressors represents an effective

line of research for developing technological products.

3.2. Chemical (biological and non-biological origin)

Secondary metabolites are chemical compounds speciﬁcally synthe-

sized to modulate stress responses and ecological interactions. Due to

their origin, these compounds can be considered biological and chemical

stressors. The hormeticresponses of crops to phytohormoneshave been dis-

cussed in the previous section. Thus, in this section, we will cover plant re-

sponses to secondary metabolites other than phytohormones, which have

also been widely proposed to improve desirable agricultural characteristics

in crops, such as yield and quality (Zulﬁqar et al., 2020).

Secondary metabolites are fundamental in plant communication under

stress conditions and hence induce adaptive responses in crops when

applied pure or as extracts. Although many authors report only applica-

tion doses with the best results, hormesis, which covers low-dose stimu-

lation and high-dose inhibition, fr equently occurs in studies that include

non-optimal doses (Pannacci et al., 2022;Perveen et al., 2020;

Ghaderiardakani et al., 2019). Moreover, secondary metabolites are

stressors that may elicit speciﬁc adaptive responses as they mediate eco-

logical interactions. Speciﬁc adaptive responses result from constant

stress exposure or long-experienced ecological interactions during the

evolution of a particular population, and, as non-speciﬁc responses,

they can be explained by the hormetic model (Erofeeva, 2022a). In

this context, essential oils, rich in volatile and defensive metabolites,

have also been shown to elicit desired responses in crops, such as seed-

ling growth (Souri and Bakhtiarizade, 2019), the activation of antioxi-

dant defense, and stress-related gene expression, leading to pest

resistance (Rashad et al., 2022;Vega-Vásquez et al., 2021). Addition-

ally, it has been suggested that other non-monophasic dose responses

caused by these stressors are mechanistically related to hormesis

(Erofeeva, 2020). Such responses, also known as paradoxical effects,

were observed for mung bean shoot and root growth (Vigna radiata)

after applying aqueous extracts of the marine algae Sargassum horridum

and Gracilaria parvispora (Hernández-Herrera et al., 2022).

Low-dose stimulation is a conserved phenomenon linked to biological

plasticity (Calabrese and Mattson, 2011). On this basis, it has been hypoth-

esized that its origin could be traced to a common unifying mechanism

(Erofeeva, 2022a), which has been proposed to be associated with

oxidative stress (Calabrese and Kozumbo, 2021). Redox adaptation is a

non-speciﬁc cytoprotective mechanism, and chemicals from oxidative pro-

cesses, such as hydrogen peroxide (H

), are hormetins (i.e, hormesis in-

ducers) ubiquitous in plant systems (Sonmez et al., 2023). At nanomolar

concentrations, hydrogen peroxide functions as a signaling molecule

linking signal transduction pathways during stress responses, while it pro-

vokes oxidative damage at higher doses, ultimately leading to cell death

(Nazir et al., 2020). Understandably, this molecule also stimulates positive

traits in cropsin a dose-dependent manner (Sonmez et al., 2023). Hydrogen

peroxide, applied in vitro, in planta, and as a pre-germination treatment,

stimulates antioxidant defenses and phenolics biosynthesis with important

implications for food quality (Goncharuk et al., 2022a;Delis-Hechavarría

et al., 2021;Gómez-Velázquez et al., 2021). However, as a general oxida-

tive stress signaling molecule, exogenous hydrogen peroxide affects many

other endpoints, including growth, photosynthetic rate, phytohormone bio-

synthesis, secondary metabolite biosynthesis, and cross-stress tolerance

(Hu et al., 2023;Singh et al., 2021;Jamaludin et al., 2020).

P.L. Godínez-Mendoza et al. Science of the Total Environment 894 (2023) 164883

Remarkably, constant environmental stimuli can also induce adaptive

hormetic responses in plants (Erofeeva, 2022b;Agathokleous, 2018). In

contrast to abrupt stress, the basal level of environmental stimuli is not

zero. Instead, plants can be exposed to an optimal or a non-optimal level,

the latter resulting in the activation of the adaptive defensive system

according to the hormetic model (Erofeeva, 2021). This explains why

non-optimal levels of nutrients and essential elements also increase the pro-

duction of ROS and activates antioxidant defenses (Tewari et al., 2021)and

can be used in agriculture as stimulants, fertilizers, and priming agents

(Kumari et al., 2022;Mason et al., 2022;Rahimi et al., 2022). Alternatively,

hormesiscaused by hazardous substances and pollutants has relevant impli-

cations for phytoremediation and improving agricultural productivity in

stressful environments (Shahid et al., 2020). For example, low levels of cad-

mium (Cd) and lead (Pb) stimulate antioxidant and photosynthetic activi-

ties via the stimulation of phenylpropanoid, auxin, and hydrogen

peroxide biosynthesis and the activation of antioxidant enzymes (Wang

et al., 2023;Małkowski et al., 2020). Furthermore,pollutants and even her-

bicides,such as ozone and glyphosate, have also been proposed as priming

agents to improve crop yield under stressful conditions due to their effec-

tiveness in activating plant defenses and metabolism (Risoli and Lauria,

2022;Santos et al., 2021).

The advent of nanotechnology has favored the research and develop-

ment of a wide range of chemical formulations for improving crop perfor-

mance. Nanostructured materials of diverse composition act as stressors

and stimulate plant redox defenses in a dose-dependent manner

(Agathokleous et al., 2019d). This fact has led to the emergence of diverse

nanofertilizers, nanopesticides, and nanoherbicides (Xin et al., 2020), of

which 244 are products currently on the market (StatNano, 2023). In addi-

tion, nanomaterials, particularly nanoparticles (NPs), have the advantage

of having a much larger surface area than bulk materials due to their

small size. Thus, NPs achieve the desired effects at a lower application

dose than conventional chemical stressors, diminishing the amount of prod-

uct that reaches the environment (Xin et al., 2020). NPs of metallic ele-

ments and compounds are most studied in agricultural research. For

example, titanium (Ti), palladium (Pd), gold (Au), and silver (Ag) NPs acti-

vate antioxidant defenses, improve the photosynthetic rate, and stimulate

plant metabolism, leading to improved yields (Shabbir et al., 2019;

Castro-González et al., 2019;Singh et al., 2019). However, high production

costs as well as the implications concerning their environmental impact

hinder the use of NPs in real agricultural applications (da Silva Júnior

et al., 2022;Pérez-de-Luque, 2017).

Allowing for environmental risks, nanomaterials that are considered in-

nocuous, such as silicon (Si) and graphene, have also been tested and

shown to induce hormesis in growth, germination, specialized metabolites

synthesis, and cross-stress tolerance (Magaña-López et al., 2022;Ren et al.,

2016). Likewise, nanoforms of essential metals, such as copper (Cu), zinc

(Zn), and iron (Fe), have been shown to elicit hormetic responses and im-

prove agricultural traits in crops with apparently fewer ecological risks

(Kolbert et al., 2021). Nevertheless, the physical and chemical properties

that confer NPs with such great potential to stimulate plants in

agroecosystems also inﬂuence how they interact with natural ecosystems

since their stimulatory dose range depends on the endpoint, genetic iden-

tity, developmental stage, and precondition of the responding organism

(Agathokleous et al., 2019d). Therefore, hormesis must also be incorpo-

rated into risk assessment practices before introducing any chemical

stressors to agroecosystems at an industrial scale. Several additional exam-

ples of reported hormetic effects of chemical stressors on plants are shown

in Table 1.

3.3. Physical

3.3.1. Temperature

Temperature has a crucial role in global change biology, as the average

global surface temperature appears to have increased during the last de-

cades (Agathokleous et al., 2019c). Although this type of stress can have

an antagonistic effect on stabilizing membrane integrity, it will also alter

the concentration of secondary metabolites and the chemical composition

found in the plant (Jamloki et al., 2021). This means that it can induce

eustressif handled properly especially with access to greenhouses withtem-

perature control, making it practical in agriculture. Obviously, the study is

complicated when the stressor is an environmental factor such as tempera-

ture due to technical difﬁculties compared to studies with chemical agents

(Agathokleous et al., 2019c). On the other hand, the growth and develop-

ment of the plant are directly related to the temperature to which the

plant is exposed (Li et al., 2020); further, depending on the temperature

stress, the plant can respond differently in the production of secondary me-

tabolites, which have several applications. Some authors have reported in-

dications of hormetic response to temperature in several endpoints of

different plant species. Cawood et al. (2018) investigated the effect of tem-

perature on the production of secondary metabolites of Amaranthus

cruentus. They revealed that growing the plants at a temperature of 28/

21 °C resulted in a higher content of secondary metabolite compounds

than plants grown at lower (14/17 °C) or higher temperatures (33/40 °C).

Hormetic responses were observed in Phaseolus vulgaris L. exposed to differ-

ent levels of air temperature at 82 days after seeding (Agathokleous et al.,

2019c). Moreover, Slot and Winter (2016) suggested that the temperature

where the maximum plant growth occurs reﬂects theoptimum temperature

for photosynthesis inthe short-term temperature response, and displays re-

sponses towards increasing or decreasing photosynthesis, depending on

growing plants under warmer or hot conditions provoking those pheno-

types. This is an interesting proposal that falls within the concept of

hormesis as shown in animal models (Calabrese, 2016).

Another study by Song et al. (2022) reported an optimal temperature of

0°Cforcoldstratiﬁcation in which stimulation was observed in the germi-

nation of Pinus koraiensis seeds. It was noted that seed germination at low

spring temperatures is an effective measure for both the growth and sur-

vival of plants in temperate forest ecosystems.

Studies applying temperature at pre- and post-harvest stages have been

carried out. Low-temperature rates (sub-optimal growing temperature)

have been found to be effective in improving the overall quality of fruits

and vegetables under pre- and post-harvest conditions. Temperature expo-

sure of 35 °C during the pre-harvest of tomato fruits improved tolerance to

oxidative damage, biosynthesis of phenolic compounds, and maintenance

of fruit quality (Toscano et al., 2019).

3.3.2. Electromagnetic radiations

As it has been known, extended photoperiod or the use of complemen-

tary electromagnetic sources such as visible light (VIS) can increase plant

growth, development, and production of secondary metabolites (Aguirre-

Becerra et al., 2020). Low doses of (4–6kJm

−2

) UV-C treatments of tomato

seeds displayed control of disease of Botrytis cinerea and Fusarium

oxysporum, as well as 8 kJm

−2

showed biostimulation of plantlets; with

higher doses displaying a reduction in seed germination and plantlet perfor-

mance (Scott et al., 2019). Thus, variations in photoperiod, intensity, and

wavelength might not only alter the conversion efﬁciency but also trigger

various plant adaptation mechanisms, indicating the possibility that elec-

tromagnetic radiation might induce hormesis.

The response to other types of low-dose radiation can be observed as in-

creased growth, accelerated development, increased tolerance to stressors,

and accumulation of secondary metabolites of interest (Volkova et al.,

2022). An example is the results of Chang et al. (2020), where they treated

Arabidopsis thaliana plants with gamma rays at different time intervals. Irra-

diated plants initially showed an irregular growth pattern; however, in the

late stages of development, these plants presented a larger projected area

than the control group. According to Volkova et al. (2020a), gamma irradi-

ation of barley seeds promotes growth stimulation. They performed a com-

plete transcriptome analysis and found that low-dose irradiation induced

growth stimulation and found genes involved in transcriptional control of

genes related to phytohormones, proteins, and cell wall components.

Non-ionizing radiation, such as UV-B, can also trigger hormetic re-

sponses in plants. Although the absorption of UV-B photons can damage

biomolecules, it has also been reported to generate positive effects such as

P.L. Godínez-Mendoza et al. Science of the Total Environment 894 (2023) 164883

growth stimulation, resistance to pathogens, and stimulation of secondary

metabolism (Martínez-Zamora et al., 2021). In the case of LED irradiation,

exposure of Artemisia annua to [Red: Blue] LED radiation at a ratio of [7:3]

in combination with dehydration for 6 was reported to double the biosyn-

thetic yield of artemisinin, a potent antimalarial, antibacterial, antiviral,

and antitumor metabolite (Kim and Hwang, 2022).

3.3.3. Magnetic ﬁelds

Exposure to magnetic ﬁelds has shown its feasibility for improving the

germination rate of crop seeds. Its application in plants also increases root

and shoot growth, productivity, photosynthetic pigment content, and

water and nutrient uptake (Sarraf et al., 2020). A research focused on

water treatment by magnetic ﬁelds, resulted in improved water quality

and crop productivity. This study reported that using magnetically treated

water could improve agricultural production and lettuce seed germination

(Mghaiouini et al., 2020).

Paponov et al. (2021) used Arabidopsis thaliana to elucidate the effect of

applying the geomagnetic ﬁeld (GMF). They found that GMF regulates

genes in shoots and roots and approximately 49 % of the genes were regu-

lated in the reverse direction, indicating that those deﬁning up-regulation

and down-regulation are resident signaling networks. They also observed

that genes regulated by GMF overlapped with stress-sensitive genes, sug-

gesting the involvement of common signals such as reactive oxygenspecies.

Although currently, GMF modiﬁcations have only been applied in plant sci-

ence research, there is an opportunity to develop new technologies in agri-

culture as near-null magnetic ﬁeld (NNMF) to apply GMF to improve crops

(Paponov et al., 2021).

3.3.4. Drought

Drought is the main limiting factor for crop productivity and affects

physiological and biochemical processes. Plants respond to drought by clos-

ing stomata, reducing CO

input to the leaf, and decreasing photosynthesis,

resulting in decreased synthesis of essential organic molecules (Moustakas

et al., 2022a).

While several recent studies use chemical or biological factors, such as

Brassica water extract, to improve the drought tolerance of plants

(Ibrahim et al., 2023a), there are also reports that drought itself is used to

induce eustress. This could be achieved by the strategy calledregulated def-

icit irrigation (RDI) as recently demonstrated in pear production (Vélez-

Sánchez et al., 2021). RDI is where water is applied in smaller amounts in

the vegetative cycle of the crop and the necessary amount during the rest

of the phenological cycle (Vélez-Sánchez et al., 2021). Paim et al. (2020)

evaluated the effect of applying moderate drought levels on lettuce before

and after harvest since the post-harvest stage is characterized to be stressful

and results in lower quality of the vegetable. It was reported that the appli-

cation of moderate drought using water necessary to saturate 90 % of the

soil (DS 90 %) resulted in higher biomass. In comparison, lettuce applied

with DS 80 % presented better quality indicators, such as higher content

of carotenoids, chlorophylls, caffeic acid, monocaffeoyl tartaric acid,

malecyl quercetin glycoside, quercetin-3-O-glucuronide, as well as in-

creased antioxidant activity at harvest.

In the case of Saposhnikova divaricate, it was reported that in drought

stress (several days of withholding water and then rewatering), plant toler-

ance was due to the activation of the antioxidant system and the accumula-

tion of osmolytes. It was also observed that moderate and severe drought

stress promoted the accumulation of the bioactive secondary metabolites

prim-O-glucosylcimifugin and 4′-O-β-D-glucosyl-5-O-methylvisamminol

(Men et al., 2018).

3.3.5. Acoustic emissions

It has been observed that acoustic emissions from ecological conditions

and artiﬁcial sources can trigger signal transduction cascades similar to

other abiotic stressors (Alvarado et al., 2019). A study conducted by

Caicedo-Lopez et al. (2021) reported that they used low-water stress

(LHS), medium-water stress (MHS), and high-water stress (HHS) acoustic

emission patterns to evaluate their effect on well-watered plants in both

vegetative and fruiting stages. The acoustic emissions were gathered

using a sensor to detect the emissions made by Capsicum annuum plants in

LHS, MHS, and HHS. It was reported that in the vegetative state, acoustic

emissions from HHS were the best to up-regulate peroxidase, superoxide

dismutase, and phenylalanine ammonia-lyase genes, while the chalcone

synthase gene was induced by acoustic emissions fromMHS. In the fruiting

stage, the acoustic emissions of MHS were the ones that signiﬁcantly in-

creased the production and accumulation of capsaicin.

Another type of sound stress is ultrasound, which can promote the bio-

synthesis of compounds that promote the health and physiological attri-

butes of lettuce, strawberry, carrot, and broccoli. Furthermore, its

application as a pre-treatment in seeds improves sprouting indexes, the con-

tent of health-promoting compounds, and the quality characteristics of

sprouts (Jacobo-Velázquez and Benavides, 2021). The application of ultra-

sound for 20 min at a frequency of 24 kHz in broccoli ﬂorets (Brassica

oleracea L.) increased phenolics, glucosinolates, and glucobrassicin

(Aguilar-Camacho et al., 2019). In the case of the common bean

(Phaseolus vulgaris), the accumulation of total phenolic acids, ﬂavonoids,

and anthocyanins increased with 360 W (60 min) of ultrasound treatment.

It also increased sprouting percentage, index, and vigor, improving the

quality of the bean sprouts. Furthermore, it was reported that the produc-

tion of hydrogen peroxide and the activity of catalase, glutathione peroxi-

dase, phenylalanine ammonia-lyase, and tyrosine ammonia lyase were

increased (Ampofo and Ngadi, 2020). Additional physical stressors evalu-

ated at the hormetic level in plants are shown in Table 1.

4. Effects of genotypic variation and phenological stage on plant

hormetic response

Plant phenology refers to a succession of events that deﬁne the essential

biological stages inthe development of plants; the moment of the phenolog-

ical stage (PS) plays a fundamental role in the balance of the ecosystems, in-

cluding now the agricultural ecosystems (Fu et al., 2022). PS is the result of

multiplemetabolic networks ﬁnely regulated by environmental and genetic

factors (Nord and Lynch, 2009). To reach the aim of each stage, the plants

must manage the energy obtained by the primarymetabolism and establish

a plastic balance between the most important biological events, which can

be classiﬁed as growth, reproduction, and defense (Lambers et al., 2008).

There have been reports on molecular interactions between signaling

pathways underlying plant switch to a new PS, but also effects of the PS

in signaling pathways activation, mostly related to defense. Both biotic

and abiotic stresses have been reported to activate defense responses differ-

ently depending on the PS of the evaluated plant; for example, melon plants

have been reported to develop a higher severity score by Acidovorax citrulli

at the seedling stage rather than plants before ﬂowering, and fruiting

stages, similarly to Cucurbitaceae species facing fruit blotch (de Assunção

et al., 2021). As an example of physical stress, on the one hand, quinoa

plants are more susceptible to frost at ﬂowering stages (from bud formation

to anthesis) compared to the vegetative stages (Jacobsen et al., 2005). On

the other hand, soybean plants haveshown the same resistance level to in-

fection by Phytophthora sojae regardless of the PS of inoculation. Those

mentioned above may suggest that the plant stage affects not only one

but multiple defense signaling pathways.

In other essays, depending on the evaluated accessions, plant defense

responses to the same stressors differ by PSs. Gieco et al. (2004) indicate

that interactions between resistance to Septoria tritici in wheat and PSs de-

pend on the genotypes involved. This suggests the existence of stage-

speciﬁc resistance genes in wheat, comparing the susceptibilityof different

genotypes to S. tritici.

Since 1994, a growth-differentiation balance hypothesis (GDBH) has

been proposed. It explains the allocation of resources from primary metab-

olism into secondary metabolism depending on various factors (Lerdau

et al., 1994). One of them was limiting resources that would prioritize the

secondary metabolism over the primary to assure plant survival. Another

reason for resource allocation was case-speciﬁc, depending on stimuli of

the environment, such as the presence of danger signals demanding the

P.L. Godínez-Mendoza et al. Science of the Total Environment 894 (2023) 164883

production of defense secondary metabolites. Finally, the PSs were re-

ported to shape the balance of nutrients in the plants (Lerdau et al., 1994).

In general, the capacity to regulate the activation of signaling pathways

resulting in the production of speciﬁc metabolites and their amount de-

pending on external stimuli appears to represent a selective advantage for

plants. The metabolism of carbohydrates in plants has dramatic changes

in distribution, storage, synthesis, and usage along the different PSs of the

plants. One of the most sophisticated defense mechanisms is the production

of the so-called secondary metabolites. Those related to pollinator attrac-

tion have shown a negative correlation to the stages of plant growth by

shiftingthe distribution of carbohydrates (Morshedloo et al., 2018). As a re-

sult, PS reports different amounts and proﬁles of secondary metabolites.

The highest production of carvacrol, an important monoterpene has been

reported in the early vegetative stage compared to the ﬂowering, seed set,

and later vegetative stages (Morshedloo et al., 2018). Conversely, the over-

all antioxidant activity and essential oil production were higher at the

ﬂowering stage.

Evidence shows that synthesizing sugars, such as trehalose-6-phos-

phate, sucrose, and glucose, regulates growth and differentiation in plant

cells, to initiate the ﬂowering process and induce new PSs (Cho et al.,

2018). As reviewed by Rosa et al. (2009), while some stressors increased

solublesugar concentration, others decreased it showing a relation between

stress factors, metabolic pathways activation and, therefore, PS regulation.

Recently, a long-held hypothesis about the resource allocation in plants

driven by the selective agricultural pressure that seeks to increase yield has

been addressed. Whitehead and Poveda (2019) have reported a negative re-

lationship between fruit size and phenolic compounds present in apple

plants of 52 wild and 56 domesticated different genotypes. As phenolic

compounds are strongly related to plant defense, this pattern may indicate

a clear trade-off between defense and yield in various divergence scales. Al-

though, it is feasible to expect that the application of stress factor in speciﬁc

doses, related to the adaptability during the plant PS, might produce high

yield and metabolite contents (Fig. 1).

On a molecular level, some master molecules have been addressed as

regulators of the growth-defense trade-off. Cytokinin applications in plants

have been linked to salicylic acid dependent resistance to biotrophic path-

ogens and, at the same time, regulate important growth functions such as

cell replication and meristem function (Albrecht and Argueso, 2017). The

transcription factor HBI1 largely related to plant growth, weakens the oxi-

dative burst displayed as one of the ﬁrst defense lines in the apoplast, in

order to prevent the rigidity of cell walls that does not allow the cells to

grow (Neuser et al., 2019). Plants have responded to jasmonic acid treat-

ment with a reduction of essential components for light harvesting,

impacting on the photosynthesis, plant ﬁtness and overall growth (Guo

et al., 2012). Multiple molecular mechanisms have been detailed in recent

reviews (Chan, 2022;Figueroa-Macías et al., 2021;Whitehead and Poveda,

2019).

The doses of stress factors application may activate different responses

depending on the PS as well. Rostami et al. (2022) obtained higher

chalcone synthase expression in Scrophularia striata plants with a higher

dose (300 μg/mL) application of jasmonic and salycilic acid in reproductive

phase but higher expression with lower doses (100 μg/Ml) of the same hor-

mones when applied at vegetative phase. At the contrary, the expression

was down-regulated at higher doses of gibberellic acid in reproductive

phase but higher at vegetative phase.

Even as some negative interactions between signaling networks have

been addressed, such as the salicylic acid and ethylene pathways with the

auxins signaling, the ethylene biosynthesis and signaling (also related to de-

fense mechanisms) have been strongly related to excision-induced adventi-

tious roots formation in several plants as reviewed by Druege et al., 2019,

being thisa cell differentiation event that is not exclusive of any PS but a re-

sponse to multiple environmental stimuli. Seeming the interactions be-

tween pathways is a ﬁnely regulated mechanism developed to diversify

the responses to environmental signals.

With all the new evidence it seems that, each defense signaling pathway

remains related to plant growth pathways in a different way, some may

display compromising trade-offs, but some others can act at the same

time and even potentiate each other obtaining plants with stronger and

faster growth that are continuously activating their defenses responses

and producing secondary metabolites of interest. Therefore, it is essential

to characterize such changes at these levels of regulation to manage plant

stress responses adequately in order to ﬁnely design controlled elicitation

strategies to decrease incidences and severity of plant diseases with a sus-

tainable approach. Thus it is clear that PS should be considered in plant

hormetic studies using controlled stress management strategies (Guevara-

González and Torres-Pacheco, 2022).

5. Considerations regarding hormesis transgenerational effects in

plant stress management

5.1. Transgenerational effects

Hormesis occurred naturally under abiotic, biotic, or anthropogenic

stressors allowing plants to cope with environmental challenges and in-

crease resilience to impacts of stress, through the overcompensation of

plant parameters and preconditioning (Erofeeva, 2022a). The precondition-

ing concept resemblesothers such as stress memory and priming in the fact

that all of them refer to the lasting effect in the near future or even on sub-

sequent generations increasing plant resistance and cross-adaptation as

hormesis transgenerational effects (HTE) (Erofeeva, 2022b). Consequently,

the term transgenerational hormesis has been described in a wide range of

organisms including microorganisms, animals, and plants in which the

hormeticeffects might remainin the offspring as tools to cope with environ-

mental challenges (Agathokleous et al., 2022;Zhang and Tian, 2022).

In plants, hormetic studies are more recent, and those with a

transgenerational evaluation are even fewer. The principal HTE described

in plants are for herbicides and heavy metals present in soil (Erofeeva,

2022a). In the case of heavy metals, plants accumulate them in a biphasic

dose-response correlation, where hormetic responses in growth parameters

and antioxidant activity are key factors in the plant biological plasticity to

accumulating heavy metals. Additionally, if it is true that the effects in

plants are dependent on the species, and metalused, there should be a com-

mon mechanism that may suggest a highly generalizable adaptive strategy

(Calabrese and Agathokleous, 2021). Therefore, there is a high probability

that this may occur also at the HTE. Regardless of heavy metals, the HTE

has been described in rice to mild stressor concentration (50 μM) of copper

(Cu), cadmium (Cd), chromium (Cr), and mercury (Hg) as enhanced toler-

ance to metal stress across two generations. The mechanism behind this is

related to epigenetic modiﬁcations, speciﬁcally tested DNA methylation

patterns of CHG hypomethylation and also, altered state transcript levels

of chromatin-related genes, which remain in the offspring (Ou et al.,

2012). In addition, changes were identiﬁed as up-regulation of heavy

metal-transporting P-type ATPases genes in response to heavy metal stress,

which remain after the removal of the heavy metals and across three gener-

ations (Cong et al., 2019). Other case of HTE reported was in Arabidopsis

treated with chromium (Cr) at long chronic stress (2.5 μM until harvest)

and medium chronic stress (5 μM for three weeks). Severe stress triggered

the best response on the offspring, which displayed a higher germination

rate, reduced hydrogen peroxide levels, and active transcriptional regula-

tion involved in Cr stress. Changes in the transcriptome correspond to an

up-regulation of ion transport and homeostasis, and a down-regulation of

defense, detoxiﬁcation, stress perception, and TFs, which are believed to

be a ﬁne-tuning regulation in which the Cr adaptation-related genes are in-

creased and genes with a possible deleterious effect on key physiological

process are down-regulated (Colzi et al., 2023). Similarly, tomato plants

cultivated in soil with Cd 6.9 mg kg

−1

showed improved tolerance to Cd

toxicity in the progeny, which presented elevated germinability, reduced

leaf area, and increased carotenoids and chlorophyll content. Interestingly,

these parameters were increased in the presence of Cd 35 μM in comparison

to absence ofCd, suggesting the preconditioning and activation of plasticity

according to the Cd threshold (Nogueira et al., 2021). It has been reported

that Cd exposure induces changes in histone modiﬁcations and DNA

P.L. Godínez-Mendoza et al. Science of the Total Environment 894 (2023) 164883

methylation in plants, which might be involved in the altered state in gene

expression to develop HTE (Carvalho et al., 2020).

Preconditioning with herbicide hormesis has also been studied in the

growing herbicide resistance in weeds due to a reduction in the sensitivity

of growth in the offspring ﬁtness, making weed control difﬁcult in agricul-

ture. Herbicide hormesis-induced adaptations of weed can favor propaga-

tion of tolerant phenotypes, and the overlapping doses of herbicide used

in crops might act as a stressor to enhancing the weed survival. Addition-

ally, in non-target plants a hormetic response to low dose stimulation

occurs, but there is little information about it (Belz, 2020;Belz and

Sinkkonen, 2021). UV-B also has shown a transgenerational effect in Pinus

radiata, for which the progeny of stressed parents displayed a proteome

remodeling driven by a rearrangement in secondary metabolism to reduce

photooxidative damage, lipoperoxidation and promote photorespiration

and redox homeostasis for maintaining photosynthesis (García-Campa

et al., 2022). There are few hormetic studies within the literature,

and even less with a HTE considered; however other evidence of

transgenerational memory in response to stressors priming is mentioned

in others assays (Walter et al., 2013;Avramova, 2015;Villagómez-Aranda

et al., 2022). It is probable that, although it has not been considered,

there is a hormetic response involved in the transgenerational features

inherited to the offspring as a result of priming (Belz and Sinkkonen,

2021). However, there is a need for more studies to elucidate the mecha-

nism and propose detailed protocols for speciﬁc plant species in particular

conditions to be exploited in agriculture.

5.2. Perspectives for plant breeding and stress management

Hormetic preconditioning using different stressors to enhance resilience

to subsequent stresses and improved growth and productivity (biostimula-

tion/elicitation) is a potential tool to develop smarter crops, more adapted

to the extreme and changing climate conditions, pests, and pathogens

(Erofeeva, 2022c;Villagómez-Aranda et al., 2022;Gallusci et al., 2023).

Global change increases the frequency of stressful conditions for plants,

thus making necessary the development of broad-spectrum resistance of

crops. In this context,priming is an interesting tool for plant breeding pur-

poses. However, there are still unanswered questions regarding stress mem-

ory. The epi-breeding strategies consider that induction of epigenetic

modiﬁcations can lead to epi-alleles variants that affect stress resilience

through transgenic, environmental, or chemical induction. Even a research

consortium working with crop epigenomics, called EPICATCH, has been

launched to reach sustainability in the agriculture system (Mladenov

et al., 2021). However, there is a need for more investigation in this ﬁeld,

especially considering the possibility of HTE to get the maximum stimula-

tory dose (“M”dose, Fig. 1) to enhance traits of interest and reach stress re-

sistance efﬁcacy at a reliable cost due to the low doses needed for the

priming process (López-Sánchez et al., 2021).

Additionally, the induction of hormetic effects with transgenerational

stability provides the possibility of increasing innate immunity and stress

response capacity without forcing the biological system and without reduc-

ing genetic diversity (Villagómez-Aranda et al., 2022). An interesting con-

sideration is that a multiple selection of progeny with variety and

different degrees of traits and ﬁtness might occur, increasing the diversity

of phenotypes available in the genetic background of the offspring origi-

nated from a parental group (Constantini and Marasco, 2022). Another in-

teresting observation is that transgenerational stability seems to be related

to the stress level that parents experienced, thus suggesting that plants use

stress levels as an environmental proxy in order to adjust the energy cost to

invest in transgenerational priming (López-Sánchez et al., 2021). Likewise,

genetic heterogeneity is dependent on the speciﬁc physiological stage of the

plant, and the parts from which the seeds are produced (Sobral and

Sampedro, 2022). Fig. 3 shows a scheme that represents the potential use

of priming agents in crop breeding. In this sense, the objective is the induc-

tion of plant cross-tolerance to multiple stress factors from a single stressor

priming, which can be affordable to a certain degree, but this will depend

on the overlapping between the stressor responses and the other

stress-speciﬁc signaling that drives transcriptional, protein, metabolic

and morphological changes (Erofeeva, 2022b).

Fig. 3. Transgenerational hormetic induction in crops. In order to determinate a priming agent (P) optimum dose to enhance the phenotype and resilience of a crop, an

hormetic curve of dose-response must be performed. Later, the tolerance in ﬁeld conditions must be tested in the parental line and determinate the stability in the next

generations. Ideally,it would be desirable for the system to be resistant to other types of stresses that occur during the life of the crop.

P.L. Godínez-Mendoza et al. Science of the Total Environment 894 (2023) 164883

There arestill challenges tosolve in further studies, suchas the hormetic

trade-offs (stimulation of some plant traits and the deterioration of others)

and the hormesis trade-offs according to species/populations/plant

development stage/environmental conditions (Erofeeva, 2022b), as well

as the inﬂuence of culturing practices like fertilization or pesticide applica-

tions. Also, we should better understand the ecological and evolutionary

implications resulting from the resources/energy cost of the hormetic

reconditioning and the possibility of it leading to adverse outcomes

(Agathokleous et al., 2022). It should be noted that, if thecues transmitted

from the parental cultivation conditions differ from those of the offspring

(for example, light conditions), the ﬁtness of the offspring could be affected

negatively (Galloway and Etterson, 2007). Therefore, there must be a spe-

ciﬁc selection of the optimum hormetic stimulus according to the biological

system to be applied to, considering that sacriﬁces in parental line and HTE

may remain across generations. This could also be true for features that may

not be observable in the ﬁtness traits, but are relevant for stress resistance.

Therefore, the determination of speciﬁc protocols for implementing

stressors is needed, although it is true that it represents a great challenge,

but it is required in the design of intelligent precision agriculture

(Agathokleous et al., 2022).

Finally, it is also important to consider that hormesis occurs at all bio-

logical levels (cells, organisms, populations, and communities) and in dif-

ferent types of organisms (plants, animals, microorganisms). The impact

of an alteration in environmental hormesis might be proportional to the

role in the ecosystem of the altered organism (Erofeeva, 2022c). Such

that, hormesis-based interventions can potentially reduce contamination

by agrochemicals, improve the bioremediation of affected systems, and en-

hance plant productivity and health (Agathokleous et al., 2023). However,

the ecological consequences on the soil and environmental health need to

be considered for hormesis-based tools to be successfully provided and ap-

plied for next generation plant breeding.

6. Concluding remarks

Having mentioned the above, it isevident that in a study on the manage-

ment of stressors in plants under a hormesisscheme, the doses that limit the

eustress zones in the response could be predicted, even “M”dose, as well as

the NOEL and NOAEL areas of the response before reaching toxicity scenar-

ios (Figs. 1 and 2). The “M”dose for a stressor applied to the cropsuggests

that it is located within an area where biostimulation and elicitation are at a

level that can promoteboth growth and development with an adequate ac-

tivation of plant defenses (Figs. 1 and 2). The preceding could be consid-

ered a scenario for crops produced either at protected or open-ﬁeld levels

when, for example, maximum yield is needed with an adequate level of im-

munity in the plant. It is important taking in mindthat, at a higher dose, this

immunity would increase, sacriﬁcing yield and could even be toxic

(i.e., excessive elicitation by ROS production thus leading to plant distress,

therefore with no observation of biostimulation in the curve; Figs. 1 and 2;

Sonmez et al., 2023). This last statement can sometimes be of higher impor-

tance, for example, when the ﬁnal yield is based on the production of a me-

tabolite of interest in the plant and not biomass yield as in the case of the

medicinal species “chilcuague”(Heliopsis longipes)toproduceafﬁnininits

roots (Parola-Contreras et al., 2020). Thus, we can hypothesize that, within

the eustress zone, at a higher dose from NOEL to M, more energy is

channeled towards biostimulation and less to elicitation (Wang et al.,

2022). On the other hand, from dose M to NOAEL, there must be an oppo-

site effect, the energy directed towards biostimulation gradually decreases,

and the energy channeled towards elicitation increases. However, out of

the hormetic (eustress)zone, the energy channeled to elicitation is in excess

(distress) causing toxicity and no biostimulation can be observed (Figs. 1

and 2). Several future studies should focus in testing this latter hypothesis,

likely including searching for “hormetic markers”at physiological, bio-

chemical, molecular, and epigenetic levels associated to eustress and dis-

tress zones in the hormesis curve. It is also clear that multi-omics and

machine learning approaches will be highly helpful in this complex task

(Rico-Chávez et al., 2022). These responses could be estimated by

measuring different output variables in studies based on experimental de-

signs that consider the possibility of hormesis at protected or open-ﬁeld

levels. In this way, an application scheme for stress management might be

proposed as a tool for the integrated management of pests and diseases,

as well as biomass or metabolites yield increase in crops (Desmedt et al.,

2021;Guevara-González and Torres-Pacheco, 2022;Christou et al., 2022;

Agathokleous et al., 2022).

Currently, the use of biostimulants in agriculture is increasing and it is

estimated this will continue growing up worldwide. However, based on

the information presented in this review, it is likely that future

biostimulants/elicitors will not only be of biological, but also of non-

biological nature. Additionally, the possibility of transgenerational

hormesis will also open a big ﬁeld for research in the future in order to de-

sign new and maybe faster plant breeding programs.

CRediT authorship contribution statement

Pablo L. Godínez-Mendoza: Formal analysis, Investigation, Data

curation. Amanda K. Rico-Chávez: Formal analysis, Investigation, Re-

sources, Data curation. Noelia I. Ferrusquía-Jimenez: Formal analysis, In-

vestigation, Data curation. Ireri A. Carbajal-Valenzuela: Formal analysis,

Investigation, Data curation. Ana L. Villagómez-Aranda: Formal analysis,

Investigation, Data curation. Irineo Torres-Pacheco: Conceptualization,

Formal analysis, Investigation, Resources, Writing –review &editing,

Data curation. Ramon G. Guevara-González: Conceptualization, Formal

analysis, Investigation, Resources, Writing –original draft, Writing –review

&editing, Data curation.

Data availability

Data will be made available on request.

Declaration of competing interest

The authors declare that they have no known competing ﬁnancial inter-

ests or personal relationships that could have appeared to inﬂuence the

work reported in this paper.

Acknowledgements

The authors acknowledge all reviewers of this manuscript for their ex-

cellent contributions to enrich the document. Moreover, we want to thank

Dr. Gobinath Chandrakasan, for kindly reviewing the English style of the ﬁ-

nal manuscript. P.L- G-M, A.K.R-Ch, N.I.F-J, I.A.C-V and A.L.V-A acknowl-

edges to CONACyT for grant support during their PhD studies.

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Synergistic effects of mining and urban effluents on the level and distribution of methylmercury in a shallow aquatic ecosystem of the Bolivian Altiplano

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Nov 2016

Lake Uru Uru (3686 m a.s.l.) located in the Bolivian Altiplano region receives both mining effluents and urban wastewater discharges originating from the surrounding local cities which are under rapid development. We followed the spatiotemporal distribution of different mercury (Hg) compounds and other metal(oid)s (e.g., Fe, Mn, Sb, Ti and W) in both water and sediments during the wet and dry seasons along a north-south transect of this shallow lake system. Along the transect, the highest Hg and metal(oid) concentrations in both water and sediments were found downstream of the confluences with mining effluents. Although a dilution effect was found for major elements during the wet season, mean Hg and metal(oid) concentrations did not significantly differ from the dry season due to the increase in acid mine drainage (AMD) inputs into the lake from upstream mining areas. In particular, high filtered (<0.45 μm) mono-methylmercury (MMHg) concentrations (0.69 ± 0.47 ng L(-1)) were measured in surface water representing 49 ± 11% of the total filtered Hg concentrations (THgF) for both seasons. Enhanced MMHg lability in relation with the water alkalinity, coupled with abundant organic ligands and colloids (especially for downstream mining effluents), are likely factors favoring Hg methylation and MMHg preservation while inhibiting MMHg photodegradation. Lake sediments were identified as the major source of MMHg for the shallow water column. During the dry season, diffusive fluxes were estimated to be 227 ng m(-2) d(-1) for MMHg. This contribution was found to be negligible during the wet season due to a probable shift of the redox front downwards in the sediments. During the wet season, the results obtained suggest that various sources such as mining effluents and benthic or macrophytic biofilms significantly contribute to MMHg inputs in the water column. This work demonstrates the seasonally dependent synergistic effect of AMD and urban effluents on the shallow, productive and evaporative high altitude lake ecosystems which promotes the formation of natural organometallic toxins such as MMHg in the water column.

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Plant hormesis: Revising of the concepts of biostimulation, elicitation and their application in a sustainable agricultural production

Article

June 2023

Pablo Godínez · Amanda Kim Rico Chávez · Noelia Isabel Ferrusquía-Jiménez · Ireri a Carbajal · Ramón Gerardo Guevara-Gonzalez