plants
Article
Chlorophyll Fluorescence Imaging as a Tool for Evaluating
Disease Resistance of Common Bean Lines in the Western
Amazon Region of Colombia
Juan Carlos Suárez 1,2,*, José Iván Vanegas 1 , Amara Tatiana Contreras 1,2 , José Alexander Anzola 1 ,
Milan O. Urban 3, Stephen E. Beebe 3 and Idupulapati M. Rao 3
1 Programa de Ingeniería Agroecológica, Facultad de Ingeniería, Universidad de la Amazonia,
Florencia 180001, Colombia; vanegas.agroeco@gmail.com (J.I.V.); 1993anzola@gmail.com (A.T.C.);
amaratatis18@gmail.com (J.A.A.)
2 Centro de Investigaciones Amazónicas (CIMAZ)—Macagual César Augusto Estrada González, Grupo de
Investigaciones Agroecosistemas y Conservación en Bosques Amazónicos-GAIA, Florencia 180001, Colombia
3 International Center for Tropical Agriculture (CIAT), Km 17 Recta Cali-Palmira, Cali 763537, Colombia;
m.urban@cgiar.org (M.O.U.); s.beebe@cgiar.org (S.E.B.); i.rao@cgiar.org (I.M.R.)
* Correspondence: ju.suarez@udla.edu.co; Tel.: +57-320-2804455
Abstract: The evaluation of disease resistance is considered an important aspect of phenotyping for
crop improvement. Identification of advanced lines of the common bean with disease resistance
contributes to improved grain yields. This study aimed to determine the response of the photosyn-
thetic apparatus to natural pathogen infection by using chlorophyll (Chla) fluorescence parameters
and their relationship to the agronomic performance of 59 common bean lines and comparing the
Citation: Suárez, J.C.; Vanegas, J.I.; photosynthetic responses of naturally infected vs. healthy leaves. The study was conducted over
Contreras, A.T.; Anzola, J.A.; Urban, two seasons under acid soil and high temperature conditions in the western Amazon region of
M.O.; Beebe, S.E.; Rao, I.M. Colombia. A disease susceptibility index (DSI) was developed and validated using chlorophyll a
Chlorophyll Fluorescence Imaging as (Chla) fluorescence as a tool to identify Mesoamerican and Andean lines of common bean (Phaseolus
a Tool for Evaluating Disease vulgaris L.) that are resistant to pathogens. A negative effect on the functional status of the photo-
Resistance of Common Bean Lines in synthetic apparatus was found with the presence of pathogen infection, a situation that allowed the
the Western Amazon Region of
identification of four typologies based on the DSI values ((i) moderately resistant; (ii) moderately
Colombia. Plants 2022, 11, 1371.
susceptible; (iii) susceptible; and (iv) highly susceptible). Moderately resistant lines, five of them
https://doi.org/10.3390/
from the Mesoamerican gene pool (ALB 350, SMC 200, BFS 10, SER 16, SMN 27) and one from the
plants11101371
Andean gene pool (DAB 295), allocated a higher proportion of energy to photochemical processes,
Academic Editor: Georgia which increased the rate of electron transfer resulting in a lower sensitivity to disease stress. This
Ouzounidou photosynthetic response was associated with lower values of DSI, which translated into an increase
Received: 6 May 2022 in the accumulation of dry matter accumulation in different plant organs (leaves, stem, pods and
Accepted: 20 May 2022 roots). Thus, DSI values based on chlorophyll fluorescence response to pathogen infection could
Published: 21 May 2022 serve as a phenotyping tool for evaluating advanced common bean lines. Six common bean lines
Publisher’s Note: MDPI stays neutral (ALB 350, BFS 10, DAB 295, SER 16, SMC 200 and SMN 27) were identified as less sensitive to disease
with regard to jurisdictional claims in stress under field conditions in the western Amazon region of Colombia, and these could serve as
published maps and institutional affil- useful parents for improving the common bean for multiple stress resistance.
iations.
Keywords: acid soil; agronomic performance; disease susceptibility index; dry matter accumulation;
grain yield; high temperature; photochemical processes; photosynthetic response
Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article 1. Introduction
distributed under the terms and
The common bean (Phaseolus vulgaris L.) is the most important food legume and it
conditions of the Creative Commons
Attribution (CC BY) license (https:// is particularly valued for its protein and micronutrient content [1]. In parts of Africa and
creativecommons.org/licenses/by/ Latin America, it provides an average of 15% of total daily calories and 36% of daily protein
4.0/). content [2]. Most of the production of common bean is carried out by small farmers under
Plants 2022, 11, 1371. https://doi.org/10.3390/plants11101371 https://www.mdpi.com/journal/plants
Plants 2022, 11, 1371 2 of 26
adverse climatic conditions in the tropics and subtropics [3,4]. The growing conditions in
these regions, particularly in the humid tropics, favor numerous infectious diseases caused
by fungi, viruses, bacteria and nematodes that result in yield losses up to 100% [5–7].
Common bean germplasm is divided into two major gene pools that have been indi-
vidually domesticated: the Andean gene pool, mainly large-seeded, and the Mesoamerican
gene pool, which is small- to medium-seeded [8]. The infection-causing pathogens (fungi,
viruses, bacteria and nematodes) are also classified into two genetic groups (Andean and
Mesoamerican), which co-evolved with the gene pools of their host [9]. While the Andean
group of pathogens affect Andean beans, Mesoamerican pathogens are more pathogenic
to Mesoamerican beans, as well as, to some extent, Andean beans, thus showing a greater
diversity of virulence [6]. Biotic stress caused by pathogens in plants inevitably induces
various changes in their physiological functions, resulting in metabolic disorders due to
infections or nutritional deficiencies [10]. Biotic stress symptoms can generally be seen in
leaves, stems and roots, but lesions can also appear in seeds, leading to losses in productiv-
ity and grain quality [5]. Thus, accurate assessment of plant symptoms can be used as a
proxy indicator when monitoring diseases, estimating yield loss and developing resistant
genotypes against plant diseases [11].
In breeding programs, the evaluation of disease resistance or biotic stress resistance is
based on disease severity, which is defined as the area of plant tissue infected by disease-
causing organisms and expressed as a percentage of the total amount of plant tissue [7,12].
Likewise, evaluation relies heavily on traditional methods such as rating scales based on
visible symptoms [13], which in most cases measure severity based on rater subjectivity that
often lacks precision, reproducibility and traceability [14]. Plants have evolved complex
sensory mechanisms to identify biotic invasion and overcome detriments to growth, yield
and survival [15]. Changes induced under both light and dark periods are critical for plant
survival [16]. Disease resistance has been observed to have a positive influence on plant
photosynthesis compared to sensitive cultivars [17]. A disease-resistant cultivar usually
shows higher rates of photosynthesis, electron transport and dark respiration, eventually
reaching high yields in regions where widespread diseases are present [17,18]. However, the
presence of a disease in a susceptible plant triggers alterations in morphology, physiological
functions and plant integrity that can cause partial or total damage [10], as these are
determinants in the plant’s ability to adapt to specific environmental conditions [19].
Among different stress responses, photosynthesis plays an important role in plant
disease defense responses [20]. The reduction of photosynthesis by the pathogen can be
caused by the deterioration of the photosynthetic apparatus. This can substantially reduce
the ability of the leaves to fix CO2, that is necessary for the formation of the photosynthates
that are required during the reproductive phase [21]. In addition, stress induced by diseases
can increase the excitation energy, to the point that it exceeds the amount necessary for
photosynthetic metabolism, generating reactive oxygen species (ROS) [22] as well as a series
of related changes in chloroplast–disease interaction [23]. These include: (i) fluctuation
of chlorophyll fluorescence and reduced chlorophyll pigmentation [24–26], (ii) inhibition
of photosystem efficiency [27], (iii) unbalanced accumulation of photoassimilates [28],
(iv) changes in chloroplast structure and function [29] and (v) decreases in Fv/Fm, ΦPSII and
increases in NPQ heat energy dissipation [30], and these changes can alter leaf temperature.
For example, when pathogens directly or indirectly impair transpiration, the net effect is a
lack of thermal regulation resulting in an increase in leaf temperature [19,31].
Improving disease resistance by developing and identifying more resistant genotypes
is considered the most sustainable method to reduce yield losses due to disease [6,7].
This disease resistance breeding approach is an efficient, reliable and inexpensive way
to sustainably manage disease with fewer chemical inputs [32]. Among plant responses
to stress, chlorophyll fluorescence is very sensitive to plant physiological changes and
is used to measure the physiological state of a plant under both biotic [13,25,26,33] and
abiotic [34,35] stress conditions. Chlorophyll a (Chla) fluorescence results from light energy
absorbed by chlorophyll in photosystem II (PSII), which can be used for photosynthesis
Plants 2022, 11, 1371 3 of 26
(qP, photochemical quenching), re-emitted as fluorescence or lost as heat (NPQ, non-
photochemical quenching). If the quantum yield of one of the processes decreases, the
quantum yield of one or both of the other two processes will increase [13,36]. One of the
main strengths of Chla fluorescence measurements is that many stresses can be detected
before any sign of visible damage occurs [37,38], depending on the type of stress suffered
by the plant, so there is great potential for helping to minimize crop production problems
through early detection of stress factors [39].
The objective of this work was to determine the response of the photosynthetic ap-
paratus to natural pathogen infection by using Chla fluorescence parameters in different
common bean lines and comparing the response from naturally infected vs. healthy leaves
under field conditions. Based on this information on chlorophyll fluorescence imaging,
a disease susceptibility index (DSI) was developed for phenotyping different bean lines
and to identify the less susceptible ones under the field conditions (acid soils and high
temperature) of the Colombian Amazon. For this purpose, the existence of variability in
the tolerance-adjustment mechanism of the photosynthetic apparatus to disease stress was
hypothesized. To test this, a DSI was developed using chlorophyll fluorescence as a tool
to evaluate the disease resistance of the Mesoamerican and the Andean lines of common
bean and identify sensitive genotypes. The DSI was mostly based on the comparison of
light use and paths of energy transformation (i.e., energy that passes to photochemistry
ΦII, dissipates as heat ΦNPQ and dissipates in a non-regulated manner ΦNO) in healthy
and naturally infected leaves.
2. Results
2.1. Response of the Photosynthetic Apparatus to Disease Stress in Leaves of Phaseolus vulgaris
Chlorophyll fluorescence parameters showed that the initial fluorescence yield (Fo)
was 38.7% higher in infected leaves, contrary to what was presented for the maximum
fluorescence (Fm), which was 25% higher in healthy leaves (p < 0.05). The maximum
quantum yield of the PSII photochemistry (Fv/Fm) for both healthy and infected leaf
conditions was found to be below 0.82, which suggests that stress conditions exist due
to acid soil and high temperature stress (Figure 1). When analyzing the increase of the
irradiance level, we found that the effective PSII quantum yield (Y(II)) was significantly
reduced for both conditions analyzed. The value was always higher in the healthy leaf,
where at 300 µmol m−2 s−1 the value of Y(II) was 0.20 for healthy and 0.14 for infected
leaves, respectively (Figure 2a). As for the fraction of the energy dissipated as heat related
to non-photochemical quenching (NPQ), it was found that in the two conditions with
increasing PAR, the NPQ also increased. The curves were different from 300 µmol m−2 s−1,
reaching a difference of 14.2% at 700 µmol m−2 s−1 between the two conditions (p < 0.05,
Figure 2b). For the quantum yield of non-regulated energy dissipation (Y(NO)), we found
that it increased up to 21 µmol m−2 s−1, at which point the values were 0.45 and 0.50 for
the healthy and infected leaves, respectively, and reached a difference of 23% between the
two leaf conditions at 700 µmol m−2 s−1 of PAR (p < 0.05, Figure 2c). The apparent electron
transport rate (ETR) was the most sensitive variable. The greatest difference was observed
between the two conditions at PAR 500 µmol m−2 s−1, where the ETR in the healthy leaf
was 3.6 times higher compared to the infected leaves (p < 0.05, Figure 2d). The coefficient
of photochemical quenching (qP) decreased with increasing PAR, with the qP value being
higher in the healthy leaf (p < 0.05, Figure 2e). Finally, the non-photochemical quenching
coefficient (qN) was proportional to PAR, with no differences from PAR 350 µmol m−2 s−1
(p < 0.05, Figure 2f).
Plants 2022, 11, x FOR PEER REVIEW 4 of 26 
 
Plants 2022, 11, 1371 4 of 26
 
Figure 1. Photochemical status of fully oxidized and reduced photochemistry II (PSII) of different
Fbiegaunrgee n1o. tPypheostowcithhesmusicceapl tsibtialittuyst oodf ifsueallsye sotxreisdsi.z(ead) I naintidal rfleudourecsecden pceh(oFto0);c(hbe)mmiasxtirmya IlIfl (uP-SII) of different 
boereasnc egneceno(Ftym)p;e(cs) wthiethm asxuismcuemptiqbuialinttyu mtoy dieilsdeoafseth setPreSsIIs.p h(ao)t oIcnhietmiails tfrlyuoFr
v/eFsce
m.nTchee (dFa0s)h; e(db) maximal fluo-
rbelsacckenlicnee c(Formr)e;s p(co)n dthseto mthaexmimeaunmof qeaucahnvtaurimab lyei.eal,db :oLfe tthteers PfoSrIIth pehboartsofcohreemacihstlerayf Fcovn/Fdmit.i oTnhe dashed black 
liinndei ccaoterrsetastpisotincadllsy tsoig tnhifiec manetadnif foerfe enacecshb vasaerdiaobnleth. eaL, SbD: Lmeetatenrsst efsotr( pth<e0 .b05a)r.sR feosur letsaicnhc luledaef condition indi-
ctahteem setanti±stiScEa(lnly= s2i8g3n2ilfeiacvaenst) .differences based on the LSD means test (p < 0.05). Results include the 
mean ± SE (n = 2832 leaves). 
 
PlaPnlatsnt2s0 22022, 21,1 1,11,3 x7 1FOR PEER REVIEW 5 5ofo f2266 
 
 
FFigiguurere2 2. .R Reessppoonnsseeo off tthhee pphhoottoossyynntthheettiicc aappppaarraattuuss ttoo ddiisseeaassee ssttrreessss.. ((aa)) TThhee eeffffeeccttiivvee qquuaanntutumm yyieieldld 
oof fp phhoototocchheemmicicaal le enneerrggyyc coonnvveerrssiioonn iinn PSIIII ((Y(II));; (b) non-photochemiicall queencchiinngg ((NPPQQ)); ;((cc)) ththee 
qquuanantutummy yieieldldo offn noonn--rreegguullaatteedde enneerrggyy diissssiipattiion (Y(NO)); (d) the appaarrentt eelleeccttrroonn ttrraannssppoorrtt rraatete 
(E(ETTRR););( e(e) )t htheec ocoeeffiffcicieienntto offp phhoototocchheemiiccaall qquueenncchhiinngg ((qqPP));; ((ff)) tthhee nnoonn--pphhoottoocchheemiiccaall qquueenncchhiningg 
cocoeeffiffciiceienntt( q(qNN).).P PAARR: :p phhoototossyynntthheettiiccaallllyy aaccttiivvee rraaddiiaattiioonn.. EEaacchh ddaattaa ppooiinntt oonn tthhee ccuurrvvee rreepprreesseenntsts 
ththeem meeaanna anndds statannddaarrddd deevviaiattioionn( (nn= = 770088 ppllaannttss ffoorr eeaacchh lleeaaff ccoonnddiittiioonn)).. 
 
Plants 2022, 11, x FOR PEER REVIEW 6 of 26 
 
Plants 2022, 11, 1371 6 of 26
When analyzing the relationships between the different variables of chlorophyll flu-
orescence in both healthy and infected leaves, contrasting differences were found (Figure 
3). For exWahmenplaen,a ilny zhinegaltthheyr elleaativoenss hailpls cboertrweelaentiothnesd wiffeerreen stigvanriifaibclaens to, fecxhclolurodpihnygl ltflhueo r-elation-
shipr ebsectewnceeeinn qboPt hanheda lYth(yNaOnd). iInnfe icntefedclteeadve lse,acvonetsr,a nstoin cgodrirfefelraetniocens wwearse ffoouunndd( bFiegtuwreee3)n.  Y(NO) 
and FYo(rIIe)x.a Ammploe,nign htheael tphoyslietaivvees caollrcroerlraetliaotinosn s(gwreereens itgon bifilcuaen tg,reaxdcliuednitn)g, wthee rfeoluatniodn sah ripbetween qP and Y(NO). In infected leaves, no correlation was found between Y(NO) andeduction 
in thYe( IcI)o.rAremlaotnigonth beeptowsietievne qcoNrr ealnatdio EnsT(Rg;r ewenhitloeb ilnu ethgera hdieeanltt)h, yw elefaofu nitd haarde dau rcetiloantiionnship of 
0.45,t hite dcoercrreelatsieond btoet 0w.e2e2n inqN thaen idnEfeTcRt;ewdh lielaefi n(pt h<e 0h.0ea5l,t hFyigleuarfei t3h).a Ad  asirmelaitliaorn sihtiupaotfio0n.4 5o,ccurred 
regairtddiencgre tahsed ctor0r.e2l2atiniotnh eoifn EfeTctRed wleiathf ( pN<P0Q.0 5a,nFdig Yur(eN3P).QA); suimnidlaerr stithuea thioenalotchcyu rcroednditions, 
the rreeglaatridoinngshtihpe cwoarrse l0a.t2io8n, obfuEt TtRhew iinthfeNctPeQd alnedafY p(NrePsQe)n;tuendd aer ctoherrheelaalttihoyn coofn d0i.t1io1n as,nd 0.06, 
resptehcetirveelaltyio (nps h<i p0w.0a5s, 0F.i2g8u, rbeu t3t)h. eInin fgeectneedralela, ftphree sveanrteiadbalec owrrietlha ttiohne ogfr0e.a1t1easnt dva0.r0i6a,tion be-
tweernes pthecet itvweloy (cpo<nd0.i0t5i,oFnigs uwrea3s) .thIneg eelneecrtarlo, tnh etrvaanrisafbelre rwaitteh (thEeTgRre) a(tpe s<t v0a.0ri5a,t iFoingbuertew e3e)nthe two conditions was the electron transfer rate (ETR) (p < 0.05, Figure 3). . 
 
FiguFreig u3r.e 3R.eRlealtaitoionnsshhiips bbetewtweeenednif fedriefnftevrearniat bvleasroifacbhlleosr opohf ylclhflluoorroepscheynclle mfleuaosureresdceincPeh asmeoeluassured in 
Phasevoullugsa rvisullegaavreis .le(a)vHese.a (ltah)y Hleeaavleths;y( ble) ainvfesc;t e(db)l eianvfeesc.teMda lxeimavael sfl. uMoraexsciemnacel f(lFumo)r, ethsceeenffceec t(iFvem), the ef-
fectivqeu aqnutuamntyuiemld yoifeplhdo toofc hpehmoitcoacl heneemrgiycacol nevneerrsigoyn icnoPnSvIeI r(Ysi(oIIn)) ,iqnu aPnStIuIm (Yyi(eIlId))o, fqruegaunltautemd  eynieerlgdy of regu-
latedd eisnsiepragtiyo ndYis(sNipPaQt)i,oqnu aYn(tNumPQyi)e,l dquofanotunrmeg uyliaetledd oenf enrgoyndreisgsuiplattieodn Ye(nNeOrg),yn odnis-psihpoatoticohnem Yic(Nal O), non-
photqoucehnecmhinicga(lN qPuQe)n, ct heinogn (-NphPoQto)c,h tehmei cnaol nqu-penhcohtioncghceomeffiiciaeln qt (uqeNn)c, hthiencgo ecfofiecfiefinctioefnpt h(oqtNoc)h, etmheic caol efficient 
of phqouteoncchienmg i(cqaPl) ,qcuoefnficchieintgo f(qpPh)o,t occoheefmficiciaelnqtu oefn cphhinogto(qchL)e,manicdatlh qeuapenpacrheinntge l(eqctLro),n atnradn stphoer tapparent 
electrraotne (tErTanRs).port rate (ETR). 
2.2. P2.h2e. nPohteynpotiynpgin ogf oAf dAvdavnancceedd LLiinneess ooffP Phhasaesoeluolsuvsu vlgualrgisafroirs Sfuorsc SeputsibcieliptytibtoilDitiys etaos eDSitsreesasse Stress 
Using chlorophyll fluorescence imaging, the disease susceptibility index (DSI) was
dUessiignnge dchtoloprhoepnhoytyllp efluadovreanscceedncbee aimn aligneins.g,W thhee ndwiseeaasnea lsyuzsecdetphteibrielsiptyo nisnedoefx th(De SI) was 
desipghnoetdo styon tphheetincoaptypparea atudsvuasnincgedD SbIe, awne lfionuensd. Wconhternas twineg adnifafelyreznecdes t(hpe< r0e.s0p5,oFnisgeu roef4 t,he pho-
tosyTnatbhleet1ic.  Farpompatrhaetuclsu sutesrinagn aDlySsiIs, ,wfoeu rfoDuSnI-dre lcaotendtrtaysptoilnog idesifwfeerreenocbetasi n(pe d< (0m.0o5d,e rFaitgeulyre 4, Ta-
ble 1re. sFisrtoanmt, tmhoed celruatsetleyrs uasncaelpytisbisle, , fsouuscre pDtiSbIl-eraenladtehdig htylypsoulsocgepietisb lwe)e. re obtained (moderately 
resistant, moderately susceptible, susceptible and highly susceptible). 
 
PlPanlatnst2s 022022,21, 11,1,1 x3 7F1OR PEER REVIEW 7 of 267 of 26
 
 
Fiigurree 4.. Diiseassee suscepttiibiilliittyy iindex (DSI) of aadvanced bbeeaan lliinneess.. TThheed daasshheeddb blalacckkl ilnineec ocrorrersep- onds
stpootnhdesm toe tahne omfeeaanc hofv eaarciha bvlaer.iaab,lbe., ac,, bd, :c,L de:t tLeertstearts eaat cehacpho pinoitnfto frore aecahchc coommmoon bean forrwaarrdd line
liinnde iicnadteicsattaet sistatitcisatlilcyalsliyg nsiigfinciafinctandti fdfeifrfeenrecnecsebs absaesdedo nonth teheL SLDSDm meaeannsst etesstt( p(p< < 00..0055)).. RReessuullttss iinn-clude
cthluedme tehaen m±eaSnE ±( nSE= (7n0 =8 )7.08). 
i. i. MoMderoadteerlya treelsyistraensits (tManRt; (nM = R6;; 2n1.8=%6 o; f2 t1h.e8 t%otaolf gtehneottyopteasl egveanluoatytepde)s weavsa al utyapteodlo)gwy as a
chatryapctoelroizgeydc bhya lroawct aenridz ehdigbhy lelvoewls oafn Fdo ahnigdh Fmle, vreeslps eocftiFvel
o ayn, idn Fthe
m, draerskp aedctaipvtealtyi,onin the
phadsaer. kAat dthaep tlaevtieoln opf henaeserg. yA dt itshteribleuvteiolno fine ntheerg dyifdfeirsetrnitb furtaicotnioinns,t htheisd itfyfperoelongt yfr aasc-tions,
signthedis tthyep hoilgohgeysta psrsoigpnoertdiotnh teo hqiPg h(pe s<t 0p.0r5o)p aonrdti,o lniketowiqsPe, (tpo <eff0ic.0ie5n)cayn idn, thliek eewlecis-e, to
trone ftfiracinesnfecry riantet h(EeTeRle, cpt r<o 0n.0t5r)a. nTshfeisr tryaptoel(oEgTyR h,apd <a 0lo.0w5e)r.  DThSIis wtyitpho alno goyvehraadll aavl-ower
eraDgeS oI fw 0i.t1h6 a±n 0.o0v2 e(rraepllraesveenrtaegde boyf l0in.1e6s ±AL0B.0 3250(r, eSpMreCs e2n0t0e,d BFbSy 1li0n, eDsAABL 2B953 5a0n,dS MC
SER 16). In terms of agronomic response (Table 1), these lines accumulated a greater 
am2o0u0n,t BoFfS b1io0m, DasAs Bin2 9d5ifafenrdenStE oRrg1a6n).s,I nsutcehrm ass othfea groroont,o smteimc r, elsepavoenss ean(Tda bcaleno1p),yt hese
biolminaesss a(pcc <u m0.0u0l1a)t,e adnad gsrheoawteerda ma goruenatteorf nbuiommbaesr soifn pdoidffse (r4e.n6t ±o 0rg.2a9n gs,).s Tuhche apslatnhtes root,
accsutmemul,alteeadv ceasnaonpdy cbainomopayssb tiwomicea sass (mpu<ch0. c0o0m1)p, aanredds thoo thwee hdigahglyre sautsecrenputimblbee trypoef .p ods
ii. Mo(d4e.r6at±ely0 s.2u9scgep).tiTblhe e(MplSa;n DtsSaI c=c 0u.m33u, lna t=e 1d6c; a2n7o.1p%y) bwioams aa stysptwoliocgeya tshmatu wchasc cohmarpaacr-ed to
teritzheed hbiyg halny isnucsrecaepset iibnl ethtey pfrea.ction of non-regulated energy (qN), and its reaction 
ii. cenMterosd ewraetreel ymsoudsecreaptteiblyle r(eMduSc;eDd SsIo =th0at.3 i3ts, enle=ctr1o6n;  2tr7a.n1s%fe)r wraatse a(EtTyRp)o wloagsy lotwhaetr was
comchpaarreadct teor itzheed mboydaenraitneclyre raesseisitnantth beefarna cltiinoens. oTfhneo bne-srte ganudla ltoewd eesnt erragteyd( qliNne)s,  ainn d its
termresa octf iDonSIc wenetreer SsMwRe r8e4 manodd SeAraBte 6l8y6r, erdesupceecdtivseolyth. Tathiists tyepleocltorgoyn rterdauncsefder itrsa pteod(E TR)
biowmaasssl;o hwoewrecvoemr, pa asrterodntgo pthreesemnoced eorf aftleolwyerress wistaasn ftoubenadn wliinthe sa.nT ihnecrbeaesset ainn drolootw est
biormaatesds. lines in terms of DSI were SMR 84 and SAB 686, respectively. This typology
iii. Susrceedptuibcleed (Sit; sDpSoI d= b0i.4o8m, ans =s; 2h9o; w49e.v1%er), awsatsr oan tgypporleosgeyn cwehoefrfle oYw(IeI)r swwasa srefdouucnedd wbyit h an
40%in acnrdea tshee ifnrarcotoiotnb oiof menaesrsg.y dissipated as heat (NPQ) and non-regulated (qN) was 
iii. incrSeuassceedp tbibyl e4(6S%;  DanSdI  =400%.4,8 r,ensp=ec2t9i;v4e9ly.1, %in) rwelaastioant ytop othloeg my owdheerareteYly( IrIe)swisatasnrte bdeuacne d by
line4s0. %Likaenwdisthe,e thfrias cttyipoonlogfye nsheorgwyed ias sciopnastiedderaasbhlee raetd(uNcPtiQon) iann tdhen ofrna-crteiognu loaft end-(qN)
ergwy adsiisntrcirbeuatseedd tboy t4h6e% pahnodto4s0y%nt,hretsipc epctriovceelsys, i(nqPre, la4t4io.8n%t)o athned mino dtehrea telleyctrreosnis tant
tranbsepaonrtl irnaetse. (LEiTkRe,w 5i3s.e2,%th).i sThtyep loinloesg ythsaht ocwonefdoramceodn stoid tehrias btyleproeldoguyc teioxnpeirnietnhceefdr ac tion
greoatfeern eefrfgecyt dfriostmri bduisteadseto sthreessp hoont opsoydn pthroedtiuccptironc,e sas (wqPe,ll4 a4s.8 o%n) tahned oitnhetrh eplealnetc tron
orgtarnasn. sport rate (ETR, 53.2%). The lines that conformed to this typology experienced
iv. Higahlgyr seuastceerpetifbfleec (tHfrSo; mDSdIi =se 0a.6se9,s ntr =e s8s; o13n.5p%od) wparos da utyctpiolno,gays wheellrea sthoen etnheergoyth wearsp lant
distorribguantesd.  in a higher proportion in the form of heat dissipation (NPQ) and as non-
iv. regHuliagtheldy (squNsc)e, patnidbl eth(eH eSf;fiDciSenI c=y 0o.f6 9th,en p=ho8t;o1s3y.n5t%he)twic aaspapatyraptoulso wgyasw vhereyr elotwhe (qePn ergy
andw EaTsRd)i.s Atritb tuhtee adgirnonaohmigihc elervperlo, pa osrigtinoinficinantth eefffoecrmt woafsh feoautndi sssiinpcaet isoenve(rNalP pQl)anatn d as
orgnaonsn -driedg unloatt eshdo(wqN ad),eaqnudatteh deeevfefilcoipemnceynto; fhtohweepvhero,t oansy inntchreeatisce ainp proaorat tbuisomwaasss very
waslo fwoun(qdP ata tnhde eExTpRe)n.sAe ot ft hsheoaogt rgornowomthi.c level, a significant effect was found since
several plant organs did not show adequate development; however, an increase in
root biomass was found at the expense of shoot growth.
 
Plants 2022, 11, 1371 8 of 26
Table 1. Chlorophyll (Chla) fluorescence and physiological, environmental and agronomic variables of different types of common bean genotypes, classified into
four groups based on the disease susceptibility index (DSI) when grown under acid soil and high temperature stress conditions in the field over two seasons.
Variable Moderately Resistant Moderately Susceptible Susceptible Highly Susceptible p-Value
Disease susceptibility index (DSI) 0.16 ± 0.02 a 0.33 ± 0.01 b 0.48 ± 0.01 c 0.69 ± 0.02 d <0.0001
Initial fluorescence (F0) 0.02 ± 0.01 a 0.02 ± 0.01 a 0.02 ± 0.01 a 0.01 ± 0.01 b 0.0028
Maximum fluorescence (Fm) 0.04 ± 0.01 a 0.04 ± 0.01 a 0.03 ± 0.01 b 0.02 ± 0.01 c <0.0001
Effective quantum yield of photochemical energy conversion in PSII (Y(II)) 0.15 ± 0.02 a 0.12 ± 0.01 a 0.09 ± 0.01 b 0.08 ± 0.02 b 0.0008
Quantum yield of regulated energy dissipation (Y(NPQ)) 0.13 ± 0.02 b 0.15 ± 0.01 b 0.19 ± 0.01 a 0.21 ± 0.02 a 0.0003
Quantum yield of non-regulated energy dissipation (Y(NO)) 0.13 ± 0.01 0.13 ± 0.01 0.12 ± 0.01 0.12 ± 0.02
Non-photochemical quenching (NPQ) 0.25 ± 0.02 0.23 ± 0.01 0.21 ± 0.01 0.2 ± 0.02
Non-photochemical quenching coefficient (qN) 0.25 ± 0.03 b 0.28 ± 0.02 b 0.35 ± 0.01 a 0.36 ± 0.04 a 0.0004
Coefficient of photochemical quenching (qP) 0.29 ± 0.02 a 0.23 ± 0.01 b 0.16 ± 0.01 c 0.09 ± 0.01 d <0.0001
Coefficient of photochemical quenching (qL) 0.17 ± 0.02 a 0.14 ± 0.01 b 0.12 ± 0.01 b 0.07 ± 0.01 c <0.0001
Electron transport rate (ETR; µmol e− m−2 s−1) 10.26 ± 0.93 a 8.08 ± 0.65 a 4.8 ± 0.41 b 3.07 ± 0.67 b <0.0001
ETRmax (ETR maximum; µmol e− m−2 s−1) 65.66 ± 9.59 a 49.40 ± 6.18 b 46.84 ± 5.33 b 19.71 ± 4.18 c <0.0001
Maximum saturating irradiance (Ek; µmol m−2 s−1) 458.1 ± 22.47 a 365.31 ± 17.747 b 358.17 ± 18.8 b 163 ± 12.82 c <0.0001
Dark respiration rates (Rd; µmol CO2 m−2 s−1) 7.49 ± 0.02 c 9.6 ± 0.29 b 10.27 ± 0.18 b 23 ± 0.98 a <0.0001
Root biomass (g) 1.05 ± 0.24 a 2.1 ± 0.38 b 1.4 ± 0.25 a 1.35 ± 0.64 a <0.0001
Stem biomass (g) 8.45 ± 0.12 a 7.12 ± 0.94 a 5.35 ± 0.7 b 3.48 ± 0.48 c <0.0001
Leaf biomass (g) 8.62 ± 0.29 a 9.26 ± 0.61 a 7.8 ± 0.23 c 5.87 ± 0.15 c <0.0001
Flower bud biomass (g) 0.01 ± 0.01 0.04 ± 0.01 0.01 ± 0.01
Flower biomass (g) 0.04 ± 0.04 0.34 ± 0.13 0.05 ± 0.02 0.1 ± 0.10
Pods biomass (g) 4.6 ± 0.29 a 3.36 ± 0.45 b 0.72 ± 0.44 c 0.34 ± 0.22 c <0.0001
Canopy biomass (CB, g) 22.98 ± 2.01 a 19.75 ± 2.38 a 15.22 ± 1.93 b 10.9 ± 1.25 c <0.0001
Mean ± standard error. a, b, c: Averages with a letter in common between rows were not significantly different at 5% probability.
Plants 2022, 11, x FOR PEER REVIEW 9 of 26 
P lants 2022, 11, 1371 9 of 26
The PCA of chlorophyll fluorescence and DSI variables could explain 67.4% of the 
total TvhaeriaPbCilAityo falcohnlogr tohpeh fyirlsl tfl tuwoor easxceesn, cseepanardatDinSgI vthaer idabiflfeesrecnotu bldeaenx plinlaeiang6e7 t.y4p%oolofgtihees 
t(op t<a l0v.0a5r)i a(Fbiigliutyrea 5loan).g Atxhies fi1 r(s4t6t.4w%o) acxoenst,rsaespteadr abteinagn ltihneesd i(fhfiegrhenlyt sbuesacneplitnibealeg)e wtyitpho hloigghiees
(p < 0.05) (Figure 5a). Axis 1 (46.4%) contrasted bean lines (highly susceptible) with higherr 
ffrraaccttiioonnss ooff eenneerrggyy ddiissssiippaatteedd aass hheeaatt ((NNPPQQ aanndd YY((NNPPQQ)))) aanndd lliinneess wwiitthh hhiigghheerr DDSSII,, qqPP 
aanndd EETTRR vvaalluueess ((mmooddeerraatetelylyr eresissitsatannt)t)( F(iFgiugurere5 a5)a. )A. Axixsi2s (22 1(2%1)%w) awsanso ntaobtalebfleo rfoitrs ihtsig hhigFh 
F o
vao lvuael,uaes, saoscsioacteiadtewdi twhitthh ethseu sscuespcteipbtleibalen danhdig hhilgyhslyu sscuespcteipbtliebblee abnealnin leisne(Fs i(gFuigreur5ea ,5ba),.bA). 
MA oMnoten-tCea-Crlaortleos ttesshto swhoedwtehda tththate tdhieff edrieffnecreenincec hinlo crhoplohryolpl hflyulol rfeluscoernecsecevnaclue evsasliugensi fisicgannitfliy-
(cpan<tly0. (0p0 <1 )0.d0i0f1fe) rdeinffteiarteendtiathteedd thifefe driefnfetrteynpt otylopgoileosgioefs tohfe thbee baenanli nliensesin ino ouurr ssttuuddyy,, wwiitthh 
aann eexxppllaaiinneedd vvaarriiaabbiilliittyy ooff 3366%% ((FFiigguurree 55bb)).. WWhheenn wwee aannaallyyzzeedd tthhee mmaajjoorr ccoonnttrriibbuuttiinngg 
vvaarriiaabblleess iinn bbootthh 11 aanndd 22 iinn tthhee PPCCAA,, wwee ffoouunndd tthhaatt tthhoossee aabboovvee tthhee rreedd lliinnee iinn FFiigguurree 55cc,,dd 
wweerree ssttaattiissttiiccaallllyy tthhee mmoosstt iimmppoorrttaanntt iinn sseeppaarraattiinngg tthhee bbeeaann lliinneess iinn eeaacchh ooff tthhee ttyyppoollooggiieess 
aaccccoorrddiinngg ttoo tthhee lleevveell ooff ddiisseeaassee ssuusscceeppttiibbiilliittyy.. 
 
Fiigurre 5.. Prrojjecttiion off chllorrophyllll fflluorrescence varriiablles grrouped by tthe diifffferrentt ttypes off common 
bbeeaann ggeennoottyyppeess oonn tthhee FF11/F/2F 2fafcatoctroiarli apllapnlaen oef othfet hperipnrciinpcailp caolmcopmonpeonnt eanntaalynsailsy (sPisC(AP)C. (Aa)) .C(ao)rrCeloar--
rtieolant icoirnclcei rfcolre cfholrocrholpohroypll hfylulloflreusocerensccee nvaceriavbalreisa.b Tlehse.  vTahreiavbalreisa bwlietsh wthiteh htihgehehsitg thoe stht eto lothweelsot wcoenst-
ctroinbturtiibount iaorne adreendoetneodt ewditwh itah caolcoorl ogrrgadraiedniet nftrofrmom grgereene ntot orerded. .(b(b) )CClalassssifiificcaattioionn ooff ccoommmmoonn bbeeaann 
genotypes from chlorophyll fluorescence variables and disease susceptibility index (DSI). (c,d) Con-
gtreibnuottyiopne soff rcohmlocrholpohryolpl hfylulloflreusocreensccee nvcaerivaabrlieasb tloe sthane dfodrimseaatsioens uosfc tehpet iFb1il/iFty2 ipnrdinecxip(DalS cI)o.m(cp,do)nCenonts- 
torfi bthueti PonCAof ucnhdloerro dpihfyfellreflnuto tryepseces nocfe covmarmiabolne sbetoanth geefnoortmypateiso.n VoafrtiahbelFes1 /aFb2ovper itnhcei preadl  cloinme pporneseenntsteodf 
thhigehPeCr Acounntrdibeur tdioifnfesr ienn etatychp ecsomofpcoonmenmto (np <b e0a.0n5g).e Anocrtoynpyems. sV aarreia sbhloeswanb ionv Teathbleer 1e.d line presented
higher contributions in each component (p < 0.05). Acronyms are shown in Table 1.
  
 
Plants 2022, 11, x FOR PEER REVIEW 10 of 26 
 
Plants 2022, 11, 1371 10 of 26
2.3. Fluorescence and Images of Chlorophyll A (Chla) Fluorescence Parameters for Phenotyping of 
A2d.3v.anFcluedo rLeisncens coef aPnhdasIemolaugse svuoflgCahrlios rophyll A (Chla) Fluorescence Parameters for Phenotyping of
AdvTanhcee dbeLainne slinofePs hwasitehol uthsev uhliggahreisst DSI values from all typology groups were obtained 
from qTuhaenbtietaantivlien easnwalyitshist haendhi gfrhoemst CDhSlIa vfaluluoeressfcreonmcea lplatryapmoleotegrys.g Froour pesxawmerpeleo, bitna itnheed 
dfarrokm aqduaapntatittiaotniv pehaansael,y wsise afonudnfrdo rmedC cholaloflru gorraedscieenntcse ipna trhaem leetaevrse.s Fwoirthex daimsepalsee,  isntrtehses dfoarrk 
thaed avpatraiatibolne Fphase, we found red color gradients in the leaves with disease stress for the
0 (Figure 6a), up to the point of having black areas caused by pathogen ne-
cvroasriisa binle sFo0m(Fei gbueraen6 lain),eusp otfo ththee hpiogihnltyo sfuhsacveipntgibbllea ctykpaorleoagsyc asuuscehd absy RpRaAth o6g0e annnde cSrEoFsi s40in 
(Fsoigmuereb 6eban). lTinhees mofaxthime huimgh qlyuasnutsucemp tyibieleldt yfopro ltohgey PsSuIIc hphasotRoRchAem60isatnryd (SFEF 40 (Figure 6b).
v/Fm, Figure 6c) 
wTahse fmouanxdim inu mtheq uhaenatluthmy yleiealvdesfo frotrh tehPe SliInI epsh BotFoSc h10em, AisLtrBy 3(5F0v /aFnmd ,DFAigBu r2e965c, )wwhaischfo cuonrdrei-n
spthoenhdeeadl tthoy thleea mveosdfeorrattheelyl irneessisBtaFnSt 1ty0,pAolLoBgy3.5 W0 ahnedn DdeAcBre2a9s5in, gw thhiec hlecvoerlr eosf proesnidsteadnctoe tihne 
thmeo bdeearna tleilnyesre osifs tthane tottyhpeor lotygpyo. lWoghieesn, dtheec rveaasluineg Fthe level of resistance in the bean lines
v/Fm was significantly reduced in the 
inoffetchteedo tlehaefr, tay pcoonlodgitiieosn,  tthheavt aclaune bFev /oFbsmerwvaesd siing nthifiec garnatdlyiernetd cuhcaendgiinngth feroinmfe vcitoeldetl eaanfd, a 
bcluone dtoit iloignhtth garteceann (bFeigoubrsee r6vce).d in the gradient changing from violet and blue to light green
(Figure 6c).
 
FFigiguurere 66. .IImaaggeess ooff cchhlloorroopphhyyllllfl fuluoorersecsecnencecep apraarmameteertesrosf odfi fdfeirfefenrteandtv aadnvceadncleinde slionfecso omf mcoomn mbeoann s
bueanndse runtwdeorl etwafoc loenadf ictoionndsit(ihoenasl t(hyeaalnthdyi annfedc tiendfe).ctBeSdF). 1B0S,FA 1L0B, A35L0B,  D35A0B, D29A5B:  m29o5d: emraotdeelyrarteslyis traen- t
si(sMtaRn)t. (SMARB).6 S1A8,BS A61B8,6 S8A6:Bm 6o86d:e mraotedleyrastueslcye sputsibcelep(tMiblSe) .(MINSB). 8IN41Ba 8n4d1 IaNnBd 6IN04B: 6su04s:c esupsticbelpet(ibSl)e.  R(SR).A 
R6R0Aa n6d0 aSnEdF S4E0:Fh 4i0g:h hlyigshulysc seupstcibelpeti(bHleS )(.H(aS)).I n(ait)i aInl ifltiuaol rfeluscoernesccee(nFcoe) ;((Fbo)); m(ba)x mimauximfluumo rfleusocerensccee(nFcme );
(F(cm));m (ca)x mimauxmimquuman qtuumanteuffimci eenffcicyieonfcPyS IoIf (PFS
v/IIF (Fv
m)./FTmh)e. Tchhaen cgheaningteh ienc tohleo rcoglroard igernatdfireonmt fvroiomle tvtioolreetd 
tos irgendi fiseigsnaifcihesa nag cehianngvea liune vfarolume hfriogmhe hr itgohleorw teor lofowreera fcohr veaarciha bvlaer. iable. 
WWee ffoouunndd tthhaatt YY((IIII)) ddeeccrreeaasseedd wiitthh iinnccrreeaassiinngg iirrrraaddiiaanncceel leevveell( (PPAARR),),b beeininggd dififfefreernetnitn 
inb obtohthth tehdei fdfeifrfeenrtenleta lfecaof ncdointidointiso(nhse a(hltehayltahnyd aindfe cintefedc)taendd) aanmdo namg tohnegd tihffee rdeinffteardenvat nacde-d
vlainecesdo flicnoems mofo cnombemanosn (bFeigaunrse (F7)i.guTrhee 7l)in. eThBeF Slin1e0 BshFoSw 1e0d shinowboetdh ihne ablotthhy haenadlthinyf eacntedd 
inlefeacvtesda lehaivgehse ra lheivgehleorf leYv(eIIl) o(fp Y<(I0I.)0 (5p, <F i0g.u05re, F7iAgu).rHe 7igAh)l.y Hsiugshcleyp stuibslceelpintiebsles ulicnhesa suScEhF 
a4s 0S,ERFR 4A0,6 R0RanAd 6I0N aBn6d0 I4NsBh o6w04e dshzoewroedY (zIIe)rion Yth(IeI)i ninfe tchted inlefeacvtesd flreoamve2s8 f0roµm o2l8m0 μ−m2 so−l 1
mo−f2 PsA−1 Rof( FPiAguRr e(F7i(gAubre)) .7AItbis). wIto irst hwnoorthin ngotthinatgt thheaste tshuesscee psutisbcleepltiinbeles wlineeres owfeirnet eorfs pinetceirfi-c
sporeicgifinic. oTrhigeiEnT. TRhwe aEsTrRe dwuacse drebdyuacenda vbeyr ange aovfer3a4g%e ionf t3h4e%in ifne cthteed inlefaevcteesdf oleraavllesth feorb eaalln 
thlien ebseaenv alliunaeste edv,arleuaactheidn,g rtehaechpionign thoef hpaovinint gofz ehraovivnaglu zeesroat v6a0l0ueµsm aot l6m00− μ2 ms−o1l omf −P2A s−R1 ofof r
PtAheR SfEorF t4h0e aSnEdF R4R0 Aan6d0 RliRnAes 6(F0 ilginueres (7FBi(gau,bre)) .7B(a,b)). 
 
PlaPnltasn2ts0 2220,212,1 1, 11,3 x7 1FOR PEER REVIEW 11 of 1216 
 of 26
 
FFiigguurree 77.. RReessppoonnssee ttoo ddiisseeaassee ssttrreessss aass aa ffuunnccttiioonn ooff tthhee pphhoottoossyynntthheettiiccaallllyy aaccttiivvee rraaddiiaattiioonn ((PPAARR)) lev-
ellesvoeflsc oofm cmomomn obnea bnealinn elisnceos ncofonrfmorimngintgo tdoi dffiefrfeernetntty tpyoploolgoigeise.sB. BSSFF1 100, ,A ALLBB3 35500,, DDAABB 229955:: mmooddeerr-ately
ately resistant (MR). SAB 618, SAB 686: moderately susceptible (MS). INB 841 and INB 604: suscep-
rteisbilset a(Sn)t. R(MRAR )6.0S aAnBd 6S1E8F, 4S0A: Bhig68h6ly:  msuoscdeeprtaibtelely (HsuSs).c (eAp)t iIbmleag(Mes So)f. tIhNe Bpa8r4a1maentedr IYN(IBI)6 o0b4t:aisnuesdc ebpyt ible
(ISM).ARGRIANE6-0PAanMd; tShEeF ch4a0n: ghei ginh tlhyes cuoslcoer pgtriabdleien(Ht fSr)o.m(A v)ioIlmeta tgo ersedo fsitghneifipeas raa cmheatnegreY in(I vI)aloubet farionmed by
IhMigAhGerI NtoE l-oPwAeMr ;fothr eeacchha nvgaeriainblteh. e(Bco) lFoarsgt rlaigdhite ncut rfvroems ovf iYol(eIIt) taosr ae dfusnigcntiiofine sofa PcAhaRn: g(Beain) Yv(aIlIu) einf rom
hhiegahlethryt olealovwese; r(Bfobr) Yea(IcIh) ivna irnifaebctleed.  (lBea)vFeas;s t(Blicg) hEtTcRu irnv heseaoltfhYy( lIeIa) vaess;a (Bfudn) cEtTioRn ino finPfAecRte:d(B leaa)vYe(sI. I) in
hMeaelatnhsy alneadv eersr;o(rB bba)rsY c(IoIr)rienspinofnedc tteod 9l6e aAvOeIss; ((Barce)aEs ToRf iinntehreesatl)t hfoyr leeaacvhe sc;o(nBddit)ioEnT R(heinalitnhfye catnedd ilne-aves.
Mfected); i.e., six AOIs were taken for each leaf, among four plant leaves selected between the fifth 
aneda nesigahnthd treirforoliratbea lresavceosr (rfersopmo napdetxo to9 6baAseO) aIst t(haer ebaesgionfniinngte orfe psth)yfsoior leoagcichalc monadtuitriiotyn, f(rhoema lftohuyr and
ipnlfaencttes do)f; eia.ec.h,  saidxvAanOcIesdw lienree otfa kcoemn mfoorne abcehanl.e af, among four plant leaves selected between the fifth
and eighth trifoliate leaves (from apex to base) at the beginning of physiological maturity, from four
plantsFoofre tahceh pahdovtaonccheedmliincealo qf ucoemncmhoingb ceoaenf.ficient (qP) level, a decrease in the color gradi-
ent from blue to light green was found. This resulted in a decrease in qP with increasing 
PARF (oFrigthuerep 8hAot)o. cAhmemonicga tlhqeu aednvchainncgedc obeefafinc ileinntes(q, PA)LlBev 3e5l,0a hdaedc rtheaes heiignhtehset fcroalcotriognr aodf ient
feronmergbyl udeevtootleigdh tto gprheoentowchaesmfiocualn qdu. eTnhcihsinregs u(qltPe,d p i<n 0a.0d5e, cFriegausree i8nAq)P inw thiteh hineaclrtehays ilnegafP. AR
(BFFigSu 1re0 8sAho).wAemd othneg hthigehaedstv aqnPc evdalubeesa ninl ininefse,cAteLdB le3a5v0ehs addutrhinegh tihgeh ersatpfirda cltigiohnt ocuf revnee rgy
devoted to photochemical quenching (qP, p < 0.05, Figure 8A) in the healthy leaf. BFS 10
showed the highest qP values in infected leaves during the rapid light curve (Figure 8A).
Therefore, those lines that reduced their energy fraction in qP increased the dissipation of
 
Plants 2022, 11, x FOR PEER REVIEW 12 of 26 
 
Plants 2022, 11, 1371 12 of 26
(Figure 8A). Therefore, those lines that reduced their energy fraction in qP increased the 
deisnseiprgaytioin  tohfe enfoermgyo ifn htheae tfo(NrmP Qof, hFeigaut (rNe 8PBQ), oFrignuorne- 8reBg) uolra nteodn-prerogcuelsasteds  (pqrNoc,eFsisgeusr (eq8NC, ).
FTighuurse, 8aCd)v. aTnhcuesd, alidnveasnocfedth leinhesig ohfl ythseu hscigehpltyib sluestcyepotilbolgey tyspuochlogays sSuEcFh 4a0s aSnEdF 4R0R aAnd6 0
RpRrAes 6en0 tpedretsheentheidg htheset hviaglhuest. vInaltuhes.e Icna tshees,seth ceacsoeslo, rthger acdoileonr tgsrfaodriNenPtQs f(oFri gNuPreQ8 (BF)iginurthe e
8Bh)e ainlt hthyel heaevaeltshtye nledaevdest otewnadredds tgorweeanrdwsh girleein twhheiilnef ienc tehde lienafvecetsetdh leeNavPeQs tvhael uNePiQnc vreaalused 
inacsrethaseecdo alosr thgera cdoileonr tgcrhaadniegnetd chfraonmgebdl ufreotmo vbiluolee tof rvoimoletth ferolemv ethl eo fle3v0e0l µofm 3o0l0m μm−2osl −m1−o2 f
s−P1 AofR P, aAnRd, ansdim ai lsairmciolanrd ciotinodnitwioans wobasse rovbesderfvoerdq fNor.  qN. 
 
FiFgiugruer e8.8 R. Resepsopnosnes etot odidsiesaesaes estsrtersess sasa sa afufnucntciotino nofo tfhteh ephpohtootsoysnytnhtehteictiaclalyll yacatcivtiev erardaidaitaiotino n(P(APAR)R )
lelveevle ol fo cfocmo mmono nbebaena nlinliense scocnofnofromrminign gddififfefreernent ttytyppoolologgieise.s B. BSFS F101,0 A, ALLBB 35305,0 D, DAABB 29259:5 m: modoedreartaetleyl y
 
Plants 2022, 11, 1371 13 of 26
resistant (MR). SAB 618, SAB 686: moderately susceptible (HS). INB 841 and INB 604: susceptible (S).
RRA 60 and SEF 40: highly susceptible (HS). (A) The coefficient of photochemical quenching (qP);
(B) non-photochemical quenching (NPQ); (C) non-photochemical cooling coefficient (qN). Images
obtained with IMAGINE-PAM, the change in color gradient from violet to red signifies a change in
value from higher to lower for each variable. Means and error bars correspond to 96 AOIs (areas
of interest) for each condition (healthy and infected); i.e., six AOIs were taken for each leaf, among
four plant leaves selected between the fifth and eighth trifoliate leaves (from apex to base) at the
beginning of physiological maturity, from four plants of each advanced line of common bean.
2.4. Correlations of Disease Susceptibility Index (DSI) with Chlorophyll A (Chla) Fluorescence
Parameters and Agronomic Variables
Chlorophyll a (Chla) fluorescence parameters were found to be related to the agro-
nomic variables that were also related to DSI (Table 2). For example, DSI was negatively
correlated with most parameters of chlorophyll fluorescence, significantly affecting the frac-
tion of energy devoted to the photosynthetic process (qP ratio coefficient r = −0.82) as well
as the rate of electron transfer (ETR r = −0.72). Increasing the susceptibility level increased
photosynthetic efficiency (r = 0.27) as well as leaf temperature (r = 0.32), but the difference
in leaf temperature (leaf temperature differential, LTD) had a negative relationship with the
photosynthetic efficiency (r = −0.29). With the dry matter accumulation variables, DSI was
positively correlated with the increase in root biomass (r = 0.28), but it was negatively cor-
related with the other parameters such as stem biomass (r = −0.4), pod biomass (r = −0.29)
and canopy biomass (r = −0.33). When leaf temperature increased, the functioning of the
photosynthetic apparatus was compromised, specifically for photosynthesis (qP r = −0.3)
and the rate of electron transfer (ETR r =−0.37). However, when leaf temperature increased,
the plant also increased the dissipation of energy in the form of non-regulated energy (YNO,
r = 0.36). At the agronomic level, the increase in leaf temperature compromised the number
of grains per pod (r = −0.43) because the number of aborted grains increased too (r = 0.36).
Likewise, leaf temperature correlated negatively with the chlorophyll content index (CCI
r = −0.41), as well as with ambient temperature (r = −0.9), relative humidity (r = −0.52)
and leaf temperature differential (r = −0.52). Since we observed a negative relationship
between different parameters of chlorophyll a (Chla) fluorescence (ETR, qP and NPQ) and
DSI, other important correlations were explored to improve confidence in the phenotyping
of the advanced bean lines. For example, significant correlations were found between the
ETR and stem biomass (r = 0.36) and the fraction of energy devoted to photosynthesis (qP)
and pod biomass (r = 0.30). Finally, the energy dissipated as heat (NPQ) was negatively
correlated with root biomass (r = −0.31).
Table 2. Correlation coefficients (r) between the disease susceptibility index (DSI), leaf temperature
(LT; ◦C), electron transport rate (ETR; µmol e− m−2 s−1), coefficient of photochemical quenching
(qP), non-photochemical quenching (NPQ) and other plant attributes for 52 bean lines grown under
acid soil and high temperature stress conditions.
Variables
Variables
DSI LT ETR qP NPQ
Disease susceptibility index (DSI) 0.32 * −0.72 *** −0.82 *** −0.38 ***
Initial fluorescence (F0) −0.49 *** −0.19 0.06 0 0.04
Maximum fluorescence (Fm) −0.66 *** −0.39 ** 0.39 *** 0.27 * 0.1
Effective quantum yield of photochemical energy conversion in
PSII (Y(II)) −0.52 *** −0.42 *** 0.8 *** 0.67 *** 0.3 **
Quantum yield of regulated energy dissipation (Y(NPQ)) 0.53 *** 0.07 −0.69 *** −0.48 *** −0.88 ***
Quantum yield of non-regulated energy dissipation (Y(NO)) −0.04 0.36 ** −0.19 −0.18 0.69 ***
Non-photochemical quenching (NPQ) −0.38 *** 0.1 0.41 *** 0.23 *
Non-photochemical cooling coefficient (qN) 0.48 *** 0.2 −0.65 *** −0.36 ** −0.77 ***
Coefficient of photochemical quenching (qP) −0.82 *** −0.3 ** 0.78 *** 0.32 **
Coefficient of photochemical quenching (qL) −0.57 *** −0.09 0.32 ** 0.8 *** 0.1
Electron transport rate (ETR, µmol e− m−2 s−1) −0.72 *** −0.37 ** 0.77 *** 0.41 ***
ETRmax (ETR maximum; µmol e− m−2 s−1) −0.13 −0.09 0.31 * 0.29 * 0.07
Plants 2022, 11, 1371 14 of 26
Table 2. Cont.
Variables
Variables
DSI LT ETR qP NPQ
Maximum saturating irradiance (Ek; µmol m−2 s−1) −0.15 0.04 0.31 * 0.12 0.08
Dark respiration rates (Rd; µmol CO2 m−2 s−1) −0.22 −0.05 0.01 0.17 −0.02
Light compensation point (LCP; µmol m−2 s−1) −0.15 −0.06 −0.02 0.08 −0.01
Photosynthetic efficiency (α; µmol CO2 µmol protons−1) 0.27 * −0.03 −0.33 ** −0.12 −0.22
Chlorophyll content index (CCI; SPAD) 0.13 −0.41 ** −0.13 −0.15 −0.09
Leaf temperature (LT; ◦C) 0.32 * −0.37 ** −0.38 ** 0.1
Stomatal conductance (gs; µmol H2O m−2 s−1) −0.13 −0.23 0.17 −0.03 0.01
Ambient temperature (◦C) −0.19 −0.9 *** 0.27 * 0.07 −0.09
Relative humidity (%) −0.07 −0.52 *** 0.14 −0.1 0
Leaf temperature differential (LTD; ◦C) −0.29 * −0.98 *** 0.35 ** 0.19 −0.08
Root biomass (g) 0.28 * −0.1 −0.13 0.05 −0.31 *
Stem biomass (g) −0.4 *** −0.15 0.36 ** 0.22 0
Leaf biomass (g) −0.2 0.04 0.2 0.03 0.04
Flower bud biomass (g) −0.19 −0.07 0.17 0.15 0.15
Flower biomass (g) −0.1 0.07 0.01 −0.01 0
Pod biomass (g) −0.29 * −0.11 0.23 0.3 ** 0.11
Viable seeds (number) −0.03 −0.43 * 0.27 0.01 −0.01
Non-viable seeds (number) −0.03 0.36 * −0.02 −0.06 0.15
Canopy biomass (CB, g) −0.33 ** −0.11 0.32 * 0.15 −0.01
Mean values were used in the correlation analysis and *, ** and *** represent levels of significance at 0.05, 0.01 and
0.001, respectively.
3. Discussion
3.1. Magnitude of Leaf Disease Severity Modifies Energy Pathways within the Photosynthetic Apparatus
In our study we found that pathogen-related biotic stress generated differential re-
sponses in chlorophyll fluorescence parameters. The changes related to the increase of
initial fluorescence (F0), the reduction of maximum fluorescence (Fm) and the maximum
efficiency of PSII photochemistry (Fv/Fm). These parameters responded by activating
acclimation mechanisms with the aim of adjusting the photosynthetic machinery to the
new conditions [40]. The interaction between plant and pathogen caused alterations in
several physiological processes, in which photosynthetic reaction to light, carbon assimila-
tion and respiration-associated processes were negatively affected [41]. We found that the
maximum efficiency of PSII photochemistry, determined by Fv/Fm, decreased to values
below 0.80 in disease-stressed leaves [42], and this could be considered as a response to
the infection process presenting greater damage to the photosynthetic apparatus, resulting
in two different processes [43]. On the one hand, the decrease in Fv/Fm revealed that
infection interferes with chloroplast protein synthesis, confirming that oxidation causes
detrimental effects at the chloroplast level [44]. On the other hand, the decrease in Fv/Fm
may be attributed to changes in the number of functional reaction centers of PSII, presenting
increased inactivation of reaction centers through damaging processes, and/or an increase
in the rate constant of the non-radiative dissipation of excitation energy [13,14]. Likewise,
the decrease in the rate constant of the PSII photochemistry led to an increase in the initial
fluorescence at the PSII open centers (F0), a feature that was observed in infected leaves
that showed increases in F0 compared to healthy leaves. This suggests a loss of excitation
energy, which is required during electron transfer from pigments to reaction centers [45].
In the case of reduced maximum fluorescence (Fm) in infected leaves, it is possible that
maximum quinone reduction did not occur, because reaction centers may not function
properly due to an operationally inefficient light energy capture process [19,46].
We found that infected leaves had to make certain adjustments to cope with the
infection process, such as decreases in Y(II) and qP photochemical quenching, resulting
in a decreasing electron transport rate (ETR) compared to healthy leaves [40]. Moreover,
this inhibition of light-dependent pathways was accompanied by an increase in qN [47].
Similarly, an increase in Y(NO) was detected at the expense of a decrease in NPQ condition,
as was also observed by Suárez at el. [48]. These observed changes are possibly attributable
to irreversible damage in the PSII reaction centers due to the infection process, and they
Plants 2022, 11, 1371 15 of 26
resulted in possible photoinhibition as reflected by low Fv/Fm levels [49]. However,
greater energy allocation towards the heat dissipation or non-photochemical pathway
(NPQ) was observed in healthy leaves compared to infected leaves. This could indicate
that pathogen infection may increase or decrease non-photochemical processes of energy
dissipation [40,49].
Looking specifically at the behavior of NPQ we found certain adjustments due to
the incidence of infection. It would be expected that greater allocation of energy to the
non-photochemical pathway (NPQ) is presented as a photoprotective mechanism [4]. This
would likely lead to lower stomatal conductance and increasing photosynthetic function,
thus limiting the negative feedback on biomass productivity and/or acting as an escape
from disease stress [50]. However, we observed that in infected leaves, the energy allocation
to NPQ was lower than that presented by healthy leaves. This situation can lead to a low
pH gradient (∆pH) across thylakoid membranes, reflecting a high ATP demand due to
metabolic stimulation in the host plant leaves [49]. Likewise, it has been observed that
these decreases in NPQ denote a loss of chloroplast functionality, possibly related to leaf
senescence [51]. Furthermore, under infected conditions, we found negative correlations
between Y(NO) and the non-photochemical energy pathways of NPQ, qN and Y(NPQ), and
low correlations between F0, Y(II), qP and qL. The above-mentioned relationships indicate
that infected leaves devoted a larger proportion of the energy absorbed by PSII to other
non-regulated energy dissipation processes [Y(NO)] [52]. The increase in Y(NO) reflect the
plant’s inability to protect itself against photochemical damage [53]; i.e., high Y(NO) values
and low NPQ values are reflected in a suboptimal capacity for photoprotective reactions,
which ultimately leads to photoinhibition [52].
3.2. Physiological Response Differences among Common Bean Lines Reflect Possible Disease
Resistance Mechanisms
Plant defense responses in terms of photosynthetic activity have mostly been studied
independently in the past [54]. However, it has been observed that it is possible to identify
materials that are disease-resistant in addition to serving as a basis for signal transduction
for plant immune defense [55,56]. The common bean originates from two main gene pools
and some diseases [8], due to the process of coevolution, present the same classification and
higher degrees of pathogenicity within specific gene pools [9,57]. These studies indicate
that plant photosynthesis and immune defense processes are interconnected [58]. In our
study, climatic conditions (high air humidity, high rainfall and high air temperature) in the
Amazon region were favorable for the more frequent development of diseases. However,
in the previous studies conducted by Suárez et al. [48,59,60], we identified bean lines that
were adapted to abiotic stress conditions at the physiological level and these lines produced
grain yields that were above the Colombian average yield.
The specific adaptation level of a bean line depends on its physiological responses and
degree of susceptibility to a given stress condition. For example, based on the physiological
responses of the lines evaluated under healthy and infected conditions, we classified bean
lines into four typologies. We found six common bean lines belonging to the moderately
disease-resistant typology, with five of them belonging to the Mesoamerican gene pool
(ALB 350, SMC 200, BFS 10, SER 16, SMN 27) and one belonging to the Andean gene pool
(DAB 295), with a higher energy allocation towards photochemical pathways (Y(II), qP, qL,
ETR) [61]. DAB 295 stands out as a line that was characterized by a greater allocation capac-
ity in Y(II), allowing it to maintain higher ETR levels than the other bean lines. Likewise,
its high qP and qL values indicated greater QA oxidation with a greater proportion of PSII
reaction centers open and connected, showing optimal functioning in the photosynthetic
apparatus [13]. In the case of the ALB 350 and BFS 10 lines, it was observed that they
maintained a higher proportion of energy allocation to Y(II). However, these two bean
lines belonging to the moderately resistant typology were the ones that most used the
non-photochemical pathway (NPQ) for improving their stress tolerance response [40,49].
Thus, these two lines responded to disease stress by activating the acclimation mechanisms
Plants 2022, 11, 1371 16 of 26
to adjust the photosynthetic machinery with the objective of maintaining their photosyn-
thetic activity, which included the increase in energy dissipation capacity, and this was
detected by the increase of the non-photochemical pathway without altering the yield of
PSII Y(II) [40].
The bean lines that formed the moderately disease-susceptible typology (SMR 84,
SMC 33, SMR 193, RRA 3, SMR 72, SIN 509-1, SMR 140, RRA 177, SMC 101, SMC 205,
CALIMA, DAB 525, SMC 216, SMC 199, SAB 618 and SAB 686) had an average DSI value
of 0.33, with a range from 0.24 to 0.39. This typology was characterized by lower efficiency
in the functioning of the photosynthetic apparatus compared to the lines of the moderately
resistant typology. Some outstanding traits were found in the old commercial Andean
bean cultivar CALIMA, which presented higher NPQ and qN values [40], indicating higher
dissipation of excess energy in PSII in the form of heat as a protection mechanism against
disease stress [62,63]. This change in energy allocation allowed the CALIMA bean cultivar
to maintain higher values in qP and qL with a high energy fraction (Y(II)), similar to that
presented by the ALB 350 bean line, allowing photosynthetic activity to be maintained
intact and without being affected by the rate of electron transfer to PSII [4,64]. The bean line
SMC 33 exhibited high values of qP and therefore the infection from the pathogen did not
generate damage to the reaction centers of PSII, as they remained open without affecting
the reduction in the proportion of energy used for photochemical processes, which resulted
in higher values of ETR [65].
The incidence of the pathogens did not favor the bean lines SER 394, ALB 352, ALB
351, ICA QUIMBAYA, SIN 351-1, SMC 135, RRA 60 and SEF 40, which conformed to the
highly disease-susceptible typology due to their values of DSI being above 0.69. This
typology presented low values of qP, and this parameter is considered useful to estimate
the saturation level of PSII under stress conditions [66]. These low qP values were due
to a degradation of photosynthetic pigments in leaves, in addition to high production
of ethylene and reactive oxygen species (ROS), which affected the biochemical function
of the chloroplast [20]. Likewise, an increase in the NPQ fraction was observed with
the genotypes ICA QUIMBAYA, RRA 60 and SIN 351-1. This effect is considered as a
photoprotective mechanism in these lines to mitigate infection [23]. However, this increase
was probably more associated with the limitation of CO2 assimilation, possibly due to an
imbalance between the activity of PSII and the electron requirement for photosynthesis,
which was reduced due to disease stress, and the above process was supported by the low
ETR values observed [67]. These conditions led to an overexcitation of light energy and
subsequent photoinhibition [68]. Other lines, such as SEF 40, SMC 135, ALB 352 and ALB
351, only presented an increase in non-photochemical dissipation (qN), which was reflected
through the activation of non-photochemical processes that led to the dissipation of non-
radiative energy, leading to changes in the trans-thylakoid pH gradient and consequently
to photoinhibition and disconnection among light-harvesting complexes [69].
3.3. Identification of Mechanisms of Energy Use among Moderately Resistant and Susceptible
Bean Lines
Pathogen incidence is known to disrupt the function of the photosynthetic appa-
ratus, resulting in differences among the bean lines [44]. Based on the response mech-
anisms observed among different bean typologies, we found two types of mechanistic
responses: (i) greater allocation of energy to the photochemical pathway; and (ii) the ability
to distribute energy to non-photochemical pathways. For example, in lines within the
moderately susceptible (SAB 618, SAB 686), susceptible (INB 841, INB 604) and highly
susceptible (RRA 60, SEF 40) typologies, fluorescence imaging showed increased values
in the maximum efficiency of PSII photochemistry in infected leaves compared to healthy
leaves. This stress-induced decrease in the Fv/Fm ratio may result in an increase in the
non-photochemical quenching processes, which decreases the value of Fm [70]. This can
also be accompanied by photoinactivation, leading to oxidative damage and loss of PSII
reaction centers [71], both of which are associated with increased value of F0 [72,73].
Plants 2022, 11, 1371 17 of 26
We found that the function of the photosynthetic apparatus is severely affected in
infected leaves. For example, with the RRA 60 and SEF 40 lines, PSII Y(II) yield was
proportionally reduced with increasing PAR level starting at 300 µmol m−2 s−1, indicating
no photosynthetic activity at 500 µmol m−2 s−1 and resulting in total loss of electron
transport at a PAR level of 600 µmol m−2 s−1. This behavior was expected because of the
disease severity leading to inhibition of light-dependent reactions (Y(II), qP and ETR), and
causing a severe loss of PSII function [40,47]. This loss was due to a reduction in the capture
of excitation energy from open PSII reaction centers [74], which promotes an increase in
the proportion of closed PSII reaction centers [67]. Thus, since the Fv/Fm ratio represents
the balance between the PSII photodamage rate and the PSII repair rate [71] and it is not
related to changes in light absorption [75], we hypothesized that infection interferes with
chloroplast protein synthesis [44].
3.4. Traits Associated with Lower Values of DSI Favor Better Agronomic Performance
When analyzing the agronomic performance of the evaluated bean lines we found that
the lines that conformed to the moderately resistant typology (ALB 350, SMC 200, BFS 10,
SER 16, SMN 27, DAB 295) had a greater capacity to increase biomass production at the
canopy level. This was due to a greater resistance to disease stress (lower leaf damage) that
made it possible to allocate more energy to the photochemical pathway (qP), contributing
to a better rate of CO2 fixation and plant development. Thus—in similar environments
with comparable soil conditions—higher CB values could be an indicator of a genotype’s
greater capacity to fix CO2, assimilate nutrients and effectively use water under both stress
conditions as well as optimal conditions.
The DSI was created with the objective of being a phenotyping tool for the selection of
bean lines with lower susceptibility to disease stress based on Chla variables. The DSI is
based on calculating the differences in the responses of different Chla variables between
healthy and infected leaves. The DSI uses the different chlorophyll fluorescence parameters
related to different energy pathways, the electron transfer rate and the different points on
the photosynthetically active radiation (PAR) response curve, which show the functional
status of the photosynthetic apparatus. Therefore, DSIs based on chlorophyll fluorescence
parameters could be useful to identify bean lines with higher levels of adaptation to
combined biotic and abiotic (acid soil and high temperatures) stress conditions. This
observation is consistent with previous studies by Suárez et al. [48,59,60,76]. These previous
studies showed that a few bean lines (ALB 350, SMC 200, BFS 10, SER 16, SMN 27, DAB 295)
are capable not only of greater accumulation of photosynthates but also their mobilization
to developing grains under stress conditions. Therefore, we can highlight, among others,
the BFS 10 line, which demonstrated a high degree of adaptation under different types of
abiotic stress. This is because it has a high capacity in the functioning of its photosynthetic
apparatus, as we observed in this study, and it also has greater capacity to maintain its
physiological processes under both biotic and abiotic stress conditions. Thus, BFS 10 could
serve as a very good parent to develop multiple stress-adapted common bean lines.
It has been shown that the high temperatures present in the western Amazon region
of Colombia impact the phenology and grain yield of common bean lines [59,76]. These
conditions can also effect the plant–pathogen interaction and thereby influence genotypic
differences in disease resistance [77]. Bean lines of the moderately resistant typology
presented phenotypic variation and plasticity [78] at the level of their photosynthetic
apparatus. These lines, in addition to increasing energy devoted to carbon fixation (qP),
equally increased other dissipation pathways in the form of heat (NPQ) or non-regulated
(qN) energy. These moderately resistant bean lines can surely be used as progenitors in
bean breeding programs that aim to combine disease resistance with abiotic stress (acid
soil and high temperature) resistance.
Plants 2022, 11, x FOR PEER REVIEW 18 of 26 
P lants 2022, 11, 1371 18 of 26
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Plants 2022, 11, x FOR PEER REVIEW 19 of 26 
 
with three replications where the plots in each block corresponded to each bean line eval-
uated. Each plot consisted of four rows with a distance between rows of 0.6 m, and each 
row was 2 m long. The bean seeds were sown at a distance of 15 cm, equivalent to 11 
Plants 2022, 11, 1371 plants m−2. Soil preparation and planting were done manually. No amendmen19tso fo2r6 prod-
ucts to regulate soil pH were added to the soil, nor was any type of chemical compound 
added to control the incidence of disease. The above-mentioned management ensures the 
simpliolat rciotnys iosft etdheo fifnofuerctrioowns lwevitehl acodnisdtainticoenbse twwiethen trhoowsse oofb0s.6ermve, adn idne tahche rfoawrmwearss’2 fmields in 
welosntegr.nT Ahembaezaonnsieae.d s were sown at a distance of 15 cm, equivalent to 11 plants m−2. Soil
preparation and planting were done manually. No amendments or products to regulate
soil pH were added to the soil, nor was any type of chemical compound added to control
4.3th. Seeilneccitdioenn coef oInf fdeicsteeads ea.nTdh Heeaablothvye -Lmeaevnetiso fnoerd Pmhyasniaogloegmiceanl tEevnasluuraetsiotnh e similarity of the
infeDctuiorinnlge vtehlec ofnlodwitieornins gw ipthertihoodse (oBbBsCerHve d65in) itnh ebfoarthm ecrrso’pfi-egldros winiwnge ssteransoAnms auzonndiear.  field 
conditions, eight plants per plot were selected in each block (n = 3). Four plants with 
4.3. Selection of Infected and Healthy Leaves for Physiological Evaluation
healthy leaves (n = 4) located between the fifth and eighth trifoliate leaves (from the apex 
to the bDausrei)n wg tehree flseolwecetreindg aps ewrieoldl a(Bs BfoCuHr 6p5l)anintsb wotihthc rionpfe-gcrtoewd ilnegavseesa s(onn =s 4u)n wdeirthfi ethlde pres-
conditions, eight plants per plot were selected in each block (n = 3). Four plants with
enhceea lothf ythleea vaesse(xnu=al4 )stloacgaet e(dRbheiztwoceteonntiha esfiolfathnia)n odfe tighhet hwteribfo blialitgehleta (vTehsa(fnraotmepthhoeraups ecxutcoumeris 
(Frthaenkba) sDe)ownker, e[7se9l]e)c. tTedhea sinwfeelcltaesdf oleuarvpelsa nsthsowwitehdi nthfeec tfeirdslte vaivseisb(lne s=y4m) wptitohmthse wpirtehs ean sceeverity 
levoeflt hoef afsoeuxru, awl shtaicghe (pRrheiszeoncttoendia isno ltahnei) foofrtmhe owfe sbmbalilglh wt (eTth sapnaottesp hthorauts lcautceurm tuerrisn(eFdr ainkto)  light 
brDowonk s, p[7o9t]s) .wTihteh idnfaerckt emd aleragvines  s[h1o2w]. eIdn tbhoethfi rhsteavlisthibyle asnydm ipntfoemctsedw iltehavaesse,v tewrioty cliervceullar ar-
eaos foffo iunrt,ewrehsict hinp trhesee cnetendtrianl tphaerfto ormf eoafchsm leaallflwete twseproet ssethleacttleadte rfotur rmnedasiuntroemligehnttb (rFoiwgunre 10). 
Thsep oatrseaw iinth wdharickhm thareg iinnfso[r1m2]a. tIinonb ootnh dheifafletrheynat ncdhlionrfoecpthedyllle falvueosr,etswcoenccirec uvlaarriaabrelaess owfas ob-
taiinnetedr e(s5t9i nbethaen cleinnetrsa ×l p 4a prtlaonf tesa cpherle laiflneet ×w 4e rleeasveleesc tpeedr fporlamnte a×s 3u rleemafelnetts( F×i g2u AreO1I0s) .pTehr eleaflet, 
fora rae atoitnawl ohfi c5h66th4e uinnfiotsrm oaf tdioantao pnedri fefearcehn tocfh tlhoero hpehaylltlhflyu oorre isncfeenccteedva lreiaabf lceosnwdaistioobnt apineer dblock). 
(59 bean lines × 4 plants per line × 4 leaves per plant × 3 leaflets × 2 AOIs per leaflet, for
Thaist oetvaal loufa5t6io64n uwnaitss coafrdriaetda  poeurt eianc hthoef ftiheeldh teoa lethvyalouraitnef ethctee ddilseeaaf sceo nbdyi toiobnseprevrinbglo tchke). natu-
ralT ohcisceuvrarleunactieo onfw thase cwarerbie dbloiguht itn inth tehfiee mldotoste avpalpuraoteprthiaetde issetaagsee,b wy ohbicsehr vcionrgrethspe onnatduerdal to the 
maoicncu frlroewnceeroinf gth epwereibodb li[g8h0t].i nTthee mobosjetcatpivpero opfr iathtees tmageen, twiohnicehdc omrraenspaognedmeedntto wthaesm taoin obtain 
beflttoewr edrisncgripmeriinoadti[o8n0] .bTehtwe oebenje ctthivee loinf ethse fmore nthtieoinre dimseansaeg seumsecnetpwtibasiltiotyo btya iindbeenttiefrying a 
nudmisbcreirm oinf altiinoensb betawseden otnhe thline eds ifsoeratshee isrudsicseapsteibsiulsitcyep itnibdielixty (bDySiId) eanntidfy finingdaingu mthbe rroeflation-
shliipn eosfb tahsee dDoSnI twheitdhi stehaes egrsauisnce ypiteibldili [ty81in,8d2e]x. (DSI) and finding the relationship of the DSI
with the grain yield [81,82].
 
Figure 10. Selected areas of interest (AOIs) in each leaflet of healthy and infected leaves of Phase-
Figoulursev 1u0lg. aSreislected areas of interest (AOIs) in each leaflet of healthy and infected leaves of Phaseolus 
. The figure shows the maximum quantum efficiency of PSII (Fv/Fm) for healthy and
vulgaris. The figure shows the maximum quantum efficiency of PSII (Fv/Fm) for healthy and infected 
infected leaves. The color gradient showing a blue color in healthy leaves indicates leaves without
leaves. The color gradient showing a blue color in healthy leaves indicates leaves without disease 
disease stress. The green color indicates a decrease in the value of the Fv/Fm ratio as a response to
stress. The green color indicates a decrease in the value of the Fv/Fm ratio as a response to disease 
disease stress.
stress. 
 
Plants 2022, 11, 1371 20 of 26
4.4. Chlorophyll (Chla) Fluorescence and Imaging for the Chla Parameters
Responses of Chla parameters in healthy and infected leaves were monitored using
a MAXI-Imaging PAM M-Series (Heinz Walz GmbH, Effeltrich, Germany), equipped
with 44 high-power royal blue (450 nm) LED lamps furnished with collimating optics
that provided pulse-modulated excitation light and at the same time served for actinic
illumination and saturation pulses. For the calibration of the light intensities, an ULM-500
light meter and recorder was used, which was equipped with a micro quantum sensor
(Heinz Walz GmbH, Effeltrich, Germany). Chlorophyll a (Chla) fluorescence emissions were
captured using a CCD (charge-coupled device) camera with a resolution of 640 × 480 pixels
and a visible sample area of 24 × 32 mm on each leaf. From the color gradients and trends
with increasing photosynthetically active radiation (PAR) obtained with the Imaging-PAM
M-Series and Imaging WIN version 2.32 software (Heinz Walz GmbH, Effeltrich, Germany),
different parameters related to chlorophyll fluorescence (Chla) were determined. The
bean leaves were individually fixed to a holder at a distance of 18.5 cm from the CCD
camera in order to perform a 60-min dark adaptation process, a process that was performed
with the aim of fully opening (i.e., oxidizing) the PSII reaction centers and minimizing
non-photochemical energy dissipation.
After adaptation, the leaves were exposed to a weak, modulated light beam
(0.5 µmol m−2 s−1, 100 µs, 1 Hz) with the aim of determining the initial fluorescence
(F0). A saturating pulse of white light (2400 µmol m−2 s−1, 10 Hz) was then emitted for
0.8 s to determine the emission of maximal fluorescence (Fm) or when all PSII reaction centers
were expected to be “closed”. After 10 min, the steady-state chlorophyll fluorescence yield
(Fs) of plants under actinic illumination was determined and a second saturation pulse, with
the same settings as for determining Fm, was applied to measure the maximum light-adapted
fluorescence yield (F ′
m ). After the application of continuous actinic light saturating pulses,
the fluorescence level increased to the Fm level and up to the F ′
m level, thereby determining
the amount of energy taken by the photochemical pathway [qP = (F ′ − F)/(F ′
m − F ′m o )] [83].
Using the above protocol, different parameters of Chla in dark-adapted and light-adapted
states were calculated, as described as follows. The maximum quantum yield of the PSII
photochemistry was calculated (Fv/Fm = (Fm − Fo)/Fm) as well as the different routes
of the energy fractions. Among these were the effective quantum yield of photochemical
energy conversion in PSII (Y(II) = ∆F/F ′
m ) as well as the quantum yield of non-regulated
non-photochemical energy loss in PSII (Y(NPQ) = (Fs/F ′
m ) − (Fs/Fm)) and the quantum
yield of non-regulated heat dissipation and fluorescence emission (Y(NO) = Fs/Fm) [84].
The sum of these three yields is equal to 1.
In order to determine the incidence of the irradiance level on the PSII fluorescence emissions,
rapid light curves (RLCs) composed of 12 steps, with durations at each PAR level of 20 s, were
performed (0, 1, 21, 56, 111, 186, 281, 336, 396, 461, 531, 611, 701 µmol photons m−2 s−1). At each
point on the curve, the electron transport rate (ETR) of the plants was calculated using the
following formula: ETR (µmol e− m−2 s−1) = (∆F/F ′
m ) × PAR × 0.5 × 0.84 [85,86] where
∆F/F ′
m refers to the effective quantum yield of photochemical energy conversion into PSII
[i.e., Y(II)] at a given radiation level; PAR is the nominal incident photon flux density in
terms of µmol m−2 s−1; 0.5 refers to an assumed stoichiometric distribution of absorbed
light energy between the two photosystems; and 0.84 denotes an empirical absorption
efficiency of 84% of incident light in higher plants. Using the results of the RLCs, the
maximum ETR (ETRmax), the maximum saturating irradiance (Ek) and the photosynthetic
efficiency (α) were calculated. α was calculated as the initial slope of the curve at the first
light passage and ETRmax was considered as the highest calculated ETR value of the curve
(ETR = ETRmax × tanh (αETR× PAR/ETRmax), where ETR is the relative electron transport
rate mentioned above, ETRmax is the saturated ETR, tanh is the hyperbolic tangent function,
αETR is the efficiency of the electron transport (initial slope of the ETR vs. irradiance
curves) and PAR is the incident irradiance [87].
Plants 2022, 11, 1371 21 of 26
4.5. Physiological, Environmental and Agronomic Performance Variables
Between 7:00 to 9:00 am, on four fully developed leaves selected between the fifth and
eighth trifoliate leaves (nodes were counted from apex to base) at the onset of physiological
maturity of each plant (n = 4), the leaf chlorophyll content index (CCI) was measured
using the SPAD502 (Minolta Camera Co., Osaka, Japan) chlorophyll meter. Leaf stomatal
conductance (gs), leaf temperature (LT, ◦C) and relative humidity (RH %) were measured
using a leaf porometer (Model SC-1, Decagon Devices, Inc. Pullman, WA, USA). The
difference between leaf temperature and ambient temperature was used to calculate the
leaf temperature differential (LTD) [48]. In each plot, a row segment of 0.5 m (equivalent to
an area of 0.3 m2) was selected, and five plants were collected for destructive sampling, an
activity that was carried out at the time of harvest (BBCH 89) in which the dry biomass of
the different components of the plant (root, stems, leaves, flower buds, flowers, pods) was
recorded as the total biomass of the canopy. The average number of viable and non-viable
grains per pod was also measured for each bean genotype.
4.6. Developing and Validating the Disease Susceptibility Index
The disease susceptibility index (DSI) was developed to quantify the level of pathogen
influence on photosynthetic functioning under stress and non-stress conditions. The DSI
was adjusted for the disease stress intensity presented in each season. This index eliminates the
effect of intra- and intergenotypic variability, showing the level of susceptibility of individual
genotypes in the context of the population median [48]. To develop the DSI, as a first step, an
initial standardization ([0–1]) of the data was performed using the value obtained from each
genotype’s chlorophyll fluorescence variable (Chla Vi) divided by the geometric value of the
whole individual experiment (year repeat); i.e., Chla Vi [0–1]= Yj/Ÿ, where Chla Vi = any of
the monitored fluorescence ith variables, Yj = mean value of the individual jth genotype,
Ÿ = geometric mean of the whole experiment and [0–1] are standardized values between a
range of 0 to 1. Once the data were standardized, two sub-indices were calculated. The first
sub-index (SI1i) considered the performance of the photosynthetic apparatus of the bean
lines in healthy leaves from the Chla Vi; this was calculated from the difference between the
genotype that had the highest value obtained (Max Chla Vi, the more the better or the less
the better) and the value of each jth genotype (SI1 = Max Chla Vi − Chla Vij). The second
sub-index (SI2i) considered the difference between each healthy leaf (HL) and one infected
(AL) by the pathogen (SI2i = HL Chla Vi − AL Chla Vi) in each jth genotype. After obtained
the two sub-indices for each variable, we added the differences calculated and then added
the score obtained for all variables. Thus, we developed and validated the DSI by having a
greater difference within any genotype, in terms of photosynthetic characteristics, between
the healthy leaf and the infected leaf with the pathogen. Where higher DSI values were
observed with certain genotypes, they were considered as bean genotypes with greater
susceptibility to disease stress (DSI [0–1] = ΣChla Vi SI1i + Chla Vi SI2i).
4.7. Data Analysis
Using the different chlorophyll fluorescence variables, such as DSI and grain yield, a
cluster analysis was performed to identify moderately resistant, moderately susceptible,
susceptible and highly susceptible bean genotypes [12,88]. From these typologies, a prin-
cipal component analysis (PCA) was used to identify the relationship of genotypes with
chlorophyll fluorescence variables and to test the effect of disease stress on the physiological
response in maintaining a higher photosynthetic efficiency, a situation that was tested by
means of a Monte-Carlo permutation test. Statistical differences for each of the chlorophyll
fluorescence variables were analyzed by fitting a linear mixed model (LMM). For this
purpose, the fixed effect within the LMM was the bean genotype, and the blocks within the
monitoring period (repeated measures) were included as random effects. Assumptions of
normality and homogeneity of variance were evaluated using an exploratory analysis of
residuals. Differences between genotypes were analyzed with Fisher’s post-hoc LSD test
with a significance of α = 0.05. Pearson correlation analyses were performed for each of
Plants 2022, 11, 1371 22 of 26
the chlorophyll fluorescence variables in both healthy and disease stressed leaves, as well
as analyses of correlation between DSI, LT, ETR, qP and NPQ with different chlorophyll
fluorescence, environmental and agronomic variables. The graphs were visualized in four
quadrants plotting the corresponding means and statistical significance on each axis. LMMs
were performed using the lme function of the nlme package, and cluster analysis, PCA and
graphical outputs were performed in the packages ade4, ggplot2, factoextra and corrplot
in R language software, version 3.4.4 [89] (R Development Core Team, 2019), using the
interface in InfoStat [90].
5. Conclusions
The photosynthetic apparatus of the common bean was markedly affected by leaf
disease stress as revealed by chlorophyll fluorescence parameters (initial F0 and maximum
Fm fluorescence; the maximum quantum yield of the PSII photochemistry Fv/Fm; the
fraction of energy devoted to photochemical processes qP; and electron transfer rate ETR).
Based on the chlorophyll fluorescence responses of naturally infected and healthy leaves
of 59 common bean lines, we classified the bean lines into four typologies ((i) moderately
resistant, (ii) moderately susceptible, (iii) susceptible, and (iv) highly susceptible) based on
the disease susceptibility index (DSI). Five bean lines from the Mesoamerican gene pool
(ALB 350, SMC 200, BFS 10, SER 16 and SMN 27) and one line from the Andean gene pool
(DAB 295) were identified as promising genotypes that can combine disease resistance
with abiotic stress resistance. These lines allocated a higher proportion of energy to pho-
tochemical processes, which increased the rate of electron transfer. Based on the results
from this study, we suggest that DSIs generated from chlorophyll fluorescence responses to
pathogen infection could serve as a phenotyping tool in common bean breeding programs
for evaluating large number of genotypes under field conditions and for identifying and/or
developing common bean lines with multiple stress resistances.
Supplementary Materials: The following supporting information can be downloaded at: https:
//www.mdpi.com/article/10.3390/plants11101371/s1. Supplementary Table S1: 59 bean genotypes
from the Mesoamerican and Andean gene pools from crosses between different species (Phaseolus
vulgaris, P. acutifolius, P. coccineus and P. dumosus).
Author Contributions: Conceptualization, J.C.S., J.I.V., M.O.U. and I.M.R.; data curation, J.C.S., J.I.V.,
J.A.A. and I.M.R.; formal analysis, J.C.S., J.I.V., J.A.A. and I.M.R.; investigation, J.C.S. and J.I.V.;
methodology, J.C.S., J.I.V., J.A.A., A.T.C., M.O.U., S.E.B. and I.M.R.; funding acquisition, J.C.S.; project
administration, J.C.S. and J.I.V.; resources, J.C.S. and S.E.B.; supervision, J.C.S., J.I.V., M.O.U., S.E.B.
and I.M.R.; writing—original draft, J.C.S., J.I.V., J.A.A., A.T.C., M.O.U. and I.M.R.; writing—review &
editing, J.C.S., A.T.C., J.I.V., M.O.U. and I.M.R. All authors have read and agreed to the published
version of the manuscript.
Funding: This research received no external funding and the APC was funded by AVISA project OPP
1198373 funded by the Bill & Melinda Gates Foundation.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Data are available from the authors upon request.
Acknowledgments: We acknowledge the financial support from the CGIAR Research Program on
Grain Legumes and Dryland Cereals and the Bill and Melinda Gates foundation for the development
of breeding lines of common bean. We would also like to thank all donors who supported this
work through their contributions to the CGIAR Fund. MOU is grateful for the support of Deutsche
Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH and the Centre for International Migra-
tion and Development (CIM).
Conflicts of Interest: The authors have declared that no competing interest exist.
Plants 2022, 11, 1371 23 of 26
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