Huanglongbing or HLB caused by Candidatus Liberibacter asiaticus (CLas) was detected in Yucatán, Mexico, in July 2009. It is currently present in 352 municipalities in 23 commercial citrus-producing states (https://goo.su/qwSbCa - 2025, www.gob.mx -; SENASICA, 2022). During the initial phase of the epidemic (2009-2014), two scenarios predominated: 1) in the Pacific region, with high intensity, prevalence, and inoculum load in vector-plant associated with commercial orchards, predominantly Citrus aurantifolia, and 2) in the Yucatan Peninsula with moderate-low intensity, prevalence, and vector-plant inoculum load in Citrus latifolia backyards (Mora-Aguilera et al., 2014; Flores-Sánchez et al., 2015). However, during the regional and intraregional dispersal phase of the vector and the disease (2015-2018), differential epidemic scenarios in terms of incidence and endemicity occurred under specific regional conditions of production, management, climate, among others, e.g., Central Gulf with sweet citrus in commercial and backyard areas (C. sinensis, C. reticulata, among others) or Northeast with high-yield commercial orchards of C. sinensis and C. reticulata.

In Mexico, published epidemiological results and indicators on intra-plot or regional dispersion of the CLas-Diaphorina citri (Dc) complex (Gottwald et al., 2014; Bassanezi et al., 2005; 2013a; Esquivel-Chávez, 2011; Márquez et al., 2011), temporal epidemic rates (Mora-Aguilera et al., 2014; Bassanezi et al., 2005; 2013a; Robles-González et al., 2013; Esquivel-Chávez, 2011), regional dispersion scenarios (Flores-Sánchez et al., 2017; Mora- Aguilera et al., 2014; Robles-González et al., 2013), among others, were used to establish official strategies for sampling, monitoring, delimitation, and control of outbreaks through Regional Dc Control Areas (ARCOs) under symptomatic conditions (Flores-Sánchez et al., 2017; Mora-Aguilera et al., 2014; Bassanezi et al., 2013a; DGSV-SENASICA, 2010).

A novel scenario arose in Mexico following the detection of five CLas - positive plant samples of C. sinensis from asymptomatic trees in commercial orchards in S.J. Acateno, Puebla (SENASICA, 2012; 2015). No characteristic HLB symptoms at the Mexican conditions were observed, such as vein clearing, diffuse mottling, or generalized light yellowing (Esquivel-Chávez et al., 2012). Interestingly, this condition prevailed until December 2015 (2.5 years), longer than reported for an asymptomatic condition associated with the incubation period of CLas (Canale et al., 2020; Lopes et al., 2009).

In this context, the General Direction of Plant Health (DGSV), associated to the National Service for Plant health, Food security, and Agri-food Quality (SENASICA) in Mexico requested to the Laboratory for Phytosanitary Epidemiological Risk Analysis (CP- LANREF) to confine two Citrus sinensis trees positive for CLas and to develop a research approach to explain this asymptomatic condition.

This study analyzes one of five hypotheses investigated simultaneously to explain the asymptomatic condition induced by CLas in Citrus sinensis / C. aurantium in the Central Gulf of Mexico. The objective was to analyze the spatio-temporal concentration of CLas at the plant canopy - root level under commercial conditions to demonstrate the possible implication of a prolonged incubation period in the asymptomatic HLB condition, under the premise that the bacterial concentration should be incremental and gradually must exhibit chronic systemic infection throughout an infection-incubation period.

Confinement of asymptomatic plants. In December 2013, two commercial Valencia sweet orange trees (Citrus sinensis) positive for Candidatus Liberibacter asiaticus (CLas), confirmed by RT-PCR protocol, were caged for confinement to study the asymptomatic condition in sweet orange / sour orange, and avoid vectoring reinfection and spreading of the detected CLas isolate. Metal structures measuring 8 x 8 x 8 m (length x width x height) protected with double aphid netting were used, following specifications defined by the DGSV-CNRF (Figure 1A). Each structure was fitted with a padlocked door to restrict access to researchers and official personnel. Two HOBO u23 Pro v2 data loggers were installed to record temperature (°C) and relative humidity (RH) variables inside and outside the confinement structure for each tree (Figure 1B). Additionally, a Davis^® (Vantage Pro 2 Plus) weather station was installed to measure precipitation, evapotranspiration, solar radiation, and other complementary variables (Figure 1C). During the experiment, weeds were removed mechanically and no agrochemicals were applied. Irrigation was seasonal.

Figure 1

Selection and sampling of plant tissue. A total of 13 and 16 primary branches were marked on trees A2 and A3, respectively (Figure 2A). The branches were numbered clockwise in a west-east direction (Figure 2B). For each primary branch, secondary branches were selected and marked specifically for leaf sampling. Due to the timing of the experiment outside the main vegetative growth periods, secondary branches were selected directly based on the availability of plant tissue optimal for molecular analysis. Leaf samples were collected from the distal and proximal regions (Figure 2C). For distal samples, recent vegetative growth was identified and expanded leaflet was taken, and for proximal samples, a leaf was collected from the vegetative shoot of the previous growing cycle. All samples were labeled and kept cold in the field and laboratory. For qPCR analysis, the central leaf vein was used. Sampling was conducted monthly between May and December 2014. A total of 1 540 samples were analyzed.

Figure 2

Root sampling. For root sampling, from the truck base, a 55° triangle was marked on the soil surface, dividing five sections every 40 cm (Figure 3A-B). Subsequently, 20 cm deep sections were dug for the first stratum A (0 to 20 cm), while for the next three strata, 30 cm deep sections were dug (B = 20 - 50 cm, C = 50 - 80 cm, D = 80 - 110 cm) (Figure 3C-D). Root samples were collected for each section-stratum and classified according to their structure and function: support (S), conduction (C), and absorption (AB). In each stratum, the soil was sifted to separate the total root mass. The samples were stored in polypropylene bags and kept in a cooler. In the laboratory, each sample was washed with water to remove soil residues.

The root samples were separated into the previously defined classification (S, C, and AB) and disinfected with 1% sodium hypochlorite (NaClO) for 1 min. They were then rinsed twice with distilled water. From the conducting and supporting roots, the cortex (phloem) was removed and ground with liquid nitrogen in a mortar. The absorbing roots were ground using all the available tissue. For each section-stratum at least three subsamples were analyzed for a total of 111.

Molecular analysis, diagnosis, and quantification of CLas. Total DNA extraction from plant and root samples was performed using the 2% CTAB method with saline buffer from 100 mg of plant and root material. Quantification by qPCR was performed on StepOne™ (Applied Biosystems^®, Foster City, CA) using the standard curve method, using the HLBp oligos (5'- GCG TTA TCC CGT AGA AAA AGG TAG -3'), HLBas (5'- TCG AGC GCG TAT GCA ATA CG -3') and the Taqman probe (5'- AGA CGG GTG AGT AAC GCG -3')

(Li et al., 2006). The reaction consisted of a thermal cycling program of 95 °C for 3 min, 40 cycles of 95 °C for 5 s; 59 °C for 40 s and 59 °C for 35 s. Samples that reported 8 to 35 thermocycling cycles (Ct for Cycle threshold) exceeding the optimal fluorescence threshold were considered positive. Samples with Ct >35 were considered negative.

Figure 3

An external calibration curve was generated to quantify the number of genomic CLas copies in samples. The fragment of the 16S rDNA gene cloned into a plasmid (PGEM-T ® Promega®) was used, which was purified and quantified by UV spectrophotometry (Nanodrop 1000) with serial dilutions. These were amplified with three replicates per concentration, and a logarithmic regression was used to estimate the CLas concentration,

(y) = 41.95 - 3.37 (Log Staring Quantity) (r²=1, efficiency 97.9%), y = Ct, which calculates the number of copies of the 16S rDNA gene. To reduce the effect of variability and for the purpose of comparing DNA concentrations, a dilution to 20 ng µL⁻¹ was performed.

Parameterization and epidemiological analysis. qPCR results were integrated into a temporal epidemiological matrix. CLas epidemic curves were constructed using CLas copy quantification (Q) and the number of positive samples over time at monthly intervals. Three occurrence windows were parameterized per CLas epidemic curve: Yi as the initial sampling (t = 0), characterized by a period of pre-rainwater stress; Ymax as the period of highest inoculum load in the plant; and Yf as the final phase of the CLas epidemic curve. The parameterization was performed by tree, branch, and distal or proximal sampling section. Geospatial vector maps of Q and log(Q) interpolated by epidemic occurrence window (Yi, Ymax, and Yf) and by root structure (support, conduction, and absorption) were processed and analyzed in Golden Surfer^®v10. ANOVA and Tukey mean comparison (p = 0.05) analyses were conducted in SAS 9.4.

Detection and quantification of CLas in canopy. Seven monthly samplings were made between May and December 2014. A total of 1 540 samples were analyzed by qPCR, 784 from tree 2 (A2) and 756 from tree 3 (A3) (Table 1). A 41.9 % (646 samples) of the total samples analyzed were positive for CLas with a Ct threshold of 22.7 - 35. There were no statistical differences in positivity between trees (p = 0.48), with A3 obtaining 52.2% (337 positive, Ct = 22.7 - 34.9) and A2 47.8% (309 positive, Ct = 23.4 - 35). At the intra-branch sampling level, positivity in distal samples was slightly higher at 50.9% (329) compared to proximal samples, which had an incidence of 49.1% (317). The positivity of CLas in the distal branch area was not different in confined trees (A2 = 164; A3 = 165) (p = 0.97). In the proximal branch sector, A3 had a higher number of positive samples (173) than the distal (164) (p = 0.48). In A2, the incidence was lower but similar in trend (distal = 165; proximal = 144) (p = 0.42). The relative incidence of CLas per tree was higher in A3 with 49.5% compared to 39.4% in A2 (p = 0.68). By sampling sector, A2 had a positivity rate of 53.4 and 46.6% in the distal and proximal zones, respectively. The incidence in A3 was higher in the proximal zone with 51.3 vs. 48.7% in the distal zone (Table 1).

Table 1

Sampling date	Positive samplesx (Log[Q CLas])y		Number of positive samples per branch sector (Log[Q CLas])
			Distal		Proximal
	A2	A3	A2	A3	A2	A3
27 may.	3 (0.5 ± 0.8)	12 (1.0 ± 1.2)	9 (1.2 ± 1.3)	0 (0.4 ± 0.8)	3 (0.5 ± 0.8)	3 (0.8 ± 0.9)
27 jun.	71 (2.0 ± 1.3)	87 (2.6 ± 0.8)	45 (2.7 ± 0.8)	38 (2.3 ± 1.1)	33 (1.8 ± 1.4)	42 (2.6 ± 0.8)
25 jul.	65 (2.0 ± 1.4)	73 (2.8 ± 1.8)	33 (0.5 ± 0.8)	36 (2.2 ± 1.4)	29 (1.7 ± 1.4)	40 (2.8 ± 1.8)
31 ago.	36 (0.5 ± 0.8)	78 (2.4 ± 1.2)	35 (2.2 ± 1.1)	19 (1.4 ± 0.8)	17 (1.2 ± 0.9)	43 (2.6 ± 1.3)
02 oct.	75 (2.0 ± 1.3)	45 (1.5 ± 1.1)	17 (1.4 ± 1.2)	39 (2.3 ± 1.3)	36 (1.7 ± 1.3)	28 (1.7 ± 0.1)
06 nov.	54 (1.3 ± 0.7)	29 (1.3 ± 0.8)	19 (1.5 ± 0.7)	31 (1.4 ± 0.7)	23 (1.2 ± 0.7)	10 (1.1 ± 0.8)
10 dic.	5 (0.3 ± 0.6)	13 (0.9 ± 0.7)	6 (0.9 ± 0.8)	2 (0.3 ± 0.6)	3 (0.3 ± 0.6)	7 (0.9 ± 0.7)
Total	309 (1.3 ± 1.2)	337 (1.8 ± 1.4)	165 (1.5 ± 1.3)	164 (1.8 ± 1.3)	144 (1.2 ± 1.2)	173 (1.8 ± 1.4)
	(39.4 %)	(44.5 %)	(53.4 %)	(48.7 %)	(46.6 %)	(51.3 %)
A2+A3	646 (1.6 ± 1.3)		329 (1.6 ± 1.3)		317 (1.5 ± 1.3)
	(41.9 %)		50.9 %)		(49.1 %)

xTotal samples by date: 112 tree A2 and 108 tree A3. Total = 1540 samples per experimental period.

The estimated inoculum load based on the average number of CLas copies for 646 positive samples was 1.6 (±1.3) log, equivalent to 109 copies/reaction of 100 mL (6.3 to 68 870.7 range). The results showed that CLas was not statistically different (p = 0.33) between positive samples from the distal zone (1.6 log-CLas) and those from the proximal zone (1.5 log-CLas). Per tree, A3 showed a significantly (p < 0.00001) higher inoculum load of 1.8 (±1.3) log-CLas, but with no difference between the proximal and distal zones (1.8 log-CLas; p = 0.8). A2 had a lower inoculum load of 1.3 (±1.2) log-CLas compared to A3 (p < 0.00001). In samples from distal sector, a higher inoculum load of 1.5 (±1.3) log- CLas was found than in the proximal zone, with 1.2 (±1.2) log-CLas (p = 0.04) (Table 1).

Temporal CLas fluctuation in canopy. In general, the period of highest statistically significant incidence was between June and October, with 37 - 87 positive samples (p < 0.0001), accounting for 82% (530) of the total positive samples. In A2, except for August, with 36 samples (17.7%) detected positive, the range of positive samples was 54 - 75 between June and November, accounting for 94% of the total (p = 0.02). Positive samples in May (3) and December (5) were associated with periods of low detectability (p = 0.88). In contrast, A3 had the most inductive period between July and August (p = 0.0003) with a monthly average of 73 - 87 positive samples, accounting for 70.1% of the total. In this tree, October-December was a period of constant decline (p > 0.05) in the detection of positive samples, falling from 45 to 13, respectively. In A3, May and December were again the significantly least inductive periods with the lowest incidence of positive samples (p = 0.95) (Figure 4A). The fluctuation in CLas showed no contrasting differences between trees (p = 0.5) or collection periods (p > 0.72), ranging between 1.6 and 3.5 log-CLas for the months of May (A2) and July (A3). A2 had a CLas concentration of 1.6 - 2.8 log-CLas, with a higher concentration (2.1 - 2.8 log-CLas, p = 0.02) associated with the period of highest detectability of positive samples (June-October). In A3, the inoculum load was 1.8 - 3.5 log-CLas, higher than in A2 (p = 0.07), with a main peak in July equivalent to 3.5 log. The inoculum load showed a decreasing trend like positivity, reducing the CLas load from 2.7 to 1.8 between October and December (Figure 4B).

Figure 4

The greatest variability of CLas fluctuation in canopy was found at the branch (R) and proximal-distal sampling sector (Table 1 and Figure 4). In general, A2 showed homogeneity in the distribution of CLas per branch with marginal significant differences (p = 0.07), ranging from 1.5 (May, R7) to 2.8 (October, R13). Branches R4 and R13 occurred at the significantly higher inoculum load peak of 3.4 log (p < 0.02), diametrically opposite in the canopy. The rest of the branches showed a decreasing trend in CLas between August and December (p = 0.0001) (Figure 4C).

In A3, although there was high variability in the fluctuation of CLas in the canopy of C. sinensis, it was not significantly different at the branch level (p = 0.15). The branches varied in CLas concentration between 1.7 log (May, R4) and 5.1 log (July, R13). The inoculum load on A3 branches was significantly higher (p = 0.0001) between May and August, with 2.4 - 5.1 log-CLas, and lower and stable between September and December, with 1.7 - 2.9 log-CLas (Figure 4D).

Regarding temporal fluctuation in the period of highest positivity at the branch level, A2 showed greater homogeneity in the distribution of CLas (p = 0.07). Except for R8 in July (4.9 log-CLas) and R1 in October (0 log-CLas), the rest of the branches behaved homogeneously in the canopy of C. sinensis. The intensity of the CLas bacterial load varied by collection period, with the highest inoculum load detected in June (2.4 - 3.1 log), July (2.1 - 4.9 log), and October (2.2-3.6 log) (p = 0.0001) (Figure 4E).

In A3, the temporal fluctuation of CLas per branch was asymmetric, variable, and higher than in A2 (p = 0.002). In general, in A3, the bacterial load of CLas in July was significantly high, fluctuating, and concentrated in R9 (4.6 log) and the R13-R16 sector with 4.9 - 5.1 log (p = 0.0001). One month later, in August, it was higher in R1 (3.9 log-CLas), R7-R8 (3.4 - 3.6log-CLas), and R14 (5.3log-CLas) (p = 0.0001). The rest of the branches had a constant and homogeneous distribution of CLas, respectively (Figure 4F).

Canopy CLas spatial distribution and directionality at three epidemic stages. Analysis of the temporal fluctuation in positive samples of CLas bacterial load at three epidemic stages ( Yi , Ymax , and Yf ) identified an asynchronous process of Ymax and a heterogeneous distribution at canopy level between A2 and A3 (Figure 5). By epidemic moment, it was shown that in Yi (May) the distribution of CLas copies was concentrated in the middle and lower third of the canopy in A2 (0.08 - 47.2 copies) and A3 (6.8 - 38,842 copies).

The intra-canopy simulation showed southeast-northwest directionality-dispersion of CLas with the highest inoculum load (21,187 - 38,842 copies), while bacterial mobility in the rest of the canopy was lower and random (6.8 - 21,187 copies) (Figure 5A). In A2, the highest inoculum load was in the center of the middle third of the canopy with a northeast- southwest directionality (20 - 47.2 copies), and in the rest of the canopy it ranged from 0.08 - 19.9 copies of CLas (Figure 5B).

The Ymax of CLas for A2 and A3 occurred in October and July, respectively, after the onset of rainfall (382.2 mm accumulated). The inoculum load remained higher in A3 (216 - 216,767 copies) than in A2 (9.2 - 4,239 copies) (Figure 5C-D). During this epidemic, the highest concentration and distribution of CLas was mainly located in the upper-middle third of the canopy of A3 (65,889 - 216,767 copies) and A2 (1,416 - 4,239 copies). In A3, CLas mobility was multidirectional with a predominance of east-west inoculum load (Figure 5C). In A2, the effect on the directionality of the highest CLas concentration was mainly south- east (Figure 5D).

Figure 5

The end of the inoculum load cycle ( Yf ) occurred in December in A2 (0.05 - 15.3 copies) and A3 (0.3 - 51.1 copies) (Figure 5F). With a lower bacterial load, Yf showed agreement in the distribution of CLas with respect to the sectors with the highest inoculum in Yi . In A3, the lower and upper thirds showed multidirectional distribution in the canopy with a south-northeast trend in the lower third (15.5 - 51.1 copies) and an east-west trend in the upper third (19.6 - 49.3 copies) (Figure 5E). In contrast, in A2, the highest concentration of CLas (5.9 - 15.3 copies) was associated with the middle third, directly linked to inoculum load in Yi , while the directionality in the sector with the highest concentration tended to be east-west. In the rest of the canopy, the inoculum load (0.05 - 5.8 copies) showed a random trend with multidirectional distribution in the canopy (Figure 5E).

Spatial CLas detection and quantification in the root structure. A total of 111 root samples divided into support (30), conduction (42), and absorption (39) were analyzed by qPCR (Table 2). CLas positivity in root samples was 38.7% with thresholds of Ct = 32.7 - 35, while on support, conduction, and absorption was 47.6, 15.4, and 38.7%, respectively.

Table 2

Sampling date	Positive samplesx (Log[Q CLas])y		Number of positive samples per branch sector (Log[Q CLas])
			Distal		Proximal
	A2	A3	A2	A3	A2	A3
27 may.	3 (0.5 ± 0.8)	12 (1.0 ± 1.2)	9 (1.2 ± 1.3)	0 (0.4 ± 0.8)	3 (0.5 ± 0.8)	3 (0.8 ± 0.9)
27 jun.	71 (2.0 ± 1.3)	87 (2.6 ± 0.8)	45 (2.7 ± 0.8)	38 (2.3 ± 1.1)	33 (1.8 ± 1.4)	42 (2.6 ± 0.8)
25 jul.	65 (2.0 ± 1.4)	73 (2.8 ± 1.8)	33 (0.5 ± 0.8)	36 (2.2 ± 1.4)	29 (1.7 ± 1.4)	40 (2.8 ± 1.8)
31 ago.	36 (0.5 ± 0.8)	78 (2.4 ± 1.2)	35 (2.2 ± 1.1)	19 (1.4 ± 0.8)	17 (1.2 ± 0.9)	43 (2.6 ± 1.3)
02 oct.	75 (2.0 ± 1.3)	45 (1.5 ± 1.1)	17 (1.4 ± 1.2)	39 (2.3 ± 1.3)	36 (1.7 ± 1.3)	28 (1.7 ± 0.1)
06 nov.	54 (1.3 ± 0.7)	29 (1.3 ± 0.8)	19 (1.5 ± 0.7)	31 (1.4 ± 0.7)	23 (1.2 ± 0.7)	10 (1.1 ± 0.8)
10 dic.	5 (0.3 ± 0.6)	13 (0.9 ± 0.7)	6 (0.9 ± 0.8)	2 (0.3 ± 0.6)	3 (0.3 ± 0.6)	7 (0.9 ± 0.7)
Total	309 (1.3 ± 1.2)	337 (1.8 ± 1.4)	165 (1.5 ± 1.3)	164 (1.8 ± 1.3)	144 (1.2 ± 1.2)	173 (1.8 ± 1.4)
	(39.4 %)	(44.5 %)	(53.4 %)	(48.7 %)	(46.6 %)	(51.3 %)
A2+A3	646 (1.6 ± 1.3)		329 (1.6 ± 1.3)		317 (1.5 ± 1.3)
	(41.9 %)		50.9 %)		(49.1 %)

v Incidence of CLas positive samples at different distances from the trunk relative to the total samples analyzed (n = 111). ^wIncidence of CLas positive samples from different distances from the trunk relative to the subtotal of positive samples (n = 43). ^xIncidence of CLas positive samples by depth strata and root type. ^yIncidence of CLas positive samples by depth strata and root type relative to the total samples analyzed (n = 111). ^zIncidence of CLas positive samples by depth strata and root type relative to the subtotal of positive samples (n = 43). Color represents positivity, being green negative and red de highest detection.

Regarding relative positivity by depth stratum, support and absorption roots at 110 cm had a 100% incidence (9/9). In support and conduction roots, 44.4 - 83.7% relative incidence was found at 20 and 40 cm depth, which corresponds to 4.5 - 7.2% of the total samples analyzed (n = 111) and 11.6 - 18.6% of positive samples (n = 43) (Table 2). The highest incidence in samples collected in relation to distance from the trunk was 58.1%, mainly associated with the section between 80 and 120 cm. In general, at 80 - 220 cm, a decreasing positivity gradient was found from 55.6 to 26.7% and an increase to 77.8% at 280 cm from the trunk, specifically associated with a depth of 20 cm. In relative terms, the highest incidence was recorded at 80 and 120 cm from the trunk, with 55.6 and 47.6%, respectively (Table 2). Regarding the CLas concentration and distribution by root type, higher concentrations were found in support and conduction roots, 38.3 (±47.5) and 43.4 (±24.4) copies, respectively, which were statistically different (p < 0.0001) from absorption roots (9.5 ± 7.2 CLas copies) (Figure 6A).

The bacterial load of CLas between 80-120 cm from the trunk was stable (22.6 - 33.7 copies), while 160 - 280 cm showed a decreasing gradient from 42.9 to 10.8 copies (p < 0.0001) (Figure 6B). In samples analyzed by depth, the gradient was significantly greater (p = 0.04) from 20 to 110 cm with 45.2 - 82.8 copies (Figure 6C). In general, conduction roots had a higher incidence and CLas concentration with 1.3 - 84.3 copies (Table 2), mainly between 20-40 cm from the trunk (p = 0.01), and 80 - 160 cm deep (p > 0.05) (Figure 6D). In absorption roots, CLas was associated with 110 cm from the trunk in combination with 80 - 120 cm depth with 39.8 - 64.1 copies (p > 0.05). In support roots, they had variable behavior with 3.2 - 144.5 copies, where a sample collected 110 cm from trunk and 80 cm deep had the statistically highest concentration with 144.5 CLas copies (p

Figure 6

Spatial geostatistical simulation of CLas. The CLas concentration in the root system showed various distribution and mobility scenarios (Figure 3 and 7). In general, two sections of greater intensity and inoculum load concentration (80 - 144 copies) were observed, associated with the middle canopy-drip zone (140 - 220 cm) and medium depth strata (40 - 80 cm) (Figure 7A). The geostatistical interpolation model showed the highest intensity gradient (144 copies) between sections of conducting roots in the middle drip zone of the canopy. A second high-intensity gradient (>80 CLas copies) was in the absorption root section (Figure 7A). A second high-intensity gradient (>80 CLas copies) was in the absorption root section (Figure 7A).

The simulation of CLas mobility using the Grid Vector Map geostatistical analysis showed that the two sections of bacterial concentration were associated with mobility patterns differentiated by the type of colonized root. The first, between 140 - 160 cm from the main axis and 20 - 65 cm deep, was associated with incidence in conducting roots (d = 6.38 mm). In this section, the mobility pattern with the highest inoculum load (size and red color of the vector) was toward a trunk distance of 160 - 200 cm and a soil depth of 40 - 60 cm. The second was between 180 - 240 cm and 80 - 110 cm, respectively, associated with support roots (d = 18 mm) and absorption roots (d = 1.5 mm) with an upward mobility pattern from soil depth strata at 110 cm to 20 - 40 cm (Figure 7B).

The incidence in supporting roots showed a decreasing gradient of CLas (30 - 118 copies) at depths greater than 40 cm towards the 220 cm zone relative to the trunk of C. sinensis. The highest CLas load and intensity (90 - 114 copies) was associated with 70 - 110 cm depth and at 200 - 250 cm distance from the trunk (Figure 7C). The CLas load in conducting roots showed variable and random mobility patterns on the three-dimensional soil core analyzed, suggesting greater mobility and less restrictiveness due to the abundance and wide distribution in the root structure.

Figure 7

The bacterium load gradient (30 - 71 copies) for conducting roots was mainly associated with 20 - 60 cm depth and 80 - 160 cm distance of the trunk, with a lower intensity and inoculum load (20 - 25 copies) between 80 - 100 and 200 - 240 cm distance (Figure 7D). In absorption roots, the highest inoculum load and mobility capacity was associated with soil depth strata between 80 - 110 and 80 - 280 cm from the trunk, although absorption roots are likely to be predominant on the surface and at the periphery of the root system. The highest inoculum load (31-70 copies) was concentrated at 160 - 240 cm distance. The mobility pattern was upward, with a predominance from 110 cm to the 60 cm depth stratum. With a lower bacterial load (5 - 18 copies), a peripheral dispersion pattern was evident, converging at medium depth and distance from the trunk (Figure 7E).

The hypothesis of asymptomatic HLB associated with a prolonged incubation period (IP) in response to infection by Candidatus Liberibacter asiaticus (CLas) on 30-years-old Valencia orange trees (C. sinensis / C. aurantium), from a commercial orchard in the Central Gulf of Mexico, was analyzed by measuring the concentration and spatiotemporal distribution of the bacteria in the canopy and three root types under confinement conditions. During seven monthly evaluations, a total of 1540 samples were analyzed. No visual symptoms were observed despite detection of 39.4 - 49.5% qPCR-positive samples well distributed in canopy, and in proximal (50.9%) and distal (49.1%) branches. The lack of symptoms for at least 7 months contrasts with the incubation of CLas for two to five months in 1.5-year-old C. sinensis / C. limonia plants after infection with infectious Diaphorina citri (Canale et al., 2020). However, the incubation associated with a presymptomatic condition of HLB is variable in citrus and has been reported to range from months to years, depending on vector population density, inoculum load, plant age, graft / rootstock, detection in commercial orchards or backyards, among other epidemiological factors (Gottwald et al., 2010). However, several of these reports have been empirical estimates or without experimental support.

In this study, the incubation period refers to the time between successful infection via D. citri and the expression of the first visible HLB symptoms. In this case, due to the novel experiment developed for a natural asymptomatic condition in the field, the infection could not be controlled and therefore time-0 was unknown. However, the premise was that the bacteria concentration should be incremental and gradually exhibit a chronic systemic canopy-root colonization if the asymptomatic condition was transient and explained by a prolonged incubation period. The objective was not to estimate the incubation period, but to analyze this event as the cause of the symptom’s expression delay.

Initial characteristic visible symptoms on foliage, following infection by CLas, also contrast depending on the citrus species, climatic conditions, inoculum source load, and other factors (Canale et al., 2020; Esquivel-Chávez et al., 2012; Lopes et al., 2009). In chronic asymptomatic HLB, symptoms are not a reference parameter for determining IP, especially when high bacterial concentrations (1 x 10⁹ copies) and low thresholds for CLas acquisition by D. citri (2694 copies) have been demonstrated under natural spreading in commercial orchards (G. Mora, unpublished). Complementarily, IP is part of the pathogenesis process sensu Vanderplank, conceived for local infections with visible symptoms / signs (e.g., fungy), not for systemic infections such as those caused by CLas. Consequently, the latency period (LP) in CLas, classically understood as the time required for a pathogen to produce new inoculum from the first visible symptom, has been indirectly inferred from the D. citri ability to acquire CLas and infect new plants, resulting in periods up to 1 month shorter than IP (Canale et al., 2020). This implies that LP is not successive and synchronous with IP sensu Vanderplank and that understanding pathogenesis in a systemic infection requires another histological-mechanistic framework (Esquivel-Chávez, 2016; Esquivel-Chávez et al., 2012). In this research, IP was inferred through inoculum dynamics, i.e., multiplication and distribution in the host.

Although these methodological and biological restrictions highlight the complexity of explaining asymptomatic HLB using PI, a critical aspect is to determine whether the space- time dynamics of bacterial concentration can determine a chronic, i.e., permanent, asymptomatic condition or a transient condition leading to the eventual expression of visible symptoms. For example, the intensity in HLB symptomatic expression, and consequently in concentration, has been associated with environmental variables (temperature and RH) and bacterial migration to the root (Bassanezi et al. 2013b).

The concentration of CLas in warm regions of São Paulo, Brazil, was related to high temperature and RH (Lopes et al., 2009). In S.J. Acateno, the highest incidence of samples (37 - 87 positive) and CLas concentration (2.1 - 3.5 log) was associated with significant temperature variation of 19.1 - 27.6 °C (x̅ = 24.4 ± 3.0) and moderate to high humidity 74.4-98.7 RH (x̅ = 89.2 ± 10.2). In contrast, the CLas decremental phase was mainly associated with lower temperature range of 12.1 - 23.6 °C (x̅ = 19.1 ± 2.6) than with humidity (79.7 - 98.9 RH, x̅ = 92.0 ± 7.5).

In general, at canopy level, a temporal effect of CLas was observed (p < 0.0001), with summer samples having a significantly higher concentration (2.1 - 3.5 log-CLas) compared to spring and fall-winter (≤ 1.8 log-CLas). Note, however, that temperatures in S.J. Acateno are not extreme and the summer effect may be reversed at other latitudes. Other studies have reported differences between seasons, validating the seasonal bacterium fluctuation in symptomatic commercial orchards (Sauer et al., 2015). These results indicate that temperature is involved in CLas concentration variation but does not explain an asymptomatic effect by IP.

The premise of attributing asymptomatic status to prolonged IP, inferred by incremental inoculum load over time and canopy-root space, was also ruled out in this investigation. The concentration of CLas fluctuated in the range of 1.5 - 3.5 log copies / reaction 100 mL during the evaluation period (range = 6.3 - 68870.7 copies). CLas studies using controlled infection in young C. sinensis Pera plants suggest stability in visual detectability at approximately 5 log cells g⁻¹ 40 days after inoculation and a minimum threshold of 2.6 log (2.6 - 3.6 log CLas) for symptom expression in new shoots, 24 days after inoculation (Cui et al., 2022; Alves et al., 2021). Although in this study the results exceeded that threshold for at least two continuous monthly periods and up to four discontinuous periods, the asymptomatic condition was maintained.

At the branch-sector or canopy-sector level, the concentration of CLas was statistically different (p = 0.07). Branches showed heterogeneous inoculum loads between sectors, reaching up to 2.4 - 5.1 log-CLas. This effect has been observed in Brazil in commercial fields on adult trees of different C. sinensis cultivars with contrasting variations in Ct's in canopy quadrants (Sauer et al., 2015), evidencing high intra-plant variability and the need for additional studies on the processes of infection and colonization of CLas in plants (Raiol-Junior et al., 2020), especially in commercial orchard conditions.

The epidemic inoculum load parameterization ( Yi , Ymax , and Yf ) of CLas concentration curves validated the temporal fluctuation of the bacteria, which was neither incremental nor gradual over the canopy, reinforcing the null or low effect of IP in the HLB-asymptomatic condition. The highest positivity and concentration of CLas (Ymax) was found to be associated with the upper-middle sector of the canopy. The inoculum in the initial phase ( Yi ) and final epidemic phase ( Yf ) showed mobility towards the lower and lower-upper sectors, respectively. The effect of higher concentration in the middle-upper sector may be associated with the emission of shoots and tissue renewal (Raiol-Junior et al., 2020), which can be asymptomatic reservoirs of the bacteria and a source of acquisition and dispersal by the insect vector. Lee and coworkers (2015) simulated that in approximately one year, up to 12 000 individuals of D. citri / tree can be infectious (Lee et al., 2015).

At the genetic recognition level, the temporal and spatial expression of CLas effectors (e.g., CLIBASIA_03875, CLIBASIA_04800, CLIBASIA_05640, etc.) should also be

considered in early colonization, suppression of tolerance genes, and long-term survival, potentially involved in an asymptomatic or presymptomatic condition (Shi et al., 2019).

The asymptomatic condition associated with the movement of CLas towards the root is a biologically and epidemiologically relevant factor (Bassanezi et al. 2013b). Recent studies have documented the movement of CLas towards newly developed root and leaf tissues (Raiol-Junior et al., 2020). However, the root factor has been little studied directly in the field due to the prioritization of visual symptom diagnosis, PCR genomic methods, and the difficulty of root sampling due to its complex structure in Citrus spp. (Alves et al., 2021).

The detection of CLas in young plants roots can precede an undetectable and asymptomatic condition in foliage, and it can be up to three times more efficient than in leaves (Xie et al., 2021; Braswell et al., 2020; Raiol-Junior et al., 2020; Graham et al., 2014; Johnson et al., 2013). This was not the case in these results, supporting the idea that PI is not mechanistically involved. Overall, CLas had a widespread distribution in canopy and roots. The probability of detecting CLas in roots vs. tissue was not statistically different (38.7 vs. 41.9%, p < 0.05), but there were differences in inoculum load (p = 0.0001) with 9 - 43.4 vs. 6.3 - 68 870.7 copies in asymptomatic leaf tissue. There was also an effect of root type with 47.6, 15.4, and 38.7% of positive samples out of a total of 111, and 38.3, 43.4, and 9.5 average copies of CLas for support, conduction, and absorption roots, respectively (p < 0.0001). In contrast, Raiol-Junior et al. (2020), who worked under controlled environment conditions with Pera 60-cm-plants C. sinensis / C. volkameriana, found that young roots (absorption) had the highest bacterial load after root pruning.

It is important to point out that results of CLas dynamics are inherent to the initial inoculum-plant interaction without the influence of external inoculum sources, since reinfection events with D. citri, and eventual transmission of other CLas variants associated with greater aggressiveness (G. Mora, unpublished), were excluded by tree confining.

Other factors, such as the vector density effect, CLas variant, and graft / rootstock combination could not be ignored in studies of an asymptomatic condition. For example, in S.J. Acateno, Puebla, low populations of D. citri were recorded, with an average of 2.9 - 3.2 insects per yellow sticky trap during periods with the highest detection of positive canopy samples, significantly lower than in high-density populations in regions such as Tecomán, Colima, with 18.3-56.1, and Martínez de la Torre, Veracruz, with 5.4-7.9 D. citri per trap on average (SIMDIA, 2022). Similarly, under chronic - endemic conditions since 2010 in Mexico (Mora-Aguilera et al., 2014), the bacterial load has been notably high, exceeding 2.5 x 10⁷ CLas copies in C. aurantifolia / Macrophylla or Volkameriana in Colima or Michoacán (De la Rosa, 2016), compared to a range of 6.3 - 68 870.7 copies in this study.

Another consideration in the presymptomatic condition is the structural modification of the phloem in infected tissue, e.g., starch accumulation, cell wall thickening, expression of callose genes and proteins (e.g., CALLOSE SYNTHASE7 and PHLOEM PROTEIN2), resulting in differential plugging of vascular bundles depending on the type of Citrus spp.

/ rootstock rather than inoculum load or CLas intra-plant movement (Cavichioli et al., 2022; Xie et al., 2021; Achor et al., 2020). This behavior was reported in palisade and spongy parenchyma of C. aurantifolia symptomatic tissue compared to that of C. sinensis. In particular, the phloem area and width in asymptomatic tissue of infected plants was 1.9 times smaller in sweet orange (Esquivel-Chávez et al., 2012).

These results provide evidence that PI does not explain the asymptomatic condition of CLas in the productive environment of S.J. Acateno. Additionally, it reinforces the importance of designing strategies to establish efficient surveillance-monitoring systems for the detection of CLas in chronic or transient asymptomatic conditions. Likewise, they generate new management perspectives based on the genetic understanding of plant- pathogen interaction and epidemic implications. This is the first study to mechanistically analyze IP at the canopy - root level, in initial detections of asymptomatic HLB in Mexico in adult productive trees of Valencia C. sinensis / C. aurantium under field condition.

This work is part of a broad investigation conducted by the CP-LANREF group, focused on analyzing for the first time the asymptomatic condition of HLB in sweet orange / N. agrio. Specifically, this work demonstrated that a prolonged incubation period does not determine the asymptomatic condition based on the spatiotemporal variation of Candidatus Liberibacter asiaticus concentration at the canopy-root plant level.

The asymptomatic positive condition of Clas was maintained through seven monthly evaluations of aerial tissue and a comprehensive root evaluation. The concentration was fluctuating, not incremental, with statistical differences according to seasonality or root type. The relatively homogeneous distribution of CLas in the tree canopy and the presence of this bacterium in support, conduction, and absorption roots suggests a chronic medium- to long-term infection, so the absence of visible symptoms may have other physiological, histological, or genetic causes inherent to the pathogen. Additionally, the eventual occurrence of symptoms in asymptomatic trees should consider reinfection by variants and changes in the population structure of the pathogen. These results contribute to strengthening surveillance-monitoring strategies by seasonality, canopy-branch sectors, and tissue type with a higher probability of detection even in asymptomatic conditions and generate new insights for Clas management.