extfieldsofstudy: Medicine Biology

text:
Co-Occurrence of Defoliating and Non-Defoliating Pathotypes of Verticillium Dahliae in Field-Grown Cotton Plants in New South Wales, Australia

Verticillium wilt (VW) is a major constraint to cotton production in Australia and worldwide. The disease is caused by a soilborne fungus, Verticillium dahliae, a highly virulent pathogen on cotton. Commonly, V. dahliae is designated into two pathotypes: defoliating (D) and non-defoliating (ND), based on induced symptoms. In the previous two survey seasons between 2017 and 2019, stems with suspected VW were sampled for the confirmation of presence and distribution of D and ND pathotypes across New South Wales (NSW), Australia. A total of 151 and 84 VW-suspected stems sampled from the 2017/18 and 2018/19 seasons, respectively, were subjected to pathogen isolation. Of these, 94 and 57 stems were positive for V. dahliae; and 18 and 20 stems sampled respectively from the two seasons yielded the D pathotype isolates. Two stems from the 2017/18 season and one stem from 2018/19 season yielded both D and ND pathotype isolates. We also successfully demonstrated the co-infection of both pathotypes in pot trials, which was driven predominantly by either of the pathotypes, and appeared independent on vegetative growth, fecundity and spore germination traits. Our study is the first report of the natural co-occurrence of both D and ND pathotypes in same field-grown cotton plants in NSW, to which a challenge to the disease management will be discussed.

Introduction
Cotton (Gossypium spp.) is an economically important fibre crop contributing to approximately 40% of the world's natural fibre [1]. Cultivated cotton can be found in a range of ecological niches from arid to semi-arid areas of the tropical and subtropical zones and is mainly derived from Upland cotton (G. hirsutum L.) and Pima cotton (G. barbadense L.) due to superior fibre quality and quantity traits [2]. In Australia, Upland cotton is a major agricultural crop and mainly grown in regional areas of New South Wales (NSW) and Queensland and produced predominantly under irrigated conditions, but smaller areas of dryland production do occur in some seasons [3]. In the 2017/18 cotton growing season, the industry employed up to 10,000 people across 152 communities and contributed significantly to the economic growth and wealth of these regions. The majority of Australian cotton is exported, which generates an average value of around AUD 1.9 billion annually [3].
In Australia, cotton is prone to infection with an array of pathogens, including black root rot pathogen Thielaviopsis basicola (Berk. and Br.) Ferraris [4], leaf spot pathogen Alternaria alternata (Fr.) Keissl. [5], Fusarium wilt pathogen Fusarium oxysporum f. sp. vasinfectum Snyder and Hansen, [6,7], and Verticillium wilt (VW) pathogen Verticillium dahliae Kleb. [8]. Of these, VW of cotton is of a major constraint to the sustainability of the cotton industry due to the lack of complete resistant resources Plants 2020, 9, 750 3 of 11

Isolation and Pathotype
A total of 151 and 84 VW-suspected stems selected from samples collected during the 2017/18 and 2018/19 seasons, respectively, were subjected to recovery of V. dahliae (Table 1). Of these, 94 and 57 stems from the two seasons, respectively, yielded putative V. dahliae cultures on an isolating medium (potato dextrose agar amended with 100 ppm of streptomycin, sPDA). Subsequently, a total of 195 and 120 putative V. dahliae isolates from the 2017/18 and 2018/19 seasons, respectively, were subcultured and purified for pathotyping using duplex PCR developed by Mercado-Blanco et al. [19]. Of these putative V. dahliae isolates, 34 and 41 isolates accounting for approximately 17% and 34% accordingly were designated to the D pathotype (Table 1), thus confirming the identification of the pathogen. Of the V. dahliae-positive stems, 18 and 76 stems were determined to yield the D and ND pathotypes, respectively, in the 2017/18 season, and two stems yielded both pathotypes. In the 2018/19 season, 20 out of the 57 V. dahliae-positive stems yielded the D pathotype, and one yielded both the D and ND pathotypes. Therefore, this confirms the first report of the natural co-occurrence of both the D and ND pathotypes of V. dahliae in cotton in NSW, Australia.

Trial 1
Control plants remained healthy (disease incidence and severity = 0) during the time course of the experiment; hence, unless otherwise stated, the control data were excluded in our ANOVA analyses and graphing.
Plants inoculated with the tested V. dahliae isolates showed the first VW symptoms, including chlorosis and wilting on cotyledons seven days after inoculation. Disease symptoms progressed upwards, and defoliation was observed on plants inoculated with isolates 19V76 and L42, and those with co-inoculation (Table 2). We recorded various degrees of disease severity from 0 = no symptoms to 5 = dead plants four weeks after inoculation. The mean disease severity varied from 3 to 4.2 and was not significantly different among the V. dahliae-inoculated treatments, irrespective of either singleor co-inoculation ( Figure 1).  4 D-and ND-positive plants were determined based on the recovery of both D and ND isolates from an inoculated plant. 5 All plants including the control were subjected to V. dahliae re-isolation individually. Numbers in parentheses indicate the frequency recovery percentage of V. dahliae from diseased plants. 6 The recovered V. dahliae isolates were subjected to pathotyping by duplex PCR [19].

Trial 2
No VW disease symptoms were observed on the control plants. The first VW symptoms were noted on cotyledons of the V. dahliae-inoculated plants at nine days after inoculation. Defoliation was observed on plants inoculated with isolates 19V76 and L42 and their co-inoculation at four weeks after inoculation (Table 2). Disease incidence was lowest (38%) in the 19V77 treatment and highest (100%) in the L41 treatment. Means of disease severity were significantly different (p = 0.05) between the 19V77 and L41 treatments, but these were not different to the others ( Figure 1).
Of the diseased plants, the V. dahliae recovery frequencies of the inoculated isolates ranged from 61 to 100% ( Table 2). As in trial 1, we did not recover any V. dahliae from asymptomatic inoculated plants and the control plants. Diseased plants from treatments singly inoculated with either D or ND yielded a single pathotype upon isolation and pathotyping using duplex PCR. Both D and ND pathotypes were recovered only from the co-inoculated plants. A single plant from the co-inoculated Of the diseased plants, the V. dahliae recovery frequencies of the inoculated isolates were from 71 to 100% (Table 2). We failed to recover any V. dahliae from asymptomatic inoculated plants and the control plants. A single pathotype, either D or ND, was recovered from the single inoculated plants. Both D and ND pathotypes were recovered only from the co-inoculated plants. Two plants from each of the co-inoculated treatments were co-infected with both pathotypes. The co-infections were driven by either of the pathotypes, indicated by the predominant recovery of one to the other ( Table 2).

Trial 2
No VW disease symptoms were observed on the control plants. The first VW symptoms were noted on cotyledons of the V. dahliae-inoculated plants at nine days after inoculation. Defoliation was observed on plants inoculated with isolates 19V76 and L42 and their co-inoculation at four weeks after inoculation ( Table 2). Disease incidence was lowest (38%) in the 19V77 treatment and highest (100%) in the L41 treatment. Means of disease severity were significantly different (p = 0.05) between the 19V77 and L41 treatments, but these were not different to the others ( Figure 1).
Of the diseased plants, the V. dahliae recovery frequencies of the inoculated isolates ranged from 61 to 100% (Table 2). As in trial 1, we did not recover any V. dahliae from asymptomatic inoculated plants and the control plants. Diseased plants from treatments singly inoculated with either D or ND yielded a single pathotype upon isolation and pathotyping using duplex PCR. Both D and ND pathotypes were recovered only from the co-inoculated plants. A single plant from the co-inoculated L41 + L42 treatment yielded both D and ND pathotypes. The co-infection was driven by the ND pathotype; six out of seven recovered isolates were designated to the ND pathotype (Table S1).

Growth Competition
At 25 • C, the D isolates 19V76 and L42 grew respectively faster than the ND isolates 19V77 and L41 after seven days incubation in darkness, regardless of being grown in single or dual cultures ( Figure 2). Colonies of 19V76 single and 19V76 dual (against 19V77) reached approximately 30 mm in diameter and were significantly higher than those of 19V77 single and 19V77 dual (against 19V76), which were around 25 mm in diameter. Similarly, growth of L42 single and L42 dual (against L41) were about 10% faster than those of L41 single and L41 dual (against L42).
Plants 2020, 9, x FOR PEER REVIEW 6 of 12 Figure 2. Colony diameter (mm) of the tested V. dahliae isolates recorded after seven days growing in darkness at 25 °C. Growth competition of 19V76 vice versa 19V77, and L41 vice versa L42 were assessed in dual culture assays (labelled "dual"). Data from the two assays were pooled due to the insignificant difference found between the two repeated assays. Bars represent standard errors of means (n = 12). Asterisks indicate significant differences among treatments (p = 0.05 for * and p = 0.01 for **).

Fecundity and Germination
The in vitro fecundity (spores/mL) and germination rate (%) of the four tested V. dahliae isolates were isolate-dependent, but independent from pathotypes ( Figure 3). Fecundity of the D isolate 19V76 was around 1.1 × 10 7 and significantly higher than that of the ND isolate 19V77 (5.3 × 10 6 ). On the other hand, the ND isolate L41 produced a significantly higher number of spores compared with the D isolate L42 under the same conditions. Colony diameter (mm) of the tested V. dahliae isolates recorded after seven days growing in darkness at 25 • C. Growth competition of 19V76 vice versa 19V77, and L41 vice versa L42 were assessed in dual culture assays (labelled "dual"). Data from the two assays were pooled due to the insignificant difference found between the two repeated assays. Bars represent standard errors of means (n = 12). Asterisks indicate significant differences among treatments (p = 0.05 for * and p = 0.01 for **).
There were no negative effects on growth of the tested V. dahliae isolates recorded in the dual culture assays (Figure 2). Growth of 19V76 in single culture (29.9 mm diameter) was comparable to that of the dual culture against 19V77 (29.4 mm diameter). A similar pattern was recorded on the growth of 19V77, L41 and L42 in single and dual cultures. This indicates growth competition between the D and ND isolates was not observed in our assays.

Fecundity and Germination
The in vitro fecundity (spores/mL) and germination rate (%) of the four tested V. dahliae isolates were isolate-dependent, but independent from pathotypes ( Figure 3). Fecundity of the D isolate 19V76 was around 1.1 × 10 7 and significantly higher than that of the ND isolate 19V77 (5.3 × 10 6 ). On the other hand, the ND isolate L41 produced a significantly higher number of spores compared with the D isolate L42 under the same conditions. Colony diameter (mm) of the tested V. dahliae isolates recorded after seven days growing in darkness at 25 °C. Growth competition of 19V76 vice versa 19V77, and L41 vice versa L42 were assessed in dual culture assays (labelled "dual"). Data from the two assays were pooled due to the insignificant difference found between the two repeated assays. Bars represent standard errors of means (n = 12). Asterisks indicate significant differences among treatments (p = 0.05 for * and p = 0.01 for **).

Fecundity and Germination
The in vitro fecundity (spores/mL) and germination rate (%) of the four tested V. dahliae isolates were isolate-dependent, but independent from pathotypes ( Figure 3). Fecundity of the D isolate 19V76 was around 1.1 × 10 7 and significantly higher than that of the ND isolate 19V77 (5.3 × 10 6 ). On the other hand, the ND isolate L41 produced a significantly higher number of spores compared with the D isolate L42 under the same conditions. Figure 3. Fecundity (spores/mL) and germination rate (%) for the four tested V. dahliae isolates on potato dextrose agar amended with 100 ppm of streptomycin (sPDA) at 25 °C in darkness. Data from the two assays were pooled due to the insignificant difference found between the two repeated assays. Bars represent standard errors of means (n = 6 and 18 for fecundity and germination assessments, respectively). Asterisks indicate significant differences among treatments (p = 0.05 for * and p = 0.01 for **). . Fecundity (spores/mL) and germination rate (%) for the four tested V. dahliae isolates on potato dextrose agar amended with 100 ppm of streptomycin (sPDA) at 25 • C in darkness. Data from the two assays were pooled due to the insignificant difference found between the two repeated assays. Bars represent standard errors of means (n = 6 and 18 for fecundity and germination assessments, respectively). Asterisks indicate significant differences among treatments (p = 0.05 for * and p = 0.01 for **).
There was no significant difference in the spore germination rates of the 19V76 and 19V77 isolates on sPDA, which were recorded around 60%. Conversely, the germination rate of L42 was recorded at 32.2%, which was about half of L41 (60.6%) (Figure 3).

Discussion
Verticillium wilt of cotton was first reported in NSW in 1959 [27]. Over 35 years of continuous disease survey since 1984 [8], we for the first time documented the natural co-occurrence of both D and ND pathotypes of V. dahliae in cotton in NSW, Australia, sampled from two survey seasons between 2017 and 2019. Additionally, we were able to demonstrate the co-infection in two independently repeated pot trials using a root dip method. Therefore, we propose that co-infections of multiple V. dahliae isolates in a cotton plant are probably not a rare event under natural field conditions. Previously, Mercado-Blanco et al. [19] reported the co-infection of D and ND pathotypes occurred naturally in olive trees. Schnathorst and Mathre [26] artificially co-inoculated cotton with the virulent D isolate T-1 and mildly virulent ND isolate SS-4; however, there was no evidence of co-infection recorded in their study.
Our pot trials indicated that the D and ND isolates recovered from the same stem were relatively comparable in virulence on cotton, and the VW disease expressions were not significantly different between the single-and co-inoculated plants. Irrespective of treatments, initial VW symptoms appeared first on cotyledons between 7 and 9 days after inoculation and dead plants were observed across the treatments four weeks after inoculation. Similarly, Wheeler and Johnson [22] reported VW disease in potato plants co-inoculated with three isolates from potato, mint and tomato was highly comparable to plants who received a single inoculation with the potato isolate. Interestingly, Schnathorst and Mathre [26] found cross-protection on cotton when co-inoculated with virulent D and mildly virulent ND isolates. Cross-protection was more often associated with co-inoculations of avirulent and virulent isolates. Shittu et al. [25] reported the VW disease scores were reduced by half on tomato plants co-inoculated with the highly virulent Vd1 and endophyte Dvd-E6 isolates compared with those recorded from single-inoculated tomato with Vd1. Sunflower challenged prior with the avirulent isolate P6 was protected from sequential inoculation with a virulent isolate of VM, V. dahliae; however, simultaneous inoculation of the two isolates did not result in different disease expressions [24].
We proposed that the D and ND isolates were able to colonise cotton stems equally due to the even number of isolates recovered from the same field-sampled stems. However, in our pot trials, the recovery frequency of D and ND isolates from the confirmed co-infected stems were predominated by one to the other. Mercado-Blanco [19] directly detected both D and ND isolates from co-inoculated olive roots at 0, 7 and 21 days after inoculation; however, DNA directly obtained from stems of the same plants were only positive with the D marker. Similarly, Shittu et al. [25] suggested that tomato plants colonised by the endophyte isolate Dvd-E6 ameliorated the effectiveness of colonisation of the pathogenic isolate Vd1. We postulated that vegetative growth competition may play a minor role in co-infection and co-colonisation of the tested V. dahliae isolates in co-inoculated plants since there were no negative effects of one to the other detected in the dual culture assays. Fecundity and the spore germination rate of the tested isolates could partly play a role in driving this predominant colonisation. For example, the isolate 19V76 produced significantly more spores than 19V77; subsequently, in the two pot trials, the isolate 19V76 was recovered more than the isolate 19V77 in co-inoculated plants. However, we did not see a similar pattern in plants co-inoculated with the L41 and L42 isolates, though L41 produced a higher number of spores which had double the germination rate compared with L42. It is not possible to offer any conclusive recommendations from the current data set since host plant responses also play an important role in a successful colonisation of the pathogen. It will be worth using green fluorescent protein (GFP)-tagged isolates to better understand the interactions between V. dahliae isolates as well as with the host in planta. GFP-tagged V. dahliae was studied to understand its capacity to colonise cotton cultivars with different degrees of susceptibility [28].
The occurrence of both D and ND pathotypes within a single cotton plant under field conditions has also raised concerns regarding the development of disease management strategies. First, commercial Australian cotton germplasms exhibited varietal responses to D and ND pathotypes differently, and to date, there has not been a highly resistant cultivar against both pathotypes, especially to the D pathotype (C. R. Trapero per. comm.). Therefore, there will be limited cultivars available for V. dahliae-infested fields where the co-occurrence of both D and ND pathotypes in cotton plants were detected. However, before this raises an alarm, a thorough assessment of the damage that co-infection may cause should be pursued. The co-infection incidence under natural field conditions was detected at a low level in the previous two seasons. We continue to carry out disease surveillance, which has been ongoing for over 30 years in NSW, to enable the monitoring of the occurrence and distribution of the co-infection of both D and ND pathotypes on cotton. Second, genetic combination was also questioned. Wheeler and Johnson [22] recently reported the putative anastomosis in planta when mustard plants were co-inoculated with three isolates: potato 653, mint 111 and tomato 461. Therefore, understanding the diversity of the isolate collection recovered from co-infected cotton in this study will warrant future research.

Sampling and Isolating
During the 2017/18 and 2018/19 survey seasons, cotton stems from VW-suspected plants were sampled for further confirmation through isolation and identification of the actual causal agent. Where possible, at least three VW-suspected stem cuts, approximately 10-15 cm long, were sampled from each of the surveyed fields. These stem cuts were double-bagged inside a paper bag and another outside zip-lock plastic bag. The stem cuts were stored in an esky (a portable cooler) away from direct Plants 2020, 9, 750 8 of 11 sunlight during the survey trips and immediately transferred to a 4 • C fridge/cold room after each trip until further processed.
Isolation of the putative pathogen was initiated by excising each of the stem cuts into smaller sections, 1-2 cm long, and peeling off the outer bark. Under aseptic conditions, each of the peeled sections was sprayed and left for 30 s with 70% ethanol for surface decontamination. The sprayed section was then plotted dry with paper towel and split in half using a sterile scalpel. Inner vascular discoloured tissues (wood chips) were thinly sliced with the scalpel and embedded into sPDA. sPDA was made of potato dextrose agar (PDA Difco) amended with 100 ppm streptomycin sulfate (Sigma Aldrich) and contained in Petri plates. The plates with embedded vascular tissues were sealed with parafilm and incubated at 25 • C in the dark for 3-5 days. Putative fungal colonies emerging from vascular tissues were individually sub-cultured onto new sPDA plates and single spore cultures were established. Pure cultures were then transferred onto half strength sPDA and incubated at 25 • C in darkness for at least a week before small plugs (0.5 cm 2 ) were excised from the colony margins, submerged in sterile water and stored at room temperature for subsequent experimentation.

DNA Extraction
Genomic DNA was obtained using a Wizard ® Genomic DNA Purification Kit (Promega, Sydney Australia) following the manufacture's protocol. However, slight modifications were deployed to suit our laboratory conditions. A small amount of mycelia (10-100 mg) was scraped off culture plates and transferred into a 1.5 mL tight-lock Eppendorf tube. Then, 50 µL Nuclei Lysis Solution was added along with two steel beads (3.3 mm dia.) to each tube and shaken to macerate the mycelia on a tissue lyser (Retsch ® MM300) for 1 min at a frequency of 28 times per second. Another 450 µL Nuclei Lysis Solution was then added to each of the tubes, vortexed to homogenicity and followed by incubation in a water bath at 65 • C for 30 min. After incubation, 3 µL RNase A Solution was added to each of the tubes and followed by another incubation at 37 • C for 15 min. After cooling down at room temperature for 5 min, 200 µL Protein Precipitation Solution was added and vortexed vigorously to homogenicity and followed by a centrifugation at 13,000 rpm for 5 min. The supernatants were carefully transferred to new 1.5 mL Eppendorf tubes containing 600 µL room temperature isopropanol. The tubes were gently inverted and centrifuged at 13,000 rpm for 1 min. The supernatants were carefully decanted and the visible DNA pellets were washed twice with 70% room temperature ethanol. The DNA pellets were then air-dried under a fume hood for 30-45 min, rehydrated with 50-200 µL DNA Rehydration Solution depending on the size of the pellets and followed with an incubation at 65 • C for 1 h. The DNA solutions were then stored at −20 • C until use.

Duplex PCR Amplification
A duplex PCR assay developed by Mercado-Blanco et al. [19] was deployed to simultaneously characterise the two defoliating (D) and non-defoliating (ND) pathotypes. All PCR amplifications were carried out using GoTaq ® G2 Green Master Mix (Promega). Each PCR mix contained: 10 µL of Green Master Mix, 8 µL of DNase free water, 1 µL of 10 mM primer mix and 1 µL of DNA template. DNase-free water was included as a negative (no-template) control. The primer mix included 3 portions of DB19 (5 -CGGTGACATAATACTGAGAG-3 ), 2 portions of DB22 (5 -GACGATGCGGATTGAACGAA3 ) and 1 portion of espdef01 (5 -TGAGACTCGGCTGCCACAC-3 ). PCR cycling conditions were slightly modified from Mercado-Blanco et al. [19] as follows: initial denaturation for 5 min at 94 • C followed by 35 cycles of 30 s at 94 • C, 30 s at 52 • C and 90 s at 72 • C, with a final elongation step of 7 min at 72 • C. The PCR products were run at 100 V in a GelRed (GeneTargetSolutions) pre-stained 1.5% agarose gel for 45 min and visualised under UV light using a UVIDOC HD6 (UVITEC Cambridge). D pathotype isolates were predicted to contain two visible PCR amplicons at sizes of 539 and 334 bp, whereas ND pathotype isolates contained a single amplicon at a size of 523 bp [19].

Pathogenicity
Root-dip assays were conducted twice in glasshouse conditions to assess the virulence of D and ND isolates solely and in combination. Two isolates from each of the pathotypes were selected for the pathogenicity assays (Table 3). Both D and ND isolates recovered from the corresponding year were isolated from a single stem. Table 3. A brief description including pathotypes, single-spored status, location and year of recovery of V. dahliae isolates from cotton used in pathogenicity assays. Cotton black seeds (cv. Sicot 75RRF, a VW susceptible cultivar) were sown individually in a 100-cell plastic seedling tray containing Searles ® potting mix and grown in a glasshouse at 10-25 • C for 15 days prior to inoculation. Upon inoculation, seedlings were gently removed from the seedling trays and washed free of the potting mix. The washed seedlings were root-dipped in conidial suspensions of the four tested isolates at the concentration of 10 4 conidia/mL for five minutes and then transferred into 140 mL pots containing Searles ® potting mix. There were two additional co-inoculum mixtures of L41 and L42, and 19V76 and 19V77. Conidial suspensions were mixed and adjusted to 10 4 conidia each/mL. There were two seedlings per pot and five and four replicate pots for each of treatment, respectively, in trial 1 and 2. Control seedlings were treated in the same manner; however, the spore suspension was replaced with sterile water. Inoculated seedlings were maintained in the same glasshouse conditions and monitored for disease occurrence and severity. Disease ratings were as follows: 0 = no symptoms, 1 = chlorosis and wilting of cotyledons, 2 = chlorosis and wilting of first true leaf, 3 = symptoms on lower 50% of the foliage, 4 = symptoms on 51-100% of the foliage and 5 = dead plant.

Isolates
Upon termination of the pathogenicity assays, all plants were subjected to re-isolation of the inoculated pathogens. The isolation of the inoculated V. dahliae from the collar sections was as described previously. All recovered isolates were also subjected to the duplex PCR again for determination of the pathotypes.

Growth Competition Assays
Relative growth of the four tested isolates was assessed singly at 25 • C. Briefly, actively growing V. dahliae cultures on sPDA were excised into 0.5 cm 2 plugs and transferred into the centre of new sPDA plates. Additionally, a dual cultures technique was undertaken to assess the growth competition of the V. dahliae isolates under the influence of one to another. As previously, active cultures of L41 and L42, and 19V76 and 19V77 were excised, transferred in pairs together and placed 5 cm apart onto new sPDA plates. All newly transferred plates were sealed with parafilm and incubated in darkness at 25 • C for seven days before the colony dia. was recorded in perpendicular directions. There were three replicate plates per each isolate/pair and the whole assay was repeated once.

Fecundity and Germination Assessments
Ten-day-old cultures growing at 25 • C in darkness were subjected to spore collection for fecundity and germination assessments. There were three plates per isolate for the fecundity examination. Each plate was flooded with 10 mL of sterile water and gently interrupted with a disposable L-shaped spreader. The spore concentration per mL of the collected suspension was determined using a haemocytometer. The spore suspension was then adjusted to 10 4 per mL for the germination assessment. Three 10 µL aliquots from each of the spore suspensions were individually spread onto clean sPDA plates (n = 9 per isolate). The plates were then incubated at 25 • C in darkness for two days, after which the colonies of V. dahliae were recorded. The experiment was repeated once.
Data collected from the pathogenicity, growth rate, fecundity and germination assays were subjected to an analysis of variance (ANOVA) and the separations of means were determined by Tukey's least significant difference (LSD) test (p ≤ 0.05). The ANOVA and graphing were performed with Graphpad Prism 8.2.0.


provenance: AgriculturalAndFoodSciences,2019-2020-Agricultural And Food Sciences-2020.jsonl.gz.gz

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Bioengineering Techniques Adopted for Controlling Riverbanks’ Superﬁcial Erosion of the Simpl í cio Hydroelectric Power Plant, Brazil

: Controlling and preventing soil erosion on slope surfaces is a pressing concern worldwide, and at the same time, there is a growing need to incorporate sustainability into our engineering works. This study evaluates the e ﬃ ciency of bioengineering techniques in the development of vegetation in soil slopes located near a hydroelectric power plant in Brazil. For this purpose, twelve di ﬀ erent bioengineering techniques were evaluated, in isolation and in combination, in the slopes (10 m high) of two experimental units (approximately 70 m long each) located next to the Para í ba do Sul riverbanks, in Brazil. High-resolution images of the slopes’ frontal view were taken in 15-day interval visits in all units for the ﬁrst 90 days after implantation, followed by monthly visits up to 27 months after the works were ﬁnished. The images were treated and analyzed in a computer algorithm that, based on three-color bands (red–green–blue scale), helps to assess the temporal evolution of the vegetative cover index for each technique adopted. The results showed that most of the solutions showed a deﬁciency in vegetation establishment and were sensitive to climatological conditions, which induced changes in the vegetation phytosanitary aspects. Techniques which provided a satisfactory vegetative cover index throughout the investigated period are pointed out.

Introduction
Soil erosion in slopes is a natural process that involves several processes such as landslides and detachment, dissolution and/or wear of soil particles, followed by their transport and deposition caused by the action of an erosive agent (e.g., water, wind, and/or gravity [1]). Human activities aggravate this process by removing existing vegetation, influencing agriculture and overstocked pasturing, and causing change in natural slopes by cutting operations routinely used in transportation works. This accelerated erosion shows relevant environmental, social, and economic impacts around the world, reducing soil fertility and promoting soil sedimentation in river flows [2]. Therefore, erosion control is a present concern and different techniques have been proposed over the last decades to address this issue, from hard engineering to more sustainable solutions, such as bioengineering [3,4].
Bioengineering is an ancient technique that has recently regained interest and popularity for use in erosion control [5]. It combines live vegetation with or without inert components (e.g., rocks, wood, metal, geosynthetics, etc.) to reinforce soil, prevent and stabilize the erosion process, decrease surface runoff, and increase water infiltration, promoting ecosystem restoration [6][7][8]. The key aspect of this technique, according to Bischetti et al. [5], is that it is intentionally used considering an environmental and landscape perspective.
In a context with an increasing need to account for sustainability in engineering projects, bioengineering systems have clear advantages, because they show lower environmental impact compared to conventional stabilization methods that rely on hard structures such as retaining walls [2,9]. In this context, in Europe and North America, soil bioengineering has been widely used [10].
Research on soil bioengineering has experienced a significant increase over the last decades, leading to major advances over the past 20 years according to Stokes et al. [11], who highlight the relevance and interest of the scientific community [9]. Focus was given to the history and types of bioengineering techniques and applications [5,10,[12][13][14], their technical, economic, environmental, and ecological benefits [15][16][17][18][19], the characterization of relevant physical and mechanical attributes of plant species application in such systems [20][21][22], and some successful case studies in transportation, urban settings, or riverbank restoration in the European Alps [23,24], North America [6,9,25], Central America [26], and South Asia [15,27,28]. The life cycle assessment (LCA) model for soil bioengineering constructions was also proposed [29].
In Brazil, the favorable climate to plant growth (especially the tropical one-characterized by a dry winter and rainy summer) supports the use of bioengineering techniques. However, few studies investigated the use of bioengineering systems in the Brazilian context, especially in large field test studies such as the one presented in this paper. Nonetheless, soil degradation is a major problem throughout the entire country [30]. Sattler et al. [31] highlight that the use of soil bioengineering in southeast Brazil (the economic pole of the country) for restoration and rehabilitation of degraded areas is still incipient, and when applied, relies mostly on the use of non-native plant species that have been shown to work in other tropical regions. After a 15-month monitoring period, the authors [31] reported successful riverbank slope protection when using hedgerow terraces (which work as living fences) with rooted or unrooted live cuttings of five native plant species (shrub or tree) associated with a biodegradable polymer.
Outside the Brazilian context, several studies reported the use of soil bioengineering techniques. Ansted et al. [29] monitored two willow spilling projects (used to prevent riverbank erosion) during the first year after installation to assess their biological and geomorphological function. Rey and Labonne [32] observed a 45% survival rate of willow (Salix) cuttings (after four growing seasons) on bioengineering structures installed in the Francon Catchment (Southern French Alps). Brush layer inclusions were used to stabilize steep slopes along a roadway in Massachusetts [6]. Petrone and Preti [16] assessed which native species were most suited (survival rate higher than 60%) for soil bio-engineering purposes in Nicaragua. Dhital and Tang [15] reported the effectiveness of vegetative check dams and wire net check dams along with vegetation in the stabilization of riverbanks located in Nepal. Furthermore, a laboratory study was carried out by Muhammed et al. [33].
Monitoring restored sites is as important as the planning stage of the restoration program. It can significantly influence the success of the solution used and provides invaluable data for future bioengineering projects, such as the lifetime and efficacy of the bioengineering system on slope stability and erosion control in different regions [2,34]. Nonetheless, studies on the ecological efficiency of slope restoration techniques are still scarce [15].
This study aims to assess the performance of 12 soil bioengineering techniques (systems) in erosion prone slopes of the Simplício Hydroelectric Power Plant-FURNAS in Brazil. We evaluated their viability and performance over 27 months after implantation. The latter was evaluated by periodic qualitative observations (integrity, anchoring, soil stability, germination, phytosanitary aspect, pests' occurrence, nutritional status, and other general aspects) in site visits, and, most importantly by a quantitative evaluation of the evolution and success of vegetative cover index throughout three years to access the long term erosion protection via permanent vegetation establishment. In this way, we intend to contribute to the knowledge building on using soil bioengineering techniques in Brazilian territory, possibly helping to broaden its use in the country.

Methodology
This study reports the application and monitoring of different bioengineering techniques for superficial slope erosion control and analyses the evolution of the vegetation developed in the slope surfaces evaluated. It is worth mentioning that the experimental units have been subjected only to the erosion process caused by the rainfall, which means the river was not in contact with any section of both experimental units (even during the flood seasons). The bioengineering techniques adopted, their application and monitoring, and procedures for determining the vegetative cover index are detailed as follows.

Experimental Units
Two slopes located on the Paraiba do Sul riverbanks, close to the Simplício Hydroeletric Power Plant (Chiador-MG in Brazil; Figure 1) were selected as experimental units in this study. In terms of the geology context, the experimental units are located on a Proerozoic gneiss-magmatic terrain (part of Juiz de Fora and Paraíba do Sul geological complexes), grouped in two lithological types: high-grade paragneisses and orthogneisses (dominant in the area of experiment).
Sustainability 2020, 12, x FOR PEER REVIEW 3 of 21 their viability and performance over 27 months after implantation. The latter was evaluated by periodic qualitative observations (integrity, anchoring, soil stability, germination, phytosanitary aspect, pests' occurrence, nutritional status, and other general aspects) in site visits, and, most importantly by a quantitative evaluation of the evolution and success of vegetative cover index throughout three years to access the long term erosion protection via permanent vegetation establishment. In this way, we intend to contribute to the knowledge building on using soil bioengineering techniques in Brazilian territory, possibly helping to broaden its use in the country.

Methodology
This study reports the application and monitoring of different bioengineering techniques for superficial slope erosion control and analyses the evolution of the vegetation developed in the slope surfaces evaluated. It is worth mentioning that the experimental units have been subjected only to the erosion process caused by the rainfall, which means the river was not in contact with any section of both experimental units (even during the flood seasons). The bioengineering techniques adopted, their application and monitoring, and procedures for determining the vegetative cover index are detailed as follows.

Experimental Units
Two slopes located on the Paraiba do Sul riverbanks, close to the Simplício Hydroeletric Power Plant (Chiador-MG in Brazil; Figure 1) were selected as experimental units in this study. In terms of the geology context, the experimental units are located on a Proerozoic gneiss-magmatic terrain (part of Juiz de Fora and Paraíba do Sul geological complexes), grouped in two lithological types: highgrade paragneisses and orthogneisses (dominant in the area of experiment). Experimental unit I (EU1) consists of two 90-m-long slopes (west facing slope) of approximately 9.5 m height (H) and a slope angle (α) close to 32°, as indicated in Figure 2a. Similarly, the experimental unit II (EU2) consists of two 70-m-long slopes (northwest facing slope): the bottom one with 8.5 m height (H) and α equal to 35°, and the upper one with H = 9.5 m and α = 32° (Figure 2b). To avoid people traffic and animal trampling, the units were demarcated with fences (appropriate materials and equipment were used). The soil samples were collected 300 mm deep from the slopes' surfaces (15 m distant apart from each other) along both units (EU1 and EU2) to provide a representative characterization of its fertility. A total of 10 soil samples was tested for the unit EU1, Experimental unit I (EU1) consists of two 90-m-long slopes (west facing slope) of approximately 9.5 m height (H) and a slope angle (α) close to 32 • , as indicated in Figure 2a. Similarly, the experimental unit II (EU2) consists of two 70-m-long slopes (northwest facing slope): the bottom one with 8.5 m height (H) and α equal to 35 • , and the upper one with H = 9.5 m and α = 32 • (Figure 2b). To avoid people traffic and animal trampling, the units were demarcated with fences (appropriate materials and equipment were used). The soil samples were collected 300 mm deep from the slopes' surfaces (15 m distant apart from each other) along both units (EU1 and EU2) to provide a representative characterization of its fertility. A total of 10 soil samples was tested for the unit EU1, whereas for the EU2, 6 soil samples were collected and tested. Following the test procedures recommended by the Brazilian Agricultural Research Corporation (EMBRAPA [35]), the soil fertility test results (Table 1; classification according to CFSEMG (1999)) indicate that the experimental units show similar fertility, with a low content for all parameters evaluated and medium acidity.  Additionally, Table 2 summarizes characterization and soil strength test results for the experimental units, performed based on the Brazilian Standard (NBR) proposed by the Brazilian Association of Technical Standards (ABNT). The laboratory tests consisted of specific gravity of soil solids (NBR 6458 [36]), grain size distribution (NBR 7181 [37]; classification according to American Society for Testing and Materials (ASTM; D 2487-06 [38]), Atterberg limits (NBR 6459 [39]; NBR 7180 [40]), standard Proctor compaction (NBR 7182 [41]), and a direct shear test (unsaturated soil samples compacted at similar density to the soil from the slopes; ASTM D 3080-98 [42]).
Prior to following the bioengineering techniques, the superficial soil of the slopes of the experimental units was prepared to provide an adequate slope (inclination) and condition for the execution process. The preparation included cleaning, removal of bulges and poorly consolidated soil masses, and manual conformation. Additionally, linear erosions (gullies and deep grooves) close to the experimental units that could impair this study were recovered using organic sediment.  Additionally, Table 2 summarizes characterization and soil strength test results for the experimental units, performed based on the Brazilian Standard (NBR) proposed by the Brazilian Association of Technical Standards (ABNT). The laboratory tests consisted of specific gravity of soil solids (NBR 6458 [36]), grain size distribution (NBR 7181 [37]; classification according to American Society for Testing and Materials (ASTM; D 2487-06 [38]), Atterberg limits (NBR 6459 [39]; NBR 7180 [40]), standard Proctor compaction (NBR 7182 [41]), and a direct shear test (unsaturated soil samples compacted at similar density to the soil from the slopes; ASTM D 3080-98 [42]).
Prior to following the bioengineering techniques, the superficial soil of the slopes of the experimental units was prepared to provide an adequate slope (inclination) and condition for the execution process. The preparation included cleaning, removal of bulges and poorly consolidated soil masses, and manual conformation. Additionally, linear erosions (gullies and deep grooves) close to the experimental units that could impair this study were recovered using organic sediment.  Retainers (OSRs; 0.20-m or 0.40-m width). OSRs consists of polypropylene screen coating filled with herbaceous straw or coconut fiber, prepared to become a suitable substrate for developing vegetation.

Bioengineering Techniques
This study assessed 12 different techniques: 6 isolated bioengineering techniques (IBT) and 6 mixed bioengineering techniques (MBT, more than one technique), both summarized in Table 3. The techniques were chosen based on bibliographic research and consulting to specialized bioengineering companies (information of most common bioengineering techniques adopted in Brazil). The experimental units were divided into sections (EU1: S01 to S11; EU2: S01 to S14; dimensions indicated in Figure 2), and the bioengineering techniques were executed contiguously (randomly) along the experimental units ( Figure 3) according to Table 3. A brief description of each technique is shown in the following table. Manual seeding was adopted as the control technique to evaluate the efficiency of the other techniques adopted herein. Manual seeding consists of the manual launch of seeds (species and quantity described in Table 4), and it was adopted in isolation conditions in EU1-S08 and EU2-S07 and in combination with organic sediment retainers (OSRs) in EU1-S06, EU1-S11, and EU2-S12. Manual seeding attached with organic material (cellulose mulch) was installed in EU1-S09 and in EU1-S10 (combined with OSRs) as an alternative to help germination and vegetation. The specimens presented in Table 4 were chosen based on bibliographic research, an indication of specialized Brazilian companies (including nurseries) and professors from Spellman College, California State University, Universidade Federal de Viçosa, and Universidade Federal de Minas Gerais. Table 3. Bioengineering techniques evaluated and respective installation site-Experimental Unit (EU) and Section (S).

Code
Bioengineering Technique Section Installed
This study also investigated the adoption of flexible organic or synthetic rolls manufactured in greenhouses (live rolled erosion control products; L-RECPs). Structural geogrids (three-dimensional UV-stabilized polypropylene mesh) were layered in a levelled watertight surface followed by a layer of organic RECP. Over the RECPs surface, a mix of fast-growing herbaceous and legume seeds (indicated in Table 4, 10 g/m 2 ), chemical fertilizer (5 g/m 2 ), organic compounds (500 g/m 2 ), and hydrogel (5 g/m 2 ) was spread. Finally, irrigation (2-5 L/m 2 ) was conducted at regular intervals. Images of L-RECPs storing and installation procedures are available in Appendix A ( Figure A2). These elements were installed in isolation at EU1-S01, EU2-S02, and EU2-S03.
Live elements associated with organic sediment retainers (L-OSRs) were cultivated in greenhouses, with dimensions of 0.20 × 2.00 m and 0.40 × 1.60 m (diameter × length). They were installed in isolation (EU2-S06) and associated with live stakes (EU1-S03, EU1-S04, and EU2-S04). The seedlings were planted directly inside the OSR after making beds filled with 100 g of vermiculite associated with 2 g of hydrogel and 20 g of NPK 20:20:20 fertilizer powder. Images from the cultivation up to its installation are available in Appendix A ( Figure A3).
This study also investigated the adoption of erosion control products commercially available in the Brazilian market. Three rolled erosion control products (RECPs) were adopted. The first one (RECP-01) is a coconut fiber blanket (mass per unit area 450 g/m 2 ) composed of a high flexible, UV-stabilized, and non-degradable three-dimensional polypropylene woven matrix, coupled with high resistance metallic hexagonal reinforcement mesh (installed in isolation in EU1-S02). The second RECP (RECP-02) is a two-dimensional erosion control blanket consisting of coconut fibers (mass per unit area 400 g/m 2 ) interlaced and incorporated in photodegradable polypropylene nets (installed in EU1-S05 and EU2-S08 in combination with OSR and in isolation in EU2-S11). Finally, the third RECP (RECP-03) is a straw erosion control blanket consisting of vegetable fibers (agricultural straw; mass per unit area 600 g/m 2 ) interlaced and incorporated in photodegradable polypropylene nets and a third UV-resistant net in the upper face (installed in isolation in EU2-S09 and combined with OSRs in EU2-S10).
An organic sediment retainer (OSR) manufactured using dehydrated vegetable fibers was combined with manual seeding in EU1-S06, EU1-S11, and EU2-S12 and further combined with cellulose mulch in EU1-S10. The experimental sections EU1-S05, EU1-S08, and EU2-S10 received a combination of OSR and rolled erosion control products (RECP). Additionally, a geocellular containment system (GCS) was adopted in sections EU1-S07 and EU2-S05. The GCSs are geobags (manufactured with a geosynthetic mesh of high-density polyethylene (HDPE) combined with an organic geotextile of coconut fiber) filled with herbaceous straw, organic matter, seeds, and fertilizers.

Monitoring the Experimental Units
Monitoring of the experimental unit sections started in December 2016 after completing the bioengineering techniques' implantation works. The monitoring occurred periodically, with 15-day interval visits in all units (i.e., EU1-S01 to EU1-S11 and EU2-S01 to EU2-S12) for the first 90 days after the implantation, followed by monthly visits up to 27 months after the works were finished. In this period, the sections were visited and detailed inspections were carried out using high-quality images taken from the front view of each section. During the visits, preventive and corrective actions were used to take care of leaf-cutting ants, leaf chlorosis, and fence conditions. Furthermore, local qualitative analyses were conducted with evaluation cards (presented in Appendix B) to register integrity, anchoring, soil stability, germination, phytosanitary aspects, pests' occurrence, nutritional status, and other general aspects of the vegetation and/or bioengineering techniques in the experimental units' sections. Due to the existence of diagnostic (observer) bias in the set of characteristics evaluated, these results require a detailed analysis that may include the (observer) bias error and are not in the scope of this study. These qualitative results are aimed to be made available in future publications.

Vegetative Cover Index Determination
The evolution of vegetative cover for each bioengineering technique adopted was evaluated by means of the vegetative cover index, calculated through a computer code in the MATLAB software (2015). The images captured (on a smartphone with wide-angle lens) during the experimental units' monitoring period (27 months; e.g., Figure 4a) were treated and analyzed with a MATLAB script (or algorithm) developed using the method proposed by Woebbecke et al. [44]. This semi-quantitative analysis is proposed as an effective approach to assess the vegetation performance under climatological changes (dry and wet spell cycles).
Prior to its analysis, all images were treated by trimming out the regions outside the analyzed section area (Figure 4b). The MATLAB algorithm splits the image into three color bands (red, green, and blue-RGB scale). The value of each pixel was used to determine the normalized ratio of each color in the band by dividing it by 255, which is the maximum value for each color, as shown in the following Equations (1)- (3): where R*, G*, and B* are the normalized ratio of red, green, and blue colors, respectively, and R, G, and B are the color value of each pixel, which ranges from 0 to 255, respectively. The normalized colors were used to calculate the ratio of each color, r, g, and b, with respect to all three colors in the pixel, as shown in the Equations below (4)- (6): Finally, the excess green (ExG) value is calculated for each pixel using the Woebbecke et al. [45] excess green Equation (7): The ExG value for each pixel was compared to a minimum threshold value that was determined for each image. Thus, if the pixel's ExG value is greater than this threshold value, the pixel is set to represent vegetative covered areas (that means a vegetation pixel). The vegetative cover index is determined for each image by the ratio between the number of green pixels and the total number of pixels in the treated image (white pixels are not considered). In addition, the vegetation pixels were superimposed in the treated image for a visual comparison (Figure 4c).

Vegetative Cover Index Determination
The evolution of vegetative cover for each bioengineering technique adopted was evaluated by means of the vegetative cover index, calculated through a computer code in the MATLAB software (2015). The images captured (on a smartphone with wide-angle lens) during the experimental units' monitoring period (27 months; e.g., Figure 4a) were treated and analyzed with a MATLAB script (or algorithm) developed using the method proposed by Woebbecke et al. [44]. This semi-quantitative analysis is proposed as an effective approach to assess the vegetation performance under climatological changes (dry and wet spell cycles).
Prior to its analysis, all images were treated by trimming out the regions outside the analyzed section area (Figure 4b). The MATLAB algorithm splits the image into three color bands (red, green, and blue-RGB scale). The value of each pixel was used to determine the normalized ratio of each color in the band by dividing it by 255, which is the maximum value for each color, as shown in the following Equations (1)- (3): where R*, G*, and B* are the normalized ratio of red, green, and blue colors, respectively, and R, G, and B are the color value of each pixel, which ranges from 0 to 255, respectively. The normalized colors were used to calculate the ratio of each color, r, g, and b, with respect to all three colors in the pixel, as shown in the Equations below (4)- (6): Finally, the excess green (ExG) value is calculated for each pixel using the Woebbecke et al. [45] excess green Equation (7): The ExG value for each pixel was compared to a minimum threshold value that was determined for each image. Thus, if the pixel's ExG value is greater than this threshold value, the pixel is set to represent vegetative covered areas (that means a vegetation pixel). The vegetative cover index is determined for each image by the ratio between the number of green pixels and the total number of pixels in the treated image (white pixels are not considered). In addition, the vegetation pixels were superimposed in the treated image for a visual comparison (Figure 4c). The vegetative cover index analysis was performed for all images taken while monitoring the experimental units (total of 601) for all sections, and bioengineering techniques were applied. The results were plotted in function of the time after the implanting the bioengineering works to evaluate the evolution of this parameter during the investigated period. In this study, vegetative cover index The vegetative cover index analysis was performed for all images taken while monitoring the experimental units (total of 601) for all sections, and bioengineering techniques were applied. The results were plotted in function of the time after the implanting the bioengineering works to evaluate the evolution of this parameter during the investigated period. In this study, vegetative cover index values higher than 70% are considered to represent a satisfactory superficial slope cover condition [45], in other words, to ensure the protection/control against erosion of the slope superficial soil.

Climatological Data
To compare the evolution of the vegetative cover index with the regional seasons, climatological data was obtained from the closest working weather station, 31 km from the experimental units. The precipitation data (in mm), obtained with a rain gauge, are summarized in Figure 5 for the inspection period adopted herein. In summary, the local climatological condition is comprised of a rainy (wet) period during the spring and summer seasons and a dry period during the autumn and winter seasons.
Sustainability 2020, 12, x FOR PEER REVIEW 9 of 21 values higher than 70% are considered to represent a satisfactory superficial slope cover condition [45], in other words, to ensure the protection/control against erosion of the slope superficial soil.

Climatological Data
To compare the evolution of the vegetative cover index with the regional seasons, climatological data was obtained from the closest working weather station, 31 km from the experimental units. The precipitation data (in mm), obtained with a rain gauge, are summarized in Figure 5 for the inspection period adopted herein. In summary, the local climatological condition is comprised of a rainy (wet) period during the spring and summer seasons and a dry period during the autumn and winter seasons.  Figure 6 shows the vegetative cover index evolution for the bioengineering techniques installed in isolation at the experimental units. The vegetative cover index evolutions can be divided into five different groups. The first one exhibits vegetative cover index values lower than 40% (nonsatisfactory values) during the whole period investigated. The index experienced small increases during the wet periods and remained or decreased during the dry ones. The manual seeding (IBT-1; EU1-S08 and EU2-S07), live stakes (IBT-2; EU2-S01), and live organic sediment retainer (L-OSRs; IBT-3; EU2-S06) techniques comprise this group (Figure 6a). The second group presented satisfactory vegetative cover index values (higher than 70%) 25 days after it was implemented and small reductions at the end of the wet periods (especially the third period). Two techniques installed in the first experimental unit compose this group: live rolled erosion control products (L-RECPs; IBT-4; EU1-S01) and rolled erosion control product (RECP-01; IBT-5; EU1-S02).

Results and Discussion
The third group identified in Figure 6 comprises L-RECPs installed at the second experimental unit (IBT-4; EU2-S02 and EU2-S03) and the geocellular containment system (GCS) installed in EU1-S07. Similar to the second group, this group exhibited satisfactory vegetative cover index values very soon (25 days after its implementation). However, there was a significant reduction in the index values during the first dry period (softer reduction for the GCS-EU1-S07) followed by an increase in the following two periods, and a small reduction in the index values at the third wet period. RECPs installed in the second experimental unit (RECP-2 in EU2-S09 and RECP-03 in EU2-S11) are considered the fourth group and showed a high variation in the vegetative cover index values during the period investigated (increases in the wet periods and sharp decreases in the dry ones). A particular case in Figure 6 (the fifth group) is the GCS installed at EU2-S05 that started a significant increase in the vegetative cover index values at the middle of the first dry period and maintained a  Figure 6 shows the vegetative cover index evolution for the bioengineering techniques installed in isolation at the experimental units. The vegetative cover index evolutions can be divided into five different groups. The first one exhibits vegetative cover index values lower than 40% (non-satisfactory values) during the whole period investigated. The index experienced small increases during the wet periods and remained or decreased during the dry ones. The manual seeding (IBT-1; EU1-S08 and EU2-S07), live stakes (IBT-2; EU2-S01), and live organic sediment retainer (L-OSRs; IBT-3; EU2-S06) techniques comprise this group (Figure 6a). The second group presented satisfactory vegetative cover index values (higher than 70%) 25 days after it was implemented and small reductions at the end of the wet periods (especially the third period). Two techniques installed in the first experimental unit compose this group: live rolled erosion control products (L-RECPs; IBT-4; EU1-S01) and rolled erosion control product (RECP-01; IBT-5; EU1-S02).

Results and Discussion
The third group identified in Figure 6 comprises L-RECPs installed at the second experimental unit (IBT-4; EU2-S02 and EU2-S03) and the geocellular containment system (GCS) installed in EU1-S07. Similar to the second group, this group exhibited satisfactory vegetative cover index values very soon (25 days after its implementation). However, there was a significant reduction in the index values during the first dry period (softer reduction for the GCS-EU1-S07) followed by an increase in the following two periods, and a small reduction in the index values at the third wet period. RECPs installed in the second experimental unit (RECP-2 in EU2-S09 and RECP-03 in EU2-S11) are considered the fourth group and showed a high variation in the vegetative cover index values during the period investigated (increases in the wet periods and sharp decreases in the dry ones). A particular case in Figure 6 (the fifth group) is the GCS installed at EU2-S05 that started a significant increase in the vegetative cover index values at the middle of the first dry period and maintained a value close to 60% until the end of the investigated period. The results presented in Figure 6a indicate that the adoption of the in-isolation manual seeding technique (IBT-1) can be insufficient to prevent and control slope superficial soil erosion. Considering the vegetation establishment, difficulties can be observed since the first wet period, and it proves to be highly influenced by the changes in the climatological condition (especially during the dry periods). In addition, widespread laminar erosion and small grooves were reported in EU1-S08 at the end of the inspection period, proving the inefficiency of this technique.
Adopting live stakes in an isolated condition (IBT-2; EU2-S01) presented minimal effectiveness for the soil conditions and vegetation species used in this study. Three main factors impair its application: the values of the vegetative cover index for IBT-2 were slightly higher than the ones obtained with IBT-1 (Figure 6a), the time consumed for the cultivation of the stakes, and the costs involved in the processes. Similarly, adopting live organic sediment retainers (L-OSRs) in isolation conditions (IBT-3; EU2-S06) proves to be inefficient. In fact, this technique (IBT-3) provided values of vegetative cover index smaller than the ones obtained with IBT-1 (Figure 6a). The results presented in Figure 6a indicate that the adoption of the in-isolation manual seeding technique (IBT-1) can be insufficient to prevent and control slope superficial soil erosion. Considering the vegetation establishment, difficulties can be observed since the first wet period, and it proves to be highly influenced by the changes in the climatological condition (especially during the dry periods). In addition, widespread laminar erosion and small grooves were reported in EU1-S08 at the end of the inspection period, proving the inefficiency of this technique.
Adopting live stakes in an isolated condition (IBT-2; EU2-S01) presented minimal effectiveness for the soil conditions and vegetation species used in this study. Three main factors impair its application: the values of the vegetative cover index for IBT-2 were slightly higher than the ones obtained with IBT-1 (Figure 6a), the time consumed for the cultivation of the stakes, and the costs involved in the processes. Similarly, adopting live organic sediment retainers (L-OSRs) in isolation conditions (IBT-3; EU2-S06) proves to be inefficient. In fact, this technique (IBT-3) provided values of vegetative cover index smaller than the ones obtained with IBT-1 (Figure 6a).
Live rolled erosion control products (L-RECPs) installed in isolation (IBT-4; EU1-S01, EU2-S02 and EU2-S03) proved to be an attractive technique to prevent slope superficial erosion. However, for the sections of the second experimental unit (EU-2), sharp drops (dry periods or beginning of the wet periods) and sensitive reductions (especially during wet periods) characterize the evolution of vegetative cover index for this technique (Figure 6b).
Changes in the vegetation phytosanitary aspects (chlorosis and phytopathogen conditions) explain the sharp drops observed. The predecessor dry period could change the phytosanitary aspects of the vegetation, leading to an intensive decay of its green colors (becoming faded). Considering the computer code adopted in this study, when the treated image (containing faded vegetation) is subjected to the RGB scale, a decrease may occur in the pixel's green value, culminating in its identification as a pixel that does not represent vegetation, decreasing the vegetative cover index.
Considering the sensitive reductions, they can be attributed to the predominant vegetation composition (type). Some vegetative species may not adapt to the soil and/or climatological conditions (especially the non-native species), leading to changes in the vegetation phytosanitary aspects (initially) and/or the vegetation death. Further studies are required to validate this assumption and identify which species are unsuitable.
Three types of rolled erosion control products (RECPs) commercially available on the Brazilian market were installed in isolated conditions (IBT-5). RECP-01 (EU1-S02) exhibited a quick establishment of the vegetation-less than 30 days after it was implanted-and it has not been significantly influenced by climate changes (Figure 6c). Similar results were reported by Álvarez-Mozos et al. [46]. RECP-02 (EU2-S11) and RECP-03 (EU2-S09) also presented a quick establishment of the vegetation, but sharp drops and sensitive reductions in the vegetative cover index values are clear (Figure 6c).
Despite the similar behavior of the vegetative cover index evolution, RECP-02 exhibited a better re-establishment of the vegetation in the third wet period. Thus, one must consider that RECPs comprising coconut fibers could be more susceptible to vegetation development than the ones comprising vegetable fiber (straw). It is worth mentioning that these conclusions are specific for the conditions of soil and vegetation species used in this study. Furthermore, these products are indicated for temporary slope protection, as high degrees of deterioration were evident at the end of the inspection period-similar results were reported by Vishnudas [47].
Considering the last in-isolation technique investigated (IBT-6), the geocellular containment system (GCS) installed in EU1-S07 and EU2-S05 exhibited similar vegetation evolutions (Figure 6d). The non-satisfactory vegetative cover index values reported are associated with the difficulty of seeds' germination and establishment. The geotextiles act as a barrier between the seeds and the soil [44,48] and between the sunlight and soil, leading to low germination rates [49]. However, the IBT-6 technique proved to avoid slope superficial erosion processes, as no erosive processes were reported during the inspections performed in the investigated period.
One must be aware of the shortcomings of comparing the performance of the in-isolation techniques in the experimental units one (EU-1) and two (EU-2). As shown by the results of the manual seeding (IBT-1; Figure 6a), L-RECPs (IBT-4; Figure 6b), and GCS (IBT-6; Figure 6d) techniques, differences in the vegetation development (and establishment) between sections installed in EU-1 and EU-2 were noted (especially in the dry periods). Overall, these results show that the sections of the second experimental unit (EU2) were more sensitive to climatological changes. In fact, because of the experimental units' different orientation (slope aspects stated in topic 2.1), the sections of EU2 face sunlight exposure for a longer period compared to the sections of EU1. This difference hampers the comparison between the results obtained with the RECPs' isolated technique (IBT-5, Figure 6c). It is not ideal to compare the results obtained with RECP-01 with RECP-02 and/or RECP-03, because they were installed under the different experimental units and a different type of RECPs was adopted in each case. Figure 7 shows the vegetative cover index evolution for the mixed bioengineering techniques installed at the experimental units. The vegetative cover index evolutions can be divided into three different groups. The first group exhibits vegetative cover index evolution similar to the first group of the in-isolation bioengineering techniques: unsatisfactory vegetative cover index values throughout the whole investigated period and increases during wet periods and maintenance or decrease of the index values during the dry periods. The manual seeding and cellulose mulch (MBT-1; EU1-S09), manual seeding and organic sediment retainers (OSRs; MBT-2; EU1-S06), and live stakes and live organic sediment retainer (L-OSRs; MBT-4; EU2-S04) techniques comprise this group. Manual seeding and ORSs (MBT-2; EU2-S12); live stakes, L-ORSs, and manual seeding (MBT-5; EU1-S04); and RECPs and OSRs (MBT-6; EU2-S10) techniques set the second group. This group is characterized by vegetative cover index values between 20 and 70%, sharp drops in the index values at the end of the dry periods, and its increase during the wet ones.
Finally, the third group of mixed bioengineering techniques is characterized by a satisfactory vegetative cover index 30 days after the techniques were implemented, followed by variations (increases and decreases) in the index values for the whole period investigated (decreases occurred especially at the end of the periods-regardless of wet or dry ones). Despite this variability, the sections of this group exhibited a satisfactory vegetative cover index at the end of the investigation period. This group is comprised by manual seeding and ORSs (MBT-2; EU1-S11); manual seeding, cellulose mulch and OSRs (MBT-3; EU1-S10); live stakes, L-ORSs and manual seeding (MBT-5; EU1-S03); and rolled erosion control products (RECPs) and OSRs (MBT-6; EU1-S05 and EU2-S08).
The results presented in Figure 7a revealed that adopting organic material (cellulose mulch) attached with manual seeding (MBT-1) did not provide any improvement in the vegetation establishment compared with the in-isolation manual seeding technique (IBT-1; Figure 6a). In addition, widespread laminar erosion and small grooves were reported in the section (EU1-S09) at the end of the inspection period. Thus, adding organic material attached to the manual seeding technique does not seem to be an effective technique for the soil conditions studied in this paper. Further studies are required to assess other types of organic material attached to the manual seeding technique.
In the case of the combined adoption of organic sediment retainers (OSRs) and manual seeding technique (MBT-02), better establishment of the vegetation (Figure 7a) compared with IBT-1 (Figure 6a) is evident. However, MBT-2 exhibited high variability in the vegetative cover index evolution between the sections installed (EU1-S06, EU1-S11 and EU2-S12)-a notable difference occurs between EU1-S06 and EU1-S11, installed at the same experimental unit (EU1). Furthermore, this technique proved to be vulnerable to climatologic changes (dry-wet cycles) for the particular vegetation species used. Despite these issues, this mixed bioengineering technique prevented the occurrence of slope superficial erosion, as no erosion process was encountered in the sections up to the end of the investigation period. This evidence was expected, as the OSR decreases runoff on the slopes, retains humidity and nutrients in the system, and promotes vegetation establishment [50].
Despite the variability encountered for the aforementioned technique (MBT-2), the OSRs provided an excellent vegetation development when added to the manual seeding technique attached to organic material-cellulose mulch (MBT-3, EU1-S10; Figure 7a). MBT-3 proves to be an effective technique as slope superficial soil erosion protection.
The combination of live stakes (IBT-02) and L-OSRs (IBT-03) techniques (MBT-4; EU2-S04; Figure 7b) did not provide an improvement in the vegetation development compared to its in-isolation techniques (IBT-02 and IBT-03; Figure 6a). Despite the slight influence of the climatological condition in the vegetative cover index values, difficulties in the vegetation establishment occurred even during the wet period. Moreover, laminar erosion and grouting processes were reported during the inspections.
On the other hand, the combination of live stakes, live organic sediment retainers (L-OSRs), and manual seeding (MBT-5; EU1-S03 and EU1-S04) exhibited an improvement of the vegetation establishment ( Figure 7) compared to its applications in isolation conditions (IBT-1, IBT-2, and IBT-3; Figure 6a). However, this technique exhibits an unexpected variability (MBT-5): vegetative cover index evolution between sections EU1-S03 and EU1-S04 is very different. As both sections are located side-by-side (Figure 2) and under identical climatological conditions, the difference in the vegetation evolution may be caused due to intrinsic variability of the technique-more than one material can contribute with its own variability.
Finally, the last mixed bioengineering technique (MBT-6) evaluated comprised the combination of RECPs and OSRs (Figure 7c). RECP-2 installed with OSRs (EU1-S05 and EU2-S08) exhibited better vegetation establishment, compared to RECP-3 installed with OSRs, during the whole period investigated (EU2-S10). Once again, the RECPs comprised by coconut fibers proves to be more susceptible for vegetation development than the ones comprised of vegetable fiber (straw) for similar conditions (soil and vegetation species used), as considered in this study.
Finally, the last mixed bioengineering technique (MBT-6) evaluated comprised the combination of RECPs and OSRs (Figure 7c). RECP-2 installed with OSRs (EU1-S05 and EU2-S08) exhibited better vegetation establishment, compared to RECP-3 installed with OSRs, during the whole period investigated (EU2-S10). Once again, the RECPs comprised by coconut fibers proves to be more susceptible for vegetation development than the ones comprised of vegetable fiber (straw) for similar conditions (soil and vegetation species used), as considered in this study.
Differences between the vegetative cover index evolution between the same technique installed in both experimental unit sections were also evident in MBT-3 and MBT-6 (with RECP-2). These differences are related to the experimental units' different orientation (stated in topic 2.1) as previously discussed.
Despite the benefits of using geosynthetics (polymeric based materials) in geotechnical works, one must be aware of the long-term environmental impacts caused by using these materials. The small particles resulting from the geosynthetic degradation (micro plastic) may enter the environment, resulting in soil pollution and spoiling the fauna [48,[51][52][53].

Conclusions
In this study, different types of bioengineering techniques were evaluated, in isolation and in combined conditions, as systems to prevent/control superficial erosion processes in the slopes of Paraíba do Sul-MG (Brazil). High-quality images taken from periodical visits conducted over the course of 27 months were submitted to a computer code to assess the percentage of vegetation developed in the slopes' superficial soil through time. Based on the results obtained in this study, the following conclusions can be drawn: • Despite the similar characteristics of the soil of the two selected experimental units, the effectiveness of the same technique applied to both (EU1 and EU2) seems to be influenced by the differences in their climatological conditions. As the experimental units are only 1.2 km apart, differences in their climatological conditions can hardly be attributed to differences in rainfall events. Thus, due to the experimental units' different orientation, experimental unit two (EU2) was exposed to sunlight incidence for longer periods compared to experimental unit one (EU1). In this case, EU2 experienced significant changes in the vegetation's phytosanitary aspects, impairing the vegetative cover index's determination. This hypothesis is supported by the sharp drops in the vegetative cover index for most techniques at the end or after the dry periods in the EU2.

•
Among the six in-isolation bioengineering techniques evaluated in this study, adopting manual seeding, live stakes, and live organic sediment retainers (L-OSRs) exhibited vegetative cover index values smaller than 40%, with difficulties in vegetation establishment over the 27-month investigated period (fluctuation in its values were also present). These techniques have not proven to be effective to prevent/control slopes' superficial erosion. Despite the high values of vegetative cover index observed when geocellular containment systems (GCSs) were applied, this technique exhibited fluctuation throughout the period investigated, which indicates vegetation establishment deficiency.

•
Live rolled erosion control products (L-RECPs) and a highly flexible, UV-stabilized, and non-degradable three-dimensional matrix rolled erosion control product (RECP) investigated in isolation conditions exhibited a high tendency for vegetation development. L-RECPs led to a swift establishment of the vegetation. Adopting different types of RECPs available in the Brazilian market has shown that RECPs comprised of coconut fibers were more susceptible for vegetation development than the ones comprised of vegetable fiber (straw) for the specific soil conditions and vegetation species used herein. However, one must consider that for these techniques (L-RECPs and RECPs), the development of vegetation seems to be highly susceptible to harsh climatological conditions (especially the dry periods).

•
Incorporating organic material (cellulose mulch) to the manual seeding technique did not improve the vegetation development. The inclusion of organic sediment retainers (OSR) to the manual seeding technique exhibited an expressive variability on the vegetative cover index, with a high influence of the dry periods in the vegetation establishment. However, the combination of manual seeding, cellulose mulch, and organic sediment retainers (OSR) proved to be an excellent technique, inducing a quick establishment of vegetation with satisfactory vegetative cover index and only slight fluctuations during the period investigated. Live stakes combined with organic sediment retainers (OSR) and the manual seeding technique exhibited high variability and non-satisfactory vegetative cover index. OSRs combined with commercially available RECPs exhibited a significant variability and proved to be sensitive in locations with a harsh climatological condition (especially the dry periods).

•
The sharp drop and sensitive reductions in the vegetative cover index can be attributed to different factors. The sharp drops, especially at the end or after the exposure to dry periods, possibly occurred due to significant changes in the vegetation's phytosanitary aspect, in other words, an intensive decay on the vegetation's green color. Regarding the sensitive reductions in the vegetative cover index, especially in wet periods, they can be attributed to difficulties in some vegetative species (possibly the non-native ones) to adapt to the soil and/or climatological conditions of the area, resulting in a similar change in the vegetative phytosanitary aspects or vegetation death. In both cases, the reductions experienced in the vegetative cover index derive from the methodology adopted in this study, which did not include faded vegetation in the vegetative cover index. It should be noted that this conservative procedure aims to neglect the vegetation without adequate phytosanitary aspects, considering that they are not able to prevent the surface erosion of the slopes.
Finally, the conclusions presented in this study are restricted to the specific site-conditions investigated herein: the given slope, a sandy silt soil with low fertility and medium acidity in a tropical climate, and for the specific selected vegetation species used in the treatments. Therefore, caution should be exercised when using these conclusions for different site-conditions.

•
The sharp drop and sensitive reductions in the vegetative cover index can be attributed to different factors. The sharp drops, especially at the end or after the exposure to dry periods, possibly occurred due to significant changes in the vegetation's phytosanitary aspect, in other words, an intensive decay on the vegetation's green color. Regarding the sensitive reductions in the vegetative cover index, especially in wet periods, they can be attributed to difficulties in some vegetative species (possibly the non-native ones) to adapt to the soil and/or climatological conditions of the area, resulting in a similar change in the vegetative phytosanitary aspects or vegetation death. In both cases, the reductions experienced in the vegetative cover index derive from the methodology adopted in this study, which did not include faded vegetation in the vegetative cover index. It should be noted that this conservative procedure aims to neglect the vegetation without adequate phytosanitary aspects, considering that they are not able to prevent the surface erosion of the slopes.
Finally, the conclusions presented in this study are restricted to the specific site-conditions investigated herein: the given slope, a sandy silt soil with low fertility and medium acidity in a tropical climate, and for the specific selected vegetation species used in the treatments. Therefore, caution should be exercised when using these conclusions for different site-conditions.   Good (Germination of 25% up to 1 month after cultivation or germination of 50% for 1-3 months after cultivation or germination of 70% after 3 months of cultivation) Medium (Germination of 15% up to 1 month after cultivation or germination of 30% for 1-3 months after cultivation or germination of 50% after 3 months of cultivation) Good (Germination less than 25% up to 1 month after cultivation or germination less than 30% for 1-3 months after cultivation or germination less than 50% after 3 months of cultivation)


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EVALUATION OF THE QUALITY OF TOMATO SEED POPULATIONS FROM THE ORGANIC PRODUCTION SYSTEM DURING AGING

A total of six tomato seed populations, collected in the autumn of 2016 at different locations in Serbia (West (3), South (1), North (1) and East (1)), were enrolled in this study. Seeds of the tomato populations considered were produced in the organic growing system in the area of Zaovice (76 m a.s.l., chernozem), Stara Pazova, Northern Serbia (44 ̊ 47 '19.6" N, 20 ̊ 27' 56.2" E) in 2017. Analyses of the germination parameters of the tomato seed populations examined (namely the germination energy, total germination, abnormal seedlings and dead seeds of the tomato seeds considered) indicated significant (р < 0.01) differences according to the production year (A) and the tomato seed population (B). The impact interactions (р < 0.01) of these factors (A × B) proved significant only relative to dead seeds. A highly significant positive correlation was found between the germination energy and the total germination of the seeds considered (r = 0.8711, p < 0.001), as well as between the amounts of their abnormal seedlings and dead seeds (r = 0.92297, p < 0.001). The germination energy and the total germination of the tomato seeds considered were found to decrease with the increasing seed age, in contrast to the numbers of their abnormal seedlings and dead seeds which continued to increase with seed aging.

INTRODUCTION
Seeds are one of the basic preconditions of successful agricultural production and regular yields of high quality. Therefore, the identification and testing of seed quality, i.e. vigor, is of paramount importance to crop production (Poštić et al., 2019). Vigor or biological viability is used to describe the physiological properties of seeds responsible for their ability to germinate rapidly in the soil (Tabaković et al., 2013). There is a deficit in organic seeds both in Serbia and worldwide, which is being increasingly compensated for by conventional non-treated seeds. However, the EU experts have announced that organic production will not be able to use untreated seeds from conventional production as of 2021. Over the past twenty years, the global organic production has rapidly expanded due to growing concerns about human health and a great demand for "healthy" food (Postic et al., 2018). Organic farming and organic tomato production have recently been receiving increased attention in Serbia. However, there are no accurate data on the organic production of tomatoes in Serbia to date.
Nowadays, a 0.9 % share of the total agricultural land in the world is devoted to organic agriculture. However, the largest share of 6.2 % of the agricultural land devoted to organic farming is recorded in Europe. As many as eight EU countries have an average of more than 10 % of their agricultural land devoted to organic farming. However, only a 0.4 % share of the total agricultural land is devoted to organic farming in Serbia. A total of 13,423 ha were devoted to organic production in Serbia in 2017, or 0.4 % of the total Serbian arable land, with 6,022 registered organic producers (FiBL, 2020). Tomatoes are one of the most common and economically significant vegetable crops in Serbia, grown in the open field or in protected areas. The conventional production of tomatoes in Serbia approximates to 180,000 t, covering a land area of 20,000 ha. Owing to the lack of organic seeds in the market, domestic producers use seeds from their own production and/or local seed populations adapted to the agroecological conditions in Serbia (Ugrenović et al., 2015).
A continuous decrease in the number of well-established local seed populations in Serbia poses a great threat to the local biodiversity and genetic resources. In the face of increasing production issues caused by climate change, it is necessary to collect and preserve as many well-established local seed populations and plant varieties as possible because they carry many genes for resistance to various adverse environmental conditions and plant diseases (pathogens). The purpose of this study is to evaluate the effects of production year and seed population on the most significant indicators of the quality of organic tomato seeds. The results obtained emphasize the overriding importance of domestic seed populations and plant varieties of tomatoes and other vegetable crops for organic agriculture.

MATERIAL AND METHOD
Production of tomato seeds in the organic farming system. A total of six tomato seed populations, collected in the autumn of 2016 at different locations in Serbia (West (3), South (1), North (1) and East (1)), were enrolled in this study. Seeds of the tomato populations considered were produced in the organic growing system in the area of Zaovice (76 m a.s.l., chernozem), Stara Pazova, Northern Serbia (44˚ 47 '19.6" N, 20˚ 27' 56.2" E) in 2017. The soil properties are shown in Table 1.
Seed sowing was performed using containers in early April, whereas planting in the open field was carried out in mid-May (at a distance of 0.4 × 0.7 m and in a plot area of 10 m 2 ). Crop management was conducted according to the commonly accepted recommendations for growing tomatoes in the organic production system. Tomatoes were harvested at full physiological maturity during August and September, followed by seed extraction and 24-hour seed fermentation. Seed drying was performed in the shade at room temperature. The seeds were stored in PVC bags at a temperature below 15ºC, RH 50%. The data on meteorological conditions are shown in Table 2. Seed quality assessment. The evaluation of tomato seed quality (namely the germination energy, total germination, abnormal seedlings and dead seeds of the tomato seeds considered) was conducted in 2017, 2018 and 2019 at the Laboratory for Seed and Planting Material Testing of the Institute for Plant Protection and the Environment in Belgrade.
The germination testing of six seed populations considered was performed using a standard laboratory method involving filter paper moistened with a 0.2 % aqueous KNO 3 solution at 4 × 100 seeds. The seeds were incubated for 14 days at a temperature of 20-30 °C and a relative air humidity of 95 %. The germination energy after 5 days of incubation, the total germination and the numbers of abnormal seedlings and dead seeds after 14 days of incubation of the tomato seeds considered were determined according to the Rules on the Quality of Seeds of Agricultural Plants ("Official Gazette of SFRY ", no. 47/87), which are in accordance with the ISTA Rules (ISTA, 2002(ISTA, -2018. Statistical analysis. The experimental data obtained were processed using the statistical package STATISTICA 8.0 for Windows. Differences between the treatments were determined using the analysis of variance (ANOVA), whereas the least significant difference (LSD) test was used for individual comparisons. Correlations between the parameters observed were determined using the Pearson correlation coefficient (r).

RESULTS AND DISCUSSION
Analyses of the germination parameters of the tomato seed populations examined (namely the germination energy, total germination, abnormal seedlings and dead seeds of the tomato seeds considered) indicated significant differences (р < 0.01) according to the production year (A) and the tomato seed population (B). The results obtained in the present study are consistent with the results of Stanisavljević et al., (2018). The impact interactions (р < 0.01) of these factors (A × B) proved significant only relative to dead seeds.  The total germination of the tomato seed populations considered ranged from 81 % to 98 % ( Table 5). As expected, the highest average total germination of 94 % was determined in 2017, followed by 88 % in 2018 and 84 % in 2019. After harvest (2017), the decreases in the overall germination of the tomato seed populations considered ranged on average from 6 % in 2018 to 10 % in 2019. The results obtained are consistent with the results of Poštić et al., (2011). Lower variability was found in the germination energy (Table 4) and the total germination (Table 5) of the tomato seeds considered, ranging from 3.15 % to 11.43 %. The number of abnormal seedlings of the tomato seeds considered was found to increase with the increasing age of tomato seeds, ranging from 0 % in the first year to 9 % in the third year (Table 6). The smallest average number of abnormal seedlings of 3.33 % was observed in the Jabučar East population (Negotin), whereas the largest number of abnormal seedlings of 7.33 % was observed in the Jabučar West population (Šabac). The number of dead seeds of the tomato seeds considered increased with seed aging, ranging from 2 % in the first year to 10 % in the third year (Table 7). High variability was found for abnormal sprouts (Table 6) and dead seeds (Table 7), ranging from 13.32 % to 91.65 %.
The coefficients of correlation (r) computed express the interdependence between the seed quality parameters observed ( Table 6). As expected, a highly significant positive correlation was found between the germination energy and the total germination of the tomato seeds considered (r = 0.8711, p < 0.001), as well as between the numbers of their abnormal seedlings and dead seeds (r = 0.92297, p < 0.001). The results obtained are consistent with the results of Stanisavljević et al., (2017). Table 4. Effects of the production year and seed population on the germination energy (%)

Population (B) / Origin
Year (  The strongest negative correlation was found between the germination energy of the tomato seeds considered and the numbers of their abnormal seedlings (r = -0.82930, p < 0.001) and dead seeds (r = -0.87727, p < 0.001), as well as between the total germination of the tomato seeds considered and the numbers of their abnormal seedlings (r = -0.97903, p < 0.001) and dead seeds (r = -0.98202, p < 0.001).

CONCLUSION
Production year, seed population and plant variety exerted strong effects on the quality of organic tomato seeds (namely the germination energy, total germination, abnormal seedlings and dead seeds of the tomato seeds considered). The tomato seed populations examined exhibited lower variability in the germination energy and the total germination with seed aging. However, high variability was observed in the numbers of their abnormal seedlings and dead seeds. A highly significant positive correlation was found between the germination energy and total germination of the tomato seeds considered (r = 0.8711, p < 0.001), as well as between the numbers of their abnormal seedlings and dead seeds (r = 0.92297, p<0.001). The germination energy and the total germination of the tomato seeds considered were found to decrease with the increasing seed age, in contrast to the numbers of their abnormal seedlings and dead seeds which continued to increase with seed aging.