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Pectobacterium and Dickeya species detected in vegetables in Northern Ireland

Destructive soft rot Pectobacteriaceae affect a number of vegetable crops and cause high economic loses in the field and storage. The diversity of Pectobacterium and Dickeya causing soft rot of vegetables in Northern Ireland is unknown. This study provides details of Pectobacterium and Dickeya spp. detected in vegetables from several locations in Northern Ireland in the years 2015–2017. Soft rot Pectobacteriaceae were identified based on DNA sequences. Thirty one strains were selected for further phylogenetic analysis based on the recA gene region. Results from the testing of over 3456 potato samples for plant health statutory purposes in years 2005–2017 demonstrated that Dickeya spp. is not the major pathogen causing soft rot or blackleg in Northern Ireland. The most predominant species causing soft rot of vegetables in Northern Ireland were Pectobacterium atrosepticum and Pectobacterium carotovorum subsp. carotovorum. Pectobacterium atrosepticum was also detected on hosts other than potato. Testing of bacteria isolated from carrots led to the detection of P. carotovorum and Dickeya sp. This is the first study to provide knowledge about Pectobacterium and Dickeya spp. diversity causing soft rot of vegetables in Northern Ireland confirmed by real-time PCR and DNA sequences. This is also the first report of the detection of D. aquatica from a source other than water.

Introduction
Soft rot Pectobacteriaceae (SRP; formerly soft rot Enterobacteriaceae) include the genera Pectobacterium and Dickeya (Adeolu et al. 2016) and are widespread globally (Bhat et al. 2010;Mansfield et al. 2012). SRP causes high loses particularly in potato production, estimated in the Netherlands at up to €30 million annually (Toth et al. 2011) with potential global losses of up to 30% (Agrios 2007) at an estimated cost of US$50-100 million every year in vegetables, fruits and ornamental plants (Pérombelon and Kelman 1980;Pérombelon 2002;Ma et al. 2007).
Previously known as Erwinia species (Winslow et al. 1920), the taxonomic reclassifications based on genetic differences within this genus led to the recognition of the genus Pectobacterium (Hauben et al. 1998) which was later separated into Pectobacterium and Dickeya (Samson et al. 2005). Pectobacterium currently includes ten formally described species and three subspecies (Gardan et al. 2003;Nabhan et al. 2013;Khayi et al. 2016) with several recently described species including Pectobacterium polaris (Dees et al. 2017b), Pectobacterium peruviense (Waleron et al. 2017), Pectobacterium punjabense (Sarfraz et al. 2018), Pectobacterium zantedeschiae (Waleron et al. in press) and Candidatus Pectobacterium maceratum (Shirshikov et al. 2018) being proposed. The genus Dickeya currently includes eight species and two subspecies (Samson et al. 2005;Brady et al. 2012;Parkinson et al. 2014;Tian et al. 2016). Recently, a number of reports have shown Dickeya solani and Pectobacterium carotovorum subsp. brasiliense to cause high losses in Western Europe (Nunes Leite et al. 2014;de Werra et al. 2015;Toth et al. 2011;van der Wolf et al. 2017). Moreover, several studies have confirmed that Pectobacterium atrosepticum and Pectobacterium carotovorum subsp. carotovorum are some of the predominant causes of soft rot and/or blackleg in temperate regions (de Boer et al. 2012;Dees et al. 2017a;Waleron et al. 2013;Elphistone 2016a, b). Pectobacterium atrosepticum is mainly associated with potato blackleg and soft rot in temperate climates (Pérombelon 2002;Skelsey et al. 2018;Oztruk et al. 2018) but its occurrence might not be limited to potato, as it has been isolated from other hosts such as sunflower (Bastas et al. 2009) and pepper (Stommel et al. 1996). Pectobacterium carotovorum subsp. carotovorum has a broad host range, including but not limited to carrots, potatoes, cabbage, lettuce and onions across a number of climatic zones including Europe (Peltzer and Sivasithamparam 1985;Waleron et al. 2002;Pérombelon 2002;Gardan et al. 2003;Toth et al. 2003;Crowhurst and Wright 1998;de Haan et al. 2008;van der Merwe et al. 2010;Cariddi and Sanzani 2013;Onkendi and Moleleki 2014;Moretti et al. 2016;Dees et al. 2017a;Naas et al. 2018;Oztruk et al. 2018). Dickeya spp. have been confirmed as the most destructive pathogens in terms of losses in Switzerland (Toth et al. 2011;Golanowska and Łojkowska 2016). The species Dickeya dianthicola is recommended for regulation as a pest in the European and Mediterranean Plant Protection Organisation (EPPO) (A2 pathogen; EPPO 2017). Therefore several countries have introduced national legislation to prevent the introduction of this species. In the UK, both Scotland and Northern Ireland have a 'nil' tolerance for Dickeya spp., and Northern Ireland has a 'nil' tolerance for Pectobacterium spp. (termed Bblackleg^) in pre-basic seed potatoes production and up to 1% tolerance for Pectobacterium spp. in basic seed potatoes (Anonymous 2010;Anonymous 2016).
The island of Ireland (Ireland and Northern Ireland) has a favourable climate for potato growing, with moderate temperatures, high humidity and a geographic location influenced by the Atlantic Ocean which restricts aphid populations and results in low levels of aphid-borne potato viruses (Proudfoot and Mccallum 1961). However, these conditions are also optimal for the spread of SRP (Pérombelon 2002). In Northern Ireland, potato is the second most important field crop after cereals (barley, wheat and oats) valued in 2017 to £23.8 million (Anonymous 2017). Overall, little is known about the diversity of SRP populations in Northern Ireland. Early observations indicated that blackleg disease may have been present in potato crops in Ireland as early as 1845 (Bourke 1966), with the first isolation of the putative organism Pectobacterium atrosepticum (listed as Bacillus melanogenes) by Pethybridge and Murphy (1911). Pectobacterium atrosepticum (recorded as Erwinia carotovora subsp. atroseptica) and P. carotovorum (recorded as Erwinia carotovora) have been recorded in Northern Ireland (Logan 1968;O'Neil and Logan 1975;Hossain 1986). Pectobacterium atrosepticum causing blackleg was listed as a large threat potato production in Northern Ireland by Logan et al. 1987. The presence of other species and subspecies of Pectobacterium in potato and other vegetables is unknown. Given the significance of potato and other vegetable (carrot and onion) production in Northern Ireland, with the total annual output of up to £42.5 million (Anonymous 2017), and the potential losses from SRP, the aim of this study was to investigate the diversity of Pectobacterium present in Northern Ireland and provide the first up to date report for over 30 years.

Sample collection
Symptomatic and asymptomatic potato samples, and water samples from potato processing facilities are submitted to the Agri-Food and Biosciences Institute (AFBI) for detection of plant pests and pathogens on behalf of the Department of Agriculture, Environment and Rural Affairs (DAERA). These statutory samples are tested for the regulated bacterial potato pathogens Clavibacter michiganensis subsp. sepedonicus, Ralstonia solanacearum, and Dickeya spp. During the years 2005-2017, 3456 statutory samples of symptomatic and asymptomatic material were tested for C. michiganensis subsp. sepedonicus, R. solanacearum with samples also tested for Dickeya spp. from 2010 onwards.
To investigate Pectobacterium diversity in Northern Ireland, in the years 2015 and 2016 a total 454 of these samples showing soft rot or blackleg symptoms were further analysed as part of this research. To supplement this data, a field survey was carried out in 2017 in four locations in Co. Londonderry and Co. Down in Northern Ireland. During this survey, potato samples with symptoms of blackleg were collected and tested for the presence of SRP. Carrots and onions grown in Northern Ireland were sourced from local growers and/or from local shops in Co. Down, Co. Antrim, Co. Armagh and Co. Londonderry and were also tested for SRP.

Preparation of samples from asymptomatic potato tuber extracts
Prior to analysis for detection of Dickeya spp. from statutory samples by real-time PCR with the specific primers ECH and/or SOL, DIC (Pritchard et al. 2013), potato extracts were prepared using the methodology adapted from Commission Directive 2006/63/CE for the control of R. solanacearum (Anonymous 2006). In brief, two hundred cores (5 mm) obtained from the stolon end of potato were transferred to a macerating container and 40 mL of macerating buffer containing Na 2 HPO 4 (4.26 g), KH 2 PO 4 (2.72 g) per litre was added, followed by 2 min of maceration at low speed in a homogeniser. Macerated samples were filter through a single layer muslin into a beaker. The filtrate was transferred into a centrifuge tube and centrifuged (200 rpm, 4-10°C) for 10 min. The obtained supernatant was poured into a clean centrifuge tube and centrifuged (11,000 rpm, 4-10°C) for 15 min. The supernatant was discarded and the pellet suspended in 1.5 mL of pellet buffer containing Na 2 HPO 4 (2.7 g), NaH 2 PO 4 (0.4 g) per litre. The sample was then enriched in pectate enrichment medium (PEM) in compact workstations for anaerobic and microaerophilic conditions for detection of Dickeya spp. for 48 h at 37°C (Anonymous 2010c).

Isolation of SRP strains from symptomatic samples
A modified double layer crystal violet pectate (CVP) media was used for detection and isolation of SRP. The agar was prepared using a modification of the method previously reported by Bdliya et al. (2004) which exc l u d e s b r o m t h y m o l b l u e a n d 2 , 3 , 5triphenylterrazolium chloride and with the inclusion of Dipecta (Agdia-Bioford) as the pectate source. For the rotting vegetables, samples were taken from the macerated tissues about 1 cm inside the surface using a sterile scalpel, suspended in 10 ml of sterile water and vortexed for 5 min at 10x speed. A total of 100 μl of plant material extract was streaked onto a CVP agar plate, followed by streaking the same hockey stick on five subsequent platesthus providing a dilution series of plates. The plates were incubated for 48 h at 28°C for detection of Pectobacterium spp. and for 48 h at 37°C for detection of Dickeya spp. from statutory samples after which they were assessed to determine the number of cavity or pit forming bacterial colonies of pink to red colour and with rod-shaped cells. Bacterial colonies that matched these characteristics were aseptically streaked onto nutrient agar (NA) plates (Oxoid) and incubated for 48 h at 25°C to obtain pure cultures.

DNA extraction and molecular detection
For DNA extraction, bacterial cultures grown on NA were transferred into the lysis buffer of the Maxwell®16 cell LEV DNA Purification kit (Promega) following the manufacturer's instructions. A number of samples of extracts of asymptomatic potato were also lysed using the procedure above. Bacterial DNA were purified for 30-45 min using a Maxwell DNA Magnetic Particle Processor MX 3031 (Promega) using the cell purification program. DNA extracts were quantified using a NanoDrop 2000 (Thermo Scientific), and the concentrations of bacterial DNA extracts adjusted to between 10 and 20 ng. Purified bacterial DNA were stored at −20°C until further analysis.
Amplification of the RecA multifunctional protein from the bacterial DNA extracts obtained was performed using primers EC-RecAR & EC-RecAF (Waleron et al. 2002). DNA amplification was performed in a 12.5 μL reaction mixture comprising GoTaq PCR Mastermix (6.25 μL), genomic DNA from bacterial culture ca. 10-20 ng (0.5 μL), primers (10 μM 0.50 μL), Nuclease-free H 2 O (Qiagen) (4.75 μL). Amplification conditions were as follows: DNA was initially denatured at 95°C for 5 min, followed by 32 cycles of denaturation 94°C for 60 s, annealing at 47°C for 60 s, and extension at 72°C for 5 min and the final extension at 72°C for 5 min. The procedure was carried out using a Life Pro Thermocycler (Bioer) RecA program for 2 h 42 min. The obtained PCR products were visualised using QIAxcel Advanced System (Qiagen). DNA extracts that amplified with RecA primers, and had a PCR product of 700-1000 bp were sent for sequencing.

Phylogenetic analysis and pairwise comparison
Sequencing of PCR amplicons was performed by a commercial sequencing service at Queens University Belfast Genomics Core Technology Unit using an Applied Biosystems 3730 (Thermo Fisher Scientific). The obtained sequences of the forward and reverse strands were assembled, aligned and trimmed using Geneious version 10.1.3 (Biomatters) software and compared using Basic Local Alignment Search Tool (BLAST) analysis with sequences available in GenBank (Altschul et al. 1990). The obtained sequences of Pectobacterium and Dickeya spp. were deposited in GenBank under following accession numbers: Obtained sequences (Table 1) were analysed for the species within the genus Pectobacterium and Dickeya spp. from across Northern Ireland by further phylogenetic analysis. Multiple alignment of the sequences was performed using CLC Main Workbench 8.0 (Qiagen) with reference sequences obtained from GenBank (National Centre of Biotechnology Information) i.e. P. atrosepticum (AY264783, KF704802), P. c. subsp. carotovorum (AY264799, AY264798, KY067403, MF314822) P. c. subsp. brasieliense (KP762587, KP762588), P. c. subsp. odoriferum (KF704811, KF704807), P. wasabiae (KC584992, KC584995 and AY264796), D. aquatica (JX273703), D. zeae (KY817909) and Candidatus P. maceratum (MK024779). Phylogenetic trees were generated using the Neighbor-joining method (Kimura 1980) using CLC Main Workbench 8.0 software. Bootstrapping was executed with 1000 replications. The bootstrap values <50% were excluded.
The multiple alignments were tested on five different models prior to construction of the tree to find the bestfit model for the final phylogenetic tree by the hierarchical likelihood ratio test (hLRT) and Bayesian Information Criterion (BIC). Both tests showed Kimura 80 as the best-fit model, thus a neighbour-joining tree was constructed based on that model (Fig. 1). The pairwise comparison of obtained multiple alignment was constructed (Tamura et al. 2004) based on percentage identity of Northern Irish strains with reference sequences obtained from GenBank using CLC Main Workbench 8.0 software.

Results
Statutory samples from asymptomatic and symptomatic potato tubers in Northern Ireland for Dickeya spp.
More than 3456 potato samples were tested for regulated bacterial pathogens between the years 2005-2017, 1891 originating in Northern Ireland and 1565 originating from other countries. Of these, Dickeya spp. were not detected in potato samples originating in Northern Ireland. Clavibacter michiganensis subsp. sepedonicus and R. solanacearum were not detected in any samples (Table 2). From 454 samples tested, 164 samples from potatoes, carrots and onions originated from Northern Ireland were tested in years 2015-2017, using real-time PCR, conventional PCR and DNA sequencing. From all samples, 164 were confirmed as members of the genera Pectobacterium or Dickeya (Table 3). Pectobacterium atrosepticum was identified in 101 samples collected from vegetables between 2015 and 2017 (Table 3). Over the three years of sampling, P. atrosepticum was the most frequent species isolated from potato (97), also three from carrots and one from onion were confirmed with real-time PCR. Pectobacterium carotovorum was confirmed from twelve samples (Table 3). In Co. Down this species was identified in 83% of samples collected from carrots and onion, and in Co. Antrim 17% from

Phylogenetic analysis
Phylogentic analysis was carried out on a panel of 33 strains (Table 1), previously identified by BLAST as P. atrosepticum (23), P. c. subsp. carotovorum (9), and D. paradisiaca (1). These strains grouped separately into three main clusters corresponding to P. atrosepticum, P. carotovorum and Dickeya spp. (Fig. 1). Pectobacterium carotovorum grouped into four main clusters: three isolates from carrots with P. carotovorum subsp. carotovorum strain (MF314822) and one carrot isolate in separate cluster with new proposed species of Candidatus P. maceratum (MK024779). Furthermore, three of the Northern Irish strains isolated from carrots (D0346, D0347 and D0348) and two potato isolates grouped in a separate clusters. Northern Irish P. atrosepticum strains constituted the cluster with the most similar in BLAST analysis type of P. atrosepticum strain (KY067402) and one grouped in a separate sub-cluster with strains of type P. atrosepticum ( AY217079, AY264784 and KF704802). Two of the Northern Irish strains Ca3A and Ca3B were grouped with the type strain of D. aquatica (JX273703) and D. zeae (KY817909) in the Dickeya cluster of Pectobacterium spp. phylogeny (Fig.1).

Discussion
In recent years, an increasing number of studies have detected Dickeya spp. in potato production in Europe (Toth et al. 2011;Potrykus et al. 2016). However detection of Dickeya spp. in countries that have implemented control programmes and legislation, such as Scotland and Norway is mostly linked to imported plant material Dees et al. 2017a). In this study, detections of Dickeya spp. from statutory potato samples in years 2005-2017 in Northern Ireland were very rare and always linked to imported plant material. Moreover, so far Dickeya spp. have not been detected from potato grown in Northern Ireland analysed as statutory samples. This work therefore focused on investigating the diversity of Pectobacterium spp. rather than Dickeya spp. and samples obtained from field survey were not enriched at temperatures higher than 28°C. As demonstrated by Potrykus et al. (2016), Pectobacterium spp. can overgrow Dickeya spp. during isolation at lower temperatures; however, Dickeya may have been present at low concentrations. Two isolates from carrots in this study (Ca3A and Ca3B) showed high similarity to D. aquatica. Separate analysis has attributed these two Northern Irish strains to the SLC 2 clade defined by Parkinson et al. (2014) in the Dickeya cluster in a separate phylogeny of Dickeya spp. with a high bootstrapping value (Supplementary Fig. 1).  In 2008/09, a Dickeya sp. was isolated from water sources in Finland and Scotland which constituted a new clade SLC 2 which shows genetic differences to the known species of Dickeya (Laurila et al. 2008;Parkinson et al. 2009). Further work differentiated this new clade as a new species: D. aquatica . Research has shown that D. aquatica from water sources can cause rotting symptoms on potatoes in lab trials, but was not particularly virulent (Laurila et al. 2008(Laurila et al. , 2010. This study is the first to isolate D. aquatica from diseased plants in the field. The presence of this pathogen in Northern Ireland and its relation to soft rot symptoms is not well understood. Although samples were collected from symptomatic carrots, the irrigation water source (a local river in Northern Ireland) cannot be excluded as the source of contamination which could allow transmission to other hosts and constitute a potential threat in potato production regions. This pathogen may also be a recent introduction. This is an area where further research is needed.
Pectobacterium atrosepticum was the most frequently detected Pectobacterium species detected during surveys 2015-2017. This study builds on previous studies in Northern Ireland (Logan 1963(Logan , 1968O'Neil and Logan 1975;Hossain and Logan 1983;Logan 1986, 1987;Wastie et al. 1988;Gans et al. 1991) and Ireland (Buttimer et al. 2018). The native range of Pectobacterium atrosepticum is unknown, however, the pathogen has potentially been causing blackleg in Ireland for over 100 years (Pethybridge and Murphy 1911;Bourke 1966). Similar to our findings, P. atrosepticum was also the most frequently detected species in temperate climates including Canada (de Boer et al. 2012), Norway (Dees et al. 2017a) and UK (Elphistone 2016a, b;Toth et al. 2016). In Scotland, most blackleg disease was caused by P. atrosepticum Toth et al. 2016). In a seed potato survey between 2013 and 2015 in England, Wales and Scotland, P. atrosepticum constituted 89.4% of all positive samples (Elphistone 2016a). In the UK, 17 haplotypes of P. atrosepticum have been confirmed to be present, including testing of some strains from the 1930s (Elphistone 2016b). Within P. atrosepticum isolates from Northern Ireland, high genetic homogeneity occurred with high identity values (99.06-100% in pairwise comparison) to strain P. atrosepticum (KY067402) (Supplementary Fig. 2). High homogeneity of P. atrosepticum has also been found previously by Dees et al. (2017a).
Pectobacterium carotovorum subsp. carotovorum was recorded in Northern Ireland previously (Logan 1963(Logan , 1966(Logan , 1984Hossain 1986). Logan (1963Logan ( , 1966 reference to Erwinia carotovora and Erwinia carotovora pv. 'aroideae' probably correspond to Pectobacterium carotovorum subsp. carotovorum and not Pectobacterium aroidearum, which is primarily a pathogen of monocotyledonous hosts (Nabhan et al. 2013) and most recently has been detected from potatoes (Moretti et al. 2016) and zucchini (Moraes et al. 2017). However, its presence has not been confirmed in phylogenetic analysis (data not shown). The P. carotovorum population in Northern Ireland was more heterogeneous than P. atrosepticum based on serological grouping (Hossain 1986), and our phylogenetic analysis agrees with this findings. Two of isolates from potatoes (SR22 and C2558) and three of the carrot strains (D0346, D0347 and D0348) grouped separately from others P. c. subsp. carotovorum and formed a separate clusters in the phylogenetic analysis (Fig.1). Further research including the analysis of more gene regions is needed to clarify the identities of these SRP. The use of more molecular markers, and a wider range of isolation methods (e.g. different temperatures), as suggested by Czajkowski et al. (2015), would likely reveal the presence of more diversity within and between the species of SRP detected in Northern Ireland, and build upon the research presented here.
In previous studies, Pectobacterium carotovorum strains originated from Ireland and Scotland were reclassified by Nabhan et al. (2013) and Waleron et al. (2013) as P. wasabiae. In this study, P. wasabiae was not detected. One isolate (from rotting carrot D0349) ( Fig. 1) clustered together with the type strain of the proposed novel taxon Candidatus P. maceratum. Recently, this new genomospecies was described based on genomic distinction of five P. c. subsp. carotovorum strains and showed the most genetic similarity to P. c. subsp. odoriferum (Shirshikov et al. 2018). Work performed by Li et al. (2018) through whole genome sequences of 84 isolates of SRP shows high genetic similarity of Candidatus P. maceratum to P. carotovorum and P. polaris. Moreover, through phylogenetic analysis this species clustered together with other P. c. subsp. carotovorum suggesting than more isolates in GenBank might belong to this morphospecies (Li et al. 2018). Thus far, one study provides the details showing virulence and pathogenicity of Candidatus P. maceratum on potato and bittersweet (Waleron et al. 2019), therefore its aggressiveness regarding other vegetables is not known. This study demonstrated that Pectobacterium spp. originating from Northern Ireland might be more diverse and further research should be performed to confirm occurrence of this new species.
The presence of three species of SRP in association with soft rot symptoms of vegetables as confirmed by PCR methods and phylogenetic analysis in Northern Ireland. This is the first published record of Pectobacterium and Dickeya spp. from Northern Ireland confirmed by DNA sequencing. This is the first study to document a confirmed isolation of D. aquatica from a symptomatic plant host in the field. Further research is needed to clarify the identity, distribution, and pathology of this taxa.


s2fieldsofstudy:
Agricultural And Food Sciences
Environmental Science

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

text:
UV-B Exposure of Black Carrot (Daucus carota ssp. sativus var. atrorubens) Plants Promotes Growth, Accumulation of Anthocyanin, and Phenolic Compounds Müller, Renate; Acosta-Motos,

Black carrot (Daucus carota L. ssp. sativus var. atroburens) is a root vegetable with anthocyanins as major phenolic compounds. The accumulation of phenolic compounds is a common response to UV-B exposure, acting as protective compounds and as antioxidants. In the present study, black carrot plants grown under a 12-h photoperiod were supplemented with UV-B radiation (21.6 kj m−2 day−1) during the last two weeks of growth. Carrot taproots and tops were harvested separately, and the effect of the UV-B irradiance was evaluated in terms of size (biomass and length), total monomeric anthocyanin content (TMC), total phenolic content (TPC), and phytohormones levels. The results showed that UV-B irradiance promoted plant growth, as shown by the elevated root (30%) and top (24%) biomass, the increased TMC and TPC in the root (over 10%), and the increased TPC of the top (9%). A hormone analysis revealed that, in response to UV-B irradiance, the levels of abscisic acid (ABA), jasmonic acid (JA), and salicylic acid (SA) decreased in tops while the level of the cytokinins cis-zeatin (cZ) and trans-zeatinriboside (tZR) increased in roots, which correlated with an amplified growth and the accumulation of anthocyanins and phenolic compounds. Beyond the practical implications that this work may have, it contributes to the understanding of UV-B responses in black carrot.

Introduction
Domesticated carrot is a root vegetable of which the colour ranges from orange (Daucus carota L. ssp. sativus var. sativus) to purple or black cultivars (Daucus carota L. ssp. sativus var. atroburens), with anthocyanins as major secondary metabolites [1]. The main interest in black carrot anthocyanins is related to their high ratio of mono-acylated structures with three sugar moieties, which provide a high physicochemical stability to the colour extracts and make black carrot suitable for developing natural colourants (labelled E163 in Europe) [2]. In addition to anthocyanins, black carrot taproot is a rich source of non-anthocyanin phenolic compounds, mainly consisting of hydroxycinnamic acids and derivatives [3]. The content of phenolic compounds is highly correlated with the strong antioxidant activity of the taproot extract, which in turn is associated with the potential health benefits of black carrot in preventing cardiovascular and neuronal diseases, among other diseases [3,4]. Although at much lower concentrations than in the taproot, phenolic compounds are also present in carrot leaves [5].
Phenolic compounds act as non-enzymatic antioxidants, scavenging reactive oxygen species (ROS) and participating in the response to stress [6]. In this respect, the metabolism and accumulation of phenolic compounds increases under stress conditions such as wounding, pathogen attack, and UV radiation, among others [7,8]. Photoprotective roles of foliar phenolic compounds against UV-B radiation have received much attention in recent years. Because of its high energy, this short-wave band of the terrestrial solar spectrum causes damages to RNA, DNA, proteins, and lipids [9]. Consequently, plants accumulate UV-B-absorbing phenolic compounds in the epidermal layers of leaves and stems. Of all classes of phenolic compounds, flavonoids, particularly anthocyanins, are regarded as the main contributors to the UV-B screening capacity of the plant [10].
Although for the past few decades UV-B radiation was mainly regarded as a stressor [11,12], it now appears to have important regulatory roles in plants [13][14][15]. In this sense, while high UV-B doses are more often associated with detrimental effects, moderate and sub-lethal levels of UV-B have been associated with the stimulation of plant growth via specific signalling, leading to an acclimation state without evident signs of stress [14,16]. Until now, the effect of UV-B light has not been investigated neither in carrot in vivo nor in a black carrot variety.
As hormones are widespread in the regulation of plant metabolism and morphogenesis, they are also implicated in UV-B stress response and signalling, participating in systemic signalling networks that ultimately affects plant growth and development [14,17]. Likewise, hormones interact in controlling anthocyanin biosynthesis [18,19]. However, the study of phytohormone profiles in carrot has been limited to the flowering process in leaf tissue [20], and the molecular mechanisms underlying differential anthocyanin accumulation in the root in response to above ground stimuli remain unknown. In the present work, we studied for the first time the effects of a moderate dose of supplemental UV-B light on black carrot performance. The levels of phytohormones (abscisic acid, cytokinins, indole-3-acetic, jasmonic acid, jasmonic acid-isoleucine, and salicylic acid), total anthocyanins, and phenolic compounds were determined, establishing a comparison between the plant top and taproot. Taken together, this study increases the knowledge on black carrot phytochemical composition and physiology and contributes to the understanding of the physiological responses to UV-B light.

Plant Material and Cultivation
Seeds of black carrots (Daucus carota L. ssp. sativus var. atrorubens) of "Deep Purple" F1 (Bejo Seeds Inc., Oceano, CA, USA) were sown in 30-cm long cylindrical pots (18 cm in diameter) with 7.5 L of an equal mixture of garden soil and perlite (particle size 1-5 mm), which provided an adequate balance of air and moisture content around the taproot [21]. Ten sowing spots per pot were distributed, and three seeds were introduced in each one at one-cm depths. Pots (12 in total) were placed in a climate chamber under a 12-h photoperiod (350 µmol m −2 s −1 visible light) in a 20 • C day/18 • C night cycle. From ten days after sowing, 1 L 1/2 Hoagland solution was applied every 3 days until the end of the experiment. Fourteen days after sowing, two seedlings per spot were removed, leaving one vigorous plant per place.

UV-B Light Treatment
Twelve weeks after sowing, the aboveground parts of the carrots plants were treated with supplemental UV-B light (6 W m −2 s −1 radiation fluence rate) during 1 h per day (21.6 kj m −2 day −1 ), coinciding with the fifth hour of white light of the 12-h photoperiod provided by low irradiance UV-B lamps (Philips Broadband TL40W/12 RS, Eindhoven, The Netherlands) placed at a distance of ca. 1.2 m from the top of the plants. Radiation was measured using a RM-12 Ultraviolet Light Meter equipped with a UVB sensor (Opsytec Dr. Gröbel GmbH, Ettlingen, Germany).

Harvest, Sample Collection, and Processing
Fourteen days after the initiation of the UV-B light treatment (16 weeks after sowing), plants were harvested, washed, and carefully dried. The length and fresh weight (FW) of the top and taproot of each plant were registered. In the case of the top length, it corresponded to the length of the longest leaf. For further analyses, two types of samples were generated: (1) shoot samples, composed of the pool of leaves and stems of the 10 plants from a pot, and (2) root samples, composed of the corresponding 10 taproots. Subsequently, each combined sample (biological replicate) was ground in liquid nitrogen prior to storage of the resulting powder at −80 • C.

Determination of Total Monomeric Anthocyanin Content (TMC) and Total Phenolic Content (TPC)
Five grams of the powder generated above was homogenised in a 3% sulfuric acid solution (1/1, w/w) using a Waring ® two-speed commercial blender (VWR-Bie & Berntsen, Herlev, Denmark). The produced homogenate was then vigorously mixed either with (a) water (1/2, w/w) for the subsequent analysis of TMC or (b) 70% ethanol (1/2, w/w) for the later analysis of TPC. After 1 h of incubation at 25 • C, the sample was centrifuged for 20 min at 4500 rpm and the resulting supernatant was collected [1].
TMC determination was based on the pH differential method with minor modifications [1]; in brief, the supernatant extracted in water was diluted in a 0.2 M KCl-HCl (pH 1) solution (1/1, v/v), and the absorption was measured between 350 and 700 nm using a UV-visible spectrophotometer (Thermo Scientific Evolution™ 220, Waltham, MA, USA). The TMC was calculated as cyanidin 3-glucoside equivalents.
TPC was determined by the Folin-Ciocalteau method [22]. In brief, the supernatant extracted in 70% ethanol was mixed with the Folin-Ciocalteau reagent (1/5, v/v), followed by the addition of 20% (w/v) sodium carbonate (0.6/1, v/v). After incubation for 2 h in the dark, the absorbance was determined at 760 nm using a UV-visible spectrophotometer (Thermo Scientific Evolution™ 220). The TPC was then calculated as mg of gallic acid equivalent (GAE) per g of FW.

Statistical Analyses
The analyses were conducted with four to six biological replicates, each of them consisting of the pool of samples from one pot (10 plants). The data were subjected to a statistical analysis using the StatGraphics Centurion XV software (StatPoint Technologies, Warrenton, VA, USA). The treatments were compared using a one-way analysis of variance (ANOVA) followed by a Least Significant Differences post hoc test (p ≤ 0.05). The Pearson's correlation coefficient was calculated to measure the linear relationship between pairs of variables. A principal component analysis (PCA) followed by a partial least squares discriminant analysis was conducted to assign the principal components displaying eigenvalues greater than or equal to 1.0, which led to the identification of two principal components explaining 84% of the variation within the data set.

Results
In the present work, 12-week-old black carrot plants of "Deep Purple" F1 grown under visible light were subjected to a moderate dose of UV-B radiation concurring with a 12-h photoperiod. After 2 weeks, the plants were harvested, and the effect of the treatment was evaluated on tops and taproots in terms of size (weight and length) and phytochemical composition (total phenolic and anthocyanin contents and phytohormones levels).
Overall  Subsequently, the effects of UV-B irradiance on TMC and TPC were analysed (Figure 2). UV-B treatment increased TMC in tops by 10%, exhibiting mean values of 208 and 228 µg g −1 FW in untreated and UV-B-treated plants, respectively, although showing no significant differences. As expected, TMC in taproots was remarkably higher than in tops, with values of 1494 and 1694 µg g −1 FW in untreated and UV-B-treated plants, respectively, the latter being significantly higher (Figure 2a).
Similarly, TPC was higher in taproots (2309 and 2612 µg g −1 FW for untreated and treated plants, respectively) than in tops (337.7 and 370.3 µg g −1 FW for untreated and treated plants, respectively) ( Figure 2b). TPC of treated plants was significantly higher than that of control plants, increasing by 9 and 13% in tops and taproots, respectively (Figure 2b). The phytohormone analysis allowed the parallel quantification of eight different hormones (ABA, cZ, IAA, JA, JA-Ile, SA, tZR, and tZROG) from one single sample ( Figure 3). Two additional ones, MeJA and tZ, were not consistently measured in the two experiment repetitions and, therefore, considered as not detected under our experimental conditions. Regardless of treatment, the levels of certain hormones (IAA, JA, JA-Ile, and tZROG) remained higher in tops than in taproots, whereas others (ABA and tZR) displayed the opposite variation. Finally, the levels of SA, the most abundant hormone, were comparable in both organs, whereas cZ was not detected in tops (Figure 3). Regarding the comparison between treatments on carrot tops, hormone levels for ABA, IAA, JA, SA, and tZR decreased significantly upon UV-B treatment. In this respect, the highest variation corresponded to ABA and tZR, where the mean values dropped over 50% (from 0.47 to 0.23 and 0.041 to 0.020 pmol g −1 FW, respectively) in response to UV-B light treatment, followed by JA, of which the levels decreased by 46% upon UV-B light treatment, passing from 0.60 to 0.32 pmol g −1 FW (Figure 3a-c). Likewise, the mean value of IAA reduced from 2020 to 1351 pmol g −1 FW, which represents a 33.1% decrease (Figure 3d), and the levels of SA passed from 1574 to 1241 pmol g −1 FW (21% decrease) (Figure 3e). On the other hand, the levels of JA-Ile and tZROG remained statistically invariable between treatments on carrot tops (Figure 3f,g).
In roots, a distinct response was found; the cytokinins cZ and tZR increased in UV-B-treated roots with respect to untreated roots, whereas the rest of hormones remained unchanged in both treated and untreated roots. cZ, which was not detected in carrot tops, was found to increase by 50% upon UV-B light treatment, displaying values of 0.030 pmol g −1 FW, whereas the levels on control taproots remained at 0.019 pmol g −1 FW (Figure 3h). The levels of tZR for roots of UV-B treated plants (0.041 pmol g −1 FW) more than doubled those found on untreated roots (0.020 pmol g −1 FW) (Figure 3b).
In order to determine any association between variables, a correlation matrix was elaborated (Table 1), which denoted noticeable variations among them. The correlation of greatest magnitude was evenly displayed for TPC and length and for TMC and length (−0.98), followed by TPC and TMC (0.97), whereas coefficients between weight and TPC and between weight and TMC were 0.88 and 0.89, respectively; this indicates that, rather than length, weight is the main factor associated positively to the levels of TPC and TMC. With respect to hormones, TMC and TPC showed very similar positive (ABA) and negative (IAA, JA, JA-Ile, SA, cZ, tZROG, and tZR) correlations, which demonstrates that the higher TMC and TPC is, the lower the levels of most of the hormones are, and indicates the close association between TMC and TPC. Interestingly, length displayed similar correlation coefficients to TMC and TPC with regard to hormones but with the opposite sign. ABA, JA, and tZROG were the most relevant hormones for the establishment of correlations. Moreover, ABA displayed negative correlations to JA and tZROG. On the other hand, SA and cZ were the variables displaying fewer correlations.  Complementarily, PCA was utilised as a mathematical tool to determine associations between the hormonal and physiological (growth, TPC, and TMC) variables ( Figure 4). PCA resulted in a model with two principal components (PCs) explaining 84% of the total variance ( Figure 4). The first PC accounted for 75%, whereas the second explained 9% of the variance. Two main groups of variables could be easily distinguished from left to right in PC1, showing the loadings for TMC, TPC, weight, ABA, and cZ clustered in one group and length and the hormones IAA, JA, JA-Ile, and tZROG grouped in the opposite direction with a similar magnitude, which is related to the higher abundance of the levels of the first and second groups in roots and tops, respectively (Figures 1-3). Concerning PC2, two variables, SA and tZR, appeared as the dominant loadings while not showing a relevant contribution to PC1.

Discussion
Numerous publications refer to UV-B-derived physiological and phenotypic changes. These reports are diverse and often show opposite effects, which likely reflect the heterogeneity of experimental conditions and plant material. Moreover, the ecological relevance of the UV treatment has to be taken into consideration in order to distinguish between UV-stress response and acclimation effects [25,26]. In the present study, a positive effect of a moderate dose of UV-B irradiance on black carrot performance was achieved. Such an effect was reflected in increased top and root growth and an enhanced accumulation of anthocyanins and phenolic compounds. These changes were associated with changes in the phytohormone profiles of roots and tops, which may cause an improved physiological status, driving growth and anthocyanin accumulation.
A common response to UV light exposure is the increased accumulation of phenolic compounds [27]. The mechanism underlying UV-B perception and the accumulation of photo-protectant phenolic compounds is quite studied in aerial parts of plants [10,[28][29][30]. Moreover, phenolic compounds display antioxidant roles acting as direct scavengers of reactive oxygen species (ROS) [29]. At the cellular level, UV-B irradiance initially triggers ROS formation, which subsequently increases the biosynthesis of certain phenolic compounds, as part of the non-enzymatic antioxidant defences [26,31,32]. This phenomenon would explain the accumulation of these compounds in non-exposed tissues to UV-B, as observed in maize roots [33]. In fact, low UV-B doses increased the flavonoid content in leaves and roots of nasturtium [34] and kale [35], which indicates that UV-B may act as a systemic inducer of phenolic contents in the whole plant. Likewise, in our study, although UV-B resulted in a significant increase of TPC in tops, its effect was more evident in roots, where both TMC and TPC increased by 13% (Figure 2). This effect may be based on shoot-root signalling events indirectly leading to the accumulation of root phenolics. Moreover, the fact that sampling was not limited to the leaf portions directly exposed to the UV-B light can explain the lower accumulation of phenolic compounds in tops.
A second frequent effect of UV-B irradiance on plant physiology is a decrease in biomass [26]. Such an effect relies on the biosynthesis costs of flavonoids and related phenolic compounds, which are generally higher than those of biomass [36]. Conversely, several authors have reported an increased plant biomass in response to moderate UV-B doses in faba bean [33], radish [37], and Arabidopsis [38]. A similar response was found in our work, where both top and root weights increased upon treatment (Figure 1). It can be hypothesised that, given the extraordinary high concentration of anthocyanins and, in general, of phenolic compounds of black carrot roots, the possible oxidative stress following UV-B light exposure would be attenuated by plant defence mechanisms to an extent that no deleterious effects were detected under our experimental conditions. UV-B interferes with hormonal metabolism and transport [39,40]. Overall, among hormones, IAA, cytokinins, and GAs act by promoting plant growth, whereas JA, ABA, and SA inhibit it [38,39]. In agreement with this, in the present study, the levels of the growth-inhibiting hormones ABA, JA, and SA decreased in the tops of treated plants, while the growth-promoting cytokinins cZ and tZR increased in roots (Figure 3), a response that correlated with the increases in top and root growth (Figure 1c). These modulations may indicate that UV-B radiation aboveground promoted carrot growth through signaling events that trigger cytokinin (cZ and tZR) accumulation in the root. In this sense, decreasing cZ levels caused a reduced root growth in Arabidopsis and rice [41][42][43], which indicates an active role of cZ in promoting root growth.
In contrast, the levels of IAA notably decreased in treated plants, which may be linked to the inhibition of auxin biosynthesis by UV-B, as reported [44]. UV-B may induce the isomerization of ABA to 50% trans, trans and 50% cis, trans [40,45], the latter being the active form; consequently, in tissues where UV-B penetrates, the amount of active ABA may be negatively affected. Among cytokinins, zeatin and its derivatives are the most important group of isoprenoid cytokinins. Although cZ has been generally reported as scarcely active compared to its trans-isomer, recent studies assign physiological functions to this hormone [46]; interestingly, cZ was quantifiable only in root samples, with its levels lower in UV-B-treated plants. Inactive forms of cytokinins are abundant and serve as a reservoir [47]. In this sense, tZROG, a conjugated inactive form of cytokinin, displayed values an order of magnitude higher than those for cZ and tZR in this study.
On the other hand, UV-B typically induces JA and SA, as stress-responsive hormones [40,48], which is contradictory to our findings, where the levels of both hormones decreased in the tops of treated plants. Considering that plants were UV-B treated for 14 days before harvest and sampling, a distinct JA and SA modulation during the first days of treatment cannot be discarded, which at the end of the experiment-likely involving an acclimation response-led to the hormone levels found in this study.

Conclusions
Collectively, we can assert that moderate UV-B irradiance on black carrot may act simultaneously to induce valuable secondary metabolites accumulation and plant growth. The analysis of the hormones profile-which is supposed as the first study conducted on black carrots-reveals noticeable changes upon UV-B-treatment and sheds light on the regulation of phenolic compounds in the root/ Beyond the practical implications that this work may have regarding the utility of UV-B on anthocyanin production, it represents a stepping-stone towards the understanding of UV-B regulation and stress in black carrot.

Conflicts of Interest:
The authors declare no conflict of interest.


text:
Germination Ecology of Brachiaria eruciformis in Australia and Its Implications for Weed Management

: Brachiaria eruciformis (Sm.) Griseb. is a noxious weed of Australia and other parts of the world. The e ﬀ ects of di ﬀ erent environmental conditions on the seed germination and seedling emergence of three biotypes sourced from di ﬀ erent cropping systems (mungbean ﬁeld, sorghum ﬁeld, and fenceline) of this weed were evaluated. There were no di ﬀ erences in the response of biotypes to the evaluated factors; therefore, the data was pooled across the biotypes. The highest germination rate was observed at 30 / 20 ◦ C, and seeds germinated both in light and dark conditions. Seed germination was inﬂuenced by di ﬀ erent sodium chloride (NaCl) concentrations and water potentials, and no seeds germinated at 200 mM NaCl and − 0.8 MPa water potential. Seeds germinated ( > 70%) at a broad range of pH, from 4 to 10. Compared with seeds sown on the soil surface, a burial depth of 4 cm reduced the seedling emergence by 84%. Similarly, a sorghum residue amount of 4 t ha − 1 on the soil surface reduced the seedling emergence by 65%, compared with no sorghum residue cover. No seedlings emerged from seeds buried at 8 cm depth and > 4 t ha − 1 sorghum residue. This study suggests that burying seeds deep into the soil through tillage or employing a residue cover on the soil surface can reduce B. eruciformis emergence.

Introduction
Brachiaria eruciformis (Sm.) Griseb. [synonym = Moorochloa eruciformis (Sm.) Veldkamp or Panicum eruciforme Sm.; sweet summer grass or sweet signal-grass] is a noxious weed affecting cropping agricultural productivity in the tropic and subtropic zones of Africa, Americas, Asia, Australia, and some parts of Europe [1][2][3][4][5][6]. It is an annual grass belonging to the Poaceae family, which can be easily identified due to its red-purple leaf margins and leaf sheaths. This plant grows up to 60 cm high with a green leaf blade and simple and alternate leaves that are 10-15 cm in length. The small clump of this weed is slightly hairy and cylindrical [7][8][9].
Brachiaria eruciformis is spreading in the northern grain and cotton region (Queensland and New South Wales) of Australia [10], with a greater prevalence in central Queensland. Although a summer-dominant weed, this weed is often present in the late phase of winter crops and both in summer and winter fallows. It occurs in both cereals, particularly sorghum (Sorghum bicolor L.), and cotton (Gossypium hirsutum L.) systems [2,10]. This weed is a more significant problem in dryland cotton than in irrigated cotton [10].
Prolific seed production (>100,000 seeds plant −1 ), a short generation time with multiple cohorts in a season, and a high level of competitiveness are the main factors leading to the evolution of this species as a major weed [10]. In addition to competing with crops, it can develop a thick grass mat and interfere with harvest operations [7][8][9]. In 2011, this weed was rated as the number one weed with the potential to evolve resistance to the herbicide glyphosate [10] and has since developed resistance in some populations [11]. Despite a wide distribution of B. eruciformis in the northern region of Australia and its occurrence as a herbicide-resistant weed [2,10,11], there is a lack of comprehensive knowledge on the management of this weed based on its germination biology. In terms of revenue loss, B. eruciformis is ranked the third weed in the northern grain region of Australia, accounting for a revenue loss of AU$ 8.8 million annually, due to its prevalence in grain crops and fallows [12].
Weed adaptation to environmental conditions could be attributed to genetic diversity in weed populations that allows them to invade new areas [13,14]. Plants often adapt to habitat conditions such as temperature, water availability, light, and soil salinity. These conditions are the prime factors that decide weed germination, emergence, and establishment [15]. In addition, tillage and the presence of mulch on the soil surface are some of the management-driven aspects affecting weed germination and emergence [15][16][17]. Identifying the response of a weed species to burial or residue cover provides useful information for framing weed management options [15][16][17]. In many weeds, tillage leads to the burial of seeds deep into the soil, where emergence is inhibited [16]. Similarly, mulch application may also reduce the germination of photoblastic weed seeds by decreasing the availability of light [17]. A deeper understanding of how the maternal environment, human activity, and genetic diversity affects weed germination could help in developing accurate and reasonable management strategies to minimize the effect of weeds on crops and in predicting invasions in new areas.
Crop management affects the germination response of weeds [18,19]. For example, weeds maturing at the crop boundary seldom receive any tillage, fertilizer, or irrigation compared to those in crop fields. Such differences in management practices may select for changes in the germination characteristics of weed seeds [18][19][20][21] and need to be accounted for while making weed management decisions based on their germination ecology.
In this study, three biotypes of B. eruciformis were evaluated for their response to a range of environmental conditions so as to frame appropriate weed management options to suppress the further prevalence of this weed.

Seed Collection
Mature seeds were collected in April 2018 from a sorghum field (27.56 • S, 152.34 • E), a mungbean field at Lawes (27.54 • S, 152.33 • E), and a field boundary from Forest Hill (27.59 • S, 152.37 • E) in the Queensland region. Seeds were collected by shaking mature plants over trays, were then cleaned and then stored in ambient conditions until the start of the experiment. Before starting the experiments, the seeds were cleaned again and X-rayed (Faxitron seed X-ray unit) to ensure that all seeds were filled ( Figure 1A-C). Some species from the Brachiaria genus, including this one, have a hard coat [22]; therefore, seeds were scarified uniformly by spreading on a wooden table and by rubbing three times (10 cm up and down) using sand paper to break the physical seed dormancy. Germination improved after scarification ( Figure 2).  Effect of scarification with sand paper on the seed germination of Brachiaria eruciformis. Each bar of the graph represents a mean value of germination data (pooled across biotypes) as no significant differences were observed among biotypes. The vertical bar shows the least significant difference (LSD) values at the 5% level of probability.

Common Procedure
Experiments were conducted in 2018 to examine the effect of environmental factors on the seed germination of three biotypes of B. eruciformis in the weed science laboratory of Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Gatton, Australia. Twenty-five seeds were placed in 9-cm diameter Petri dishes on top of two layers of sterilized filter paper and moistened with water or other appropriate experimental solutions. Except for the temperature and light experiments, all experiments were conducted in an incubator set at 30/20 °C   Effect of scarification with sand paper on the seed germination of Brachiaria eruciformis. Each bar of the graph represents a mean value of germination data (pooled across biotypes) as no significant differences were observed among biotypes. The vertical bar shows the least significant difference (LSD) values at the 5% level of probability.

Common Procedure
Experiments were conducted in 2018 to examine the effect of environmental factors on the seed germination of three biotypes of B. eruciformis in the weed science laboratory of Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Gatton, Australia. Twenty-five seeds were placed in 9-cm diameter Petri dishes on top of two layers of sterilized filter paper and moistened with water or other appropriate experimental solutions. Except for the temperature and light experiments, all experiments were conducted in an incubator set at 30/20 °C Figure 2. Effect of scarification with sand paper on the seed germination of Brachiaria eruciformis. Each bar of the graph represents a mean value of germination data (pooled across biotypes) as no significant differences were observed among biotypes. The vertical bar shows the least significant difference (LSD) values at the 5% level of probability.

Common Procedure
Experiments were conducted in 2018 to examine the effect of environmental factors on the seed germination of three biotypes of B. eruciformis in the weed science laboratory of Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Gatton, Australia. Twenty-five seeds were placed in 9-cm diameter Petri dishes on top of two layers of sterilized filter paper and moistened with water or other appropriate experimental solutions. Except for the temperature and light experiments, all experiments were conducted in an incubator set at 30/20 • C day/night temperature and a 12 h photoperiod. Further details on the temperature and light experiments are below. Seeds with a 2-mm radical were considered germinated, and the germination assessment was continued up to 28 days. Experiments were repeated after completing the first run.

Temperature and Light
Five alternating day/night temperatures (15/5, 20/10, 25/15, 30/20, and 35/25 • C) in two light regimes [12 h photoperiod and complete darkness (24 h)] were used to determine the effect of temperature and light on germination. To avoid the penetration of light to seeds in the continuous dark treatment, Petri dishes were wrapped with three layers of aluminum foil. For the dark treatment, the seed germination counted only after 28 days.

Burial Depth and Sorghum Residue Amount
Pots of 10 cm diameter × 12 cm height (1 L) were used to determine the effect of the sorghum residue amount and burial depth on the seedling emergence. The soil used in this experiment was collected from the Gatton Research Farm of the University of Queensland and had a pH of 7.1, organic matter of 2.4%, nitrogen of 34 mg kg −1 , phosphorus of 214 mg kg −1 , and potash of 410 mg kg −1 . To avoid the background seed bank of B. eruciformis, the soil was sieved and dried (100 • C) in an oven for 96 h. The selected burial depths were 0 (soil surface), 0.5, 1, 2, 4, and 8 cm. The sorghum residue was prepared by chopping (2 cm pieces) mature sorghum plants (cv. MR Bazley) and placing the chopped pieces in an oven at 70 • C for 96 h. To examine the effect of the sorghum residue amount, seeds were placed on the soil surface and covered with dry sorghum crop residue at equivalent rates of 0, 4, 8, 16, and 32 t ha −1 . Fifty seeds per pot were used, and the pots were placed in an incubator set at 30/20 • C and sub-irrigated. Emerged seedlings were counted at a weekly interval over 28 days.

Statistical Analyses
All experiments were conducted twice. The data was pooled as there was no interaction between the experimental runs and treatments. A completely randomized design (Factorial = biotype × treatment) with three replications was used for all tests. Before analyzing (ANOVA) (SAS software v. 9; SAS Institute, Cary, NC, USA) each experiment, the normality and homogeneity of variance (Shapiro-Wilk test) were tested, and no transformation was needed. For all treatments, the seed germination data was pooled across the biotypes, as no significant difference was observed among the biotypes (n = 18). The effects of the scarification, temperature and light, pH, burial depth, and sorghum residue on the germination of B. eruciformis were determined using the least significant difference test (LSD, p ≤ 0.05). A three-parameter sigmoid model was used to describe the seed germination (%) at different water potentials (Equation (1)): In this equation, G (%) is the germination (%) at water potential X, Gmax is the maximum germination (%), X50 is the water potential that caused a 50% reduction in the seed germination, and b is the slope.
A three-parameter logistic model (Equation (2)) was used to model the salinity data following this equation: where G (%) is the germination (%) at NaCl concentration X, Gmax is the maximum germination (%), X50 is the concentration of NaCl for a 50% inhibition of germination, and b shows the slope.

Scarification
A poor germination (<15%) was obtained in the control (no-treatment) condition ( Figure 2). The germination improved (p < 0.001) by physical scarification. No difference was observed among the biotypes in response to the seed scarification.

Temperature and Light
The seed germination was significantly (p < 0.001) affected by alternating the temperature and light conditions, and their interaction produced a significant effect on the germination of B. eruciformis (Figure 3). There were no significant differences among the biotypes. Seed germination was not observed at 15/5 • C day/night temperature. The lowest germination was observed at 20/10 • C, and germination was the greatest at day/night temperatures of 30/20 • C. Germination increased with an increasing temperature from 20/10 to 30/20 • C. Increasing the temperature from 30/20 to 35/25 • C had a negative effect on the seed germination. Except at 25/35 • C, no significant differences were observed between the light/dark and dark treatments. A three-parameter logistic model (Equation (2)) was used to model the salinity data following this equation: where G (%) is the germination (%) at NaCl concentration X, Gmax is the maximum germination (%), X50 is the concentration of NaCl for a 50% inhibition of germination, and b shows the slope.

Scarification
A poor germination (<15%) was obtained in the control (no-treatment) condition ( Figure 2). The germination improved (p < 0.001) by physical scarification. No difference was observed among the biotypes in response to the seed scarification.

Temperature and Light
The seed germination was significantly (p < 0.001) affected by alternating the temperature and light conditions, and their interaction produced a significant effect on the germination of B. eruciformis ( Figure 3). There were no significant differences among the biotypes. Seed germination was not observed at 15/5 °C day/night temperature. The lowest germination was observed at 20/10 °C, and germination was the greatest at day/night temperatures of 30/20 °C. Germination increased with an increasing temperature from 20/10 to 30/20 °C. Increasing the temperature from 30/20 to 35/25 °C had a negative effect on the seed germination. Except at 25/35 °C, no significant differences were observed between the light/dark and dark treatments.

Water Potential
Germination was affected by different water potential levels ( Figure 4). The effects of the treatments on the biotypes were not significant. Germination was reduced as the water potential decreased. The highest germination was observed for the control (0 MPa), and no germination was observed at the water potential −0.8 MPa. The three-parameter sigmoidal model predicted a water potential of −0.3 MPa to inhibit a 50% germination (X50) of B. eruciformis.

Water Potential
Germination was affected by different water potential levels ( Figure 4). The effects of the treatments on the biotypes were not significant. Germination was reduced as the water potential decreased. The highest germination was observed for the control (0 MPa), and no germination was observed at the water potential −0.8 MPa. The three-parameter sigmoidal model predicted a water potential of −0.3 MPa to inhibit a 50% germination (X50) of B. eruciformis.

Salinity
Different levels of NaCl concentrations caused significant differences in the germination of B. eruciformis ( Figure 5). No significant differences were observed among the biotypes. Germination was the greatest at the control condition (0 mM). Under increasing NaCl concentrations, the germination decreased, with 200 mM NaCl inhibiting the germination completely. NaCl concentrations of 85 mM inhibited the germination by 50% (X50 value).

Salinity
Different levels of NaCl concentrations caused significant differences in the germination of B. eruciformis ( Figure 5). No significant differences were observed among the biotypes. Germination was the greatest at the control condition (0 mM). Under increasing NaCl concentrations, the germination decreased, with 200 mM NaCl inhibiting the germination completely. NaCl concentrations of 85 mM inhibited the germination by 50% (X50 value).

pH
The germination of B. eruciformis was influenced by the pH (p < 0.001) ( Figure 6). The effect of the pH was similar among biotypes. The highest germination percentage occurred at a neutral pH condition (6-8), and seeds germinated more than 70% over the broad range of pH from 4 to 10.

pH
The germination of B. eruciformis was influenced by the pH (p < 0.001) ( Figure 6). The effect of the pH was similar among biotypes. The highest germination percentage occurred at a neutral pH condition (6)(7)(8), and seeds germinated more than 70% over the broad range of pH from 4 to 10. Figure 5. The effect of sodium chloride (NaCl) concentrations on the seed germination of three biotypes of B. eruciformis. Each point of the graph represents a mean value of the germination data (pooled across biotypes), as no significant differences were observed among biotypes. A threeparameter logistic model was fitted to the germination (%). The vertical bars represented the standard error of mean.

pH
The germination of B. eruciformis was influenced by the pH (p < 0.001) ( Figure 6). The effect of the pH was similar among biotypes. The highest germination percentage occurred at a neutral pH condition (6)(7)(8), and seeds germinated more than 70% over the broad range of pH from 4 to 10. Figure 6. The effect of the pH level on the seed germination of three biotypes of Brachiaria eruciformis. Each bar of the graph represents a mean value of the germination data (pooled across biotypes), as no significant differences were observed among biotypes. The vertical bar shows the least significant difference (LSD) values at the 5% level of probability.

Burial Depth
The effect of the burial depth was significant (p < 0.001) for the seedling emergence of B. eruciformis (Table 1). No significant differences in the seedling emergence were observed among biotypes. The emergence of all biotypes decreased as the burial depth increased; there was a >84% decrease in emergence from seeds buried 4 or more cm in comparison with a burial depth of 0 cm. No seedling emergence was observed from 8 cm.

Sorghum Residue Amount
The results showed that sorghum residue adversely influenced the emergence of B. eruciformis (Table 2). No significant differences were observed among biotypes in response to sorghum residue levels. The highest emergence was observed with the no sorghum residue treatment (63%), while a sorghum residue amount of >8 t ha −1 completely inhibited emergence.

Discussion
Brachiaria eruciformis is a native weed in tropical and subtropical zones of the world, and it has infested many agroecological regions [12]. The lack of germination at 15/5 • C indicates the inability of this scarified weed seed to germinate under extreme winter conditions; however, more than 45% germination at 20/10 • C shows the potential of this weed to germinate during the latter part of the winter season. In Queensland, unlike other growing regions, warm subtropical to tropical weather conditions exist with intermittent hot days even during the winter season. This study suggests the predominance of this weed in Queensland throughout the summer and late winter seasons and its potential to invade more areas of the northern region of Australia.
Similar germination responses to temperatures were observed in other weeds, such as Brachiaria platyphylla (Griseb.) Nash and Eleusine indica (L.) Gaertn, for which a cumulative germination increased with an increasing temperature, with the highest germination observed at 30/20 • C day/night temperature [26,27]. In the current study, biotypes responded similarly to changes in light and temperature conditions. In the dark condition, germination occurred across all temperatures. A similar germination pattern was observed in many weeds, including B. platyphylla and Poa annua L. [28,29]. The observation of germination in the dark condition explains the ability of B. eruciformis to germinate under a plant canopy or mulch. These results also suggest that this weed will germinate regardless of light conditions, allowing germination to occur even if it is buried at shallow depths.
Seed germination was not sensitive to varying pH levels. Seeds germinated more than 70% over a broad range of pHs from 4 to 10; however, the maximum germination was observed at the neutral pH condition (6)(7)(8). Similar results were observed in Lolium rigidum Gaudin [30], Chloris virgata Sw. [31], and Urochloa subquadripara Trin. [32]. Therefore, pH is not a restricting factor for the germination of B. eruciformis, allows this weed to adapt to several soil conditions, and provides the rationale for the wide distribution of B. eruciformis.
Brachiaria eruciformis could germinate between water potentials of 0 to −0.6 MPa. With a decreasing water potential, germination was concomitantly reduced, and no germination was observed at −0.8 MPa. Similar results were observed for Echinochloa colona (L.) Link. [33]. Persistence mechanisms such as the inhibition of germination under drought stress result in an induced dormancy until sufficient water is accessible for germination, consequently improving the ability for seeds to germinate once favorable conditions occur [34]. Although the northern cropping region receives ample summer rainfall, vagaries in rainfall are often observed, with fluctuations in the quantity and distribution of rainfall. Our results Agronomy 2020, 10, 30 9 of 11 confirm those of other studies, which indicate the potential of this weed to emerge under a moderate level of water potential [33].
Similar to the water potential, salt stress can cause a reduction in germination. Our study indicates a high level of salt tolerance in B. eruciformis. Fifty percent of seeds were still able to germinate at NaCl concentrations of 85 mM, indicating that the salt tolerance is higher in B. eruciformis than in many other weeds. For example, the NaCl concentration that inhibited a 50% germination in Rapistrum rugosum (L.) All. was 77 mM [35]. The ability to germinate under high NaCl concentrations has been reported in many weeds, such as Chloris virgata Sw. and Eragrostis pilosa (L.) P. Beauv. [36], and this ability favors the distribution of the weed to new areas.
An increase in the burial depth and sorghum residue amount reduced B. eruciformis emergence. A burial depth of 4 cm and a sorghum residue amount of 4 t ha −1 reduced the emergence of B. eruciformis by 84% and 65%, respectively. Reductions in the emergence of weeds due to an increase in the burial depth and residue amount have been reported for numerous weeds [37][38][39]. The low emergence of B. eruciformis with the increase in the burial depth and sorghum residue amount could be attributed to low seed carbohydrate reserves, the light requirement [40,41], and could sometimes be due to allelopathy of the sorghum residue [42]. Light is not a restricting factor for B. eruciformis germination. Baskin and Baskin [43] noted that the emergence of small-seeded species with limited carbohydrate reserves was inhibited by deep burial in soil. Rather than spreading chaff (harvested crop straw and debris) into the entire field during crop harvest, the accumulation of chaff in line (chaff lining) is recommended so that the thick straw concentrated in line (12 to 40 t ha −1 ) can minimize the emergence of weeds [9]. In this experiment, there was no emergence of this weed beyond 8 t ha −1 residue, indicating that maintaining straw to this magnitude through conservation agriculture practices or chaff lining can minimize the emergence of this weed. Tillage that can bury seeds more than 6 cm could be a good option for managing this weed. However, buried seeds with a long persistence in deep soil result in the accumulation of more seeds in the soil seed ban and keep the seeds safe from desiccation or predation [17]. B. eruciformis seeds have a hard seed coat and seem to remain in the soil for long periods; therefore, information on seed persistence is required to make management decisions.

Conclusions
The chosen biotypes from different cropping systems (mungbean and sorghum fields, and crop boundary) had no differences in their response to the evaluated factors on germination. It could be concluded that the germination ecology of B. eruciformis was mainly affected by the maternal environment, as the three biotypes were collected from the same region. None of the growing conditions had an inhibitory role or, rather, none favored the germination of one biotype over the others from a germination biology perspective. The ability to germinate over a broad range of environmental conditions could explain the wide distribution of this weed, and management options such as a thick residue cover may suppress the germination and emergence of this weed.