Sorghum allelopathy under field conditions may be caused by a combination of allelochemicals

Abstract

A field experiment replicated over two seasons examined allelopathic effects of eleven sorghum accessions with known sorgoleone content on sorghum growth and yield, weed density and biomass at Panmure Experiment Station, in Shamva, Zimbabwe in the 2017/2018 summer and in late winter to summer in 2018. The trial was a 2 × 11 factorial in a randomized complete block design plus two control treatments replicated thrice. Factor A was weeding regime with two levels: clean weeding and no weeding. Factor B were 11 sorghum accessions. There was a significant sorghum accession × weeding regime interaction effect (p < 0.05) on sorghum head weight. Weeding significantly (p < 0.05) caused heavy Macia heads compared to no weeding. There was a weak negative relationship between sorgoleone content and head weight (r = −.28, p = 0.413), and between sorgoleone content and grain weight (r = −.31, p = 0.357) in winter. There was a highly significant sorghum presence × weeding regime interaction (p < 0.001) on A. conyzoides and R. scabra density in summer. There was no significant correlation (p > 0.05) between sorgoleone content and weed density and biomass, suggesting that sorgoleone may not instantly cause allelopathic effects on weeds upon its release from root hairs because it is strongly sorbed in soil, and inhibition of density and biomass might have been caused by other allelopathic compounds. Future research should trace uptake and translocation of allelopathic compounds to target sites of receiver plants, and demonstrate that subsequent damage symptoms are caused by the allelopathic compounds.

Keywords:

• Sorghum allelopathy
• sorghum presence
• weeding

Reviewing Editor:

• Manuel Tejada, Universidad de Sevilla, Spain

SUBJECTS:

• Agriculture & Environmental Sciences
• Plant & Animal Ecology
• Soil Sciences

Introduction

Weeds compete with crops for resources (Little et al., 2021), and sometimes, their mere presence can cause a reduction of crop yields (Horvath et al., 2023). In southern Africa, in addition to the multiple challenges that include high cost of hybrid seed (Tibugari et al. 2019a), pests and diseases (Karavina et al., 2011; Nyabanga et al., 2021; Tibugari et al., 2013), soil erosion and poor soil fertility (Chipomho et al., 2020; Mafongoya et al., 2006; Parwada et al., 2020), high post-harvest losses (Ngwenyama et al., 2023; Stathers et al., 2020; Strecker et al., 2022), and negative impacts of climate change (Farooq et al., 2023; Mandumbu et al., 2020; Musara et al., 2021), many smallholder farmers lack effective weed management strategies (Nyamangara et al., 2014). Farmers usually control weeds by hand weeding (Mandumbu et al., 2011; Tibugari et al., 2020a) which is labour intensive (Lehnhoff et al., 2022), inefficient (Chivinge, 1990; Mashingaidze, 2004), and not done on time (Mashingaidze, 2004) due to labour bottlenecks (Chikowo et al., 2008). In managing weeds, weeding priorities are given to the main crops, and secondary crops are weeded later. It is not surprising that crops such as may be weeded only once or twice per season (Tibugari et al., 2020a). To reduce the impact of weeds in late weeded crops, farmers may select sorghum varieties that can tolerate weeds during the early stages of growth. Continuous investment in environmentally friendly weed management is critical for sustainable crop production.

Sorghum [Sorghum bicolor (L.) Moench] is a drought tolerant crop adapted to marginal lands in arid and semi-arid regions with low rainfall (Ali et al., 2023; Khalifa & Eltahir, 2023; Pinto et al., 2023; Rad et al., 2023; Tu et al., 2023). It is the fifth most important cereal crop in the world after rice (Oryza sativa (L.), wheat (Triticum aestivum L.), maize (Zea mays L.) and barley (Hordeum vulgare L.) (Hossain et al., 2022). Broadleaf weeds, sedges and grass weeds infest the crop (Mandumbu et al., 2016; Oliveira et al., 2019; Tibugari et al., 2020a, 2020b, 2020c) and can cause high crop losses (Scavo & Mauromicale, 2021). Allelopathy, which has much unrealized potential (Hickman et al., 2023), can beused to together with other methods for sustainable weed management (Kundra et al., 2023).

Different sorghum accessions that include commercial varieties, landrace, wild sorghum and sweet sorghum differ in the production of allelopathic compounds that naturally and sustainably suppress weeds. Reports of sorghum being able to suppress weeds under field conditions have been made. In the Binga District of Zimbabwe, where sorghum is a key grain crop of the Tonga people (Figuié et al., 2021), Chiduza et al. (1995) evaluated production practices of smallholder sorghum farmers and found that Tonga farmers did not weed “Maila Tonga” sorghum landraces until 5-6 weeks after emergence due to their tolerance to weeds. The researchers also found that the Tonga farmers weeded their sorghum crop only once per season. Since sorghum grows slowly in the initial stages, and is considered to be a weak competitor against weeds during the early weeks of growth (Barber et al., 2015), it is possible that the tolerance to weeds in the first 5-6 weeks could be due to production of allelopathic compounds that suppress weed emergence and growth. Since the Tonga farmers practice sorghum monocropping, it is possible that allelopathic compounds that accumulate in the soil over a number of years may prevent weed germination and suppress weed growth. Einhellig and Rasmussen (1989) demonstrated that three years of growing sorghum resulted in reduced weediness in the following crop year.

Sorghum produces allelochemicals, which can accidentally harm other crops (Kremer & Reinbott, 2021; Tibugari et al., 2021) and also suppress certain weeds (Alsaadawi et al., 2015; Uddin et al., 2014). The allelochemicals inhibit photosynthesis, enzymatic activities and protein synthesis (Reicosky & Crovetto, 2014). Sorghum allelopathy is caused by the activity of phenolic acids (Alsaadawi et al., 2015), dhurrin (Bjarnholt et al., 2018) and sorgoleone (Pan et al., 2018; Uchimiya, 2020). Phenolic acids are simple in structure and they quickly disappear in the soil (Czarnota et al., 2003). On their own, they are regarded as weak phytotoxins (Duke, 2015). Dhurrin, which is highly concentrated in young sorghum seedlings (Blomstedt et al., 2012) also breaks down rapidly (Adewusi, 1990), suggesting that on its own, the compound may have a limited role in allelopathy. Sorgoleone causes the major allelopathic activity of sorghum (Pan et al., 2018; Tibugari et al. 2019b). Its high hydrophobicity (Trezzi et al., 2006) causes it to be strongly adsorbed by soil colloids (Trezzi et al., 2016) such that it is released slowly into the soil solution (Dayan et al., 2010), allowing it to persist (Weston & Czarnota, 2001) and suppress weeds over an extended period of time (Dayan et al., 2010). Sorghum varieties producing high sorgoleone content can harm themselves through autotoxicity (Tibugari, Chiduza, Mashingaidze, et al. 2020c) and this may be possible under sorghum monoculture. In terms of weed control, the limitations of the individual allelochemicals produced by sorghum have made some scholars to suggest that under field conditions, sorghum allelopathy may be caused by the joint action of sorgoleone, dhurrin and phenolic acids (Einhellig, 1995; Inderjit & Duke, 2003).

A large number of weeds that are found in southern Africa have been reported to be suppressed by sorghum allelopathy (Table 1).

Table 1. Some of the weeds found in southern Africa, reported to be suppressed by sorghum allelopathy.

Weed species	Common name	Category	Family name	Reference
Abutilon theophrasti Medik.	Velvetleaf	Broadleaf	Malvaceae	Roth et al., 2000
Aeschynomene indica l.	Indian jointvetch	Broadleaf	Fabaceae	Uddin et al., 2013
Amaranthus retroflexus L.	Redroot pigweed	Broadleaf	Amaranthaceae	Uddin et al., 2014
Amaranthus hybridus L.	Smooth pigweed	Broadleaf	Amaranthaceae	Mandumbu et al., 2016
Amaranthus palmeri S. Wats.	Palmer amaranth	Broadleaf	Amaranthaceae	Forney et al., 1985
Anagallis arvensis L.	Scarlet pimpernel	Broadleaf	Primulaceae	Ashraf & Akhlaq, 2007
Avena fatua L.	Wild oat	Grass	Poaceae	Khan et al., 2018
Bidens pilosa L.	Blackjack	Broadleaf	Asteraceae	Tibugari et al. 2020c
Chenopodium album L.	Fat hen	Broadleaf	Chenopodiaceae	Naeem et al., 2018
Convolvulus arvensis L.	Field bindweed	Broadleaf	Convolvulaceae	Cheema, 1988
Cynodon dactylon (L.) Pers.	Couch grass	Grass	Poaceae	Cheema et al., 2002
Cyperus rotundus L.	Purple nutsedge	Sedge	Cyperaceae	Kandhro et al., 2014
Cyperus iria L.	Rice flatsedge	Sedge	Cyperaceae	Forney et al., 1985
Dactyloctenium aegyptium (L.) Willd.	Crowfoot grass	Grass	Poaceae	Mubeen et al., 2012
Datura stramonium L.	Jimsonweed	Broadleaf	Solanaceae	Einhellig & Souza, 1992
Digitaria sanguinalis (L.) Scop.	Hairy crabgrass	Grass	Poaceae	Uddin et al., 2014
Digitaria ischaemum Schr. Muhl.	Smooth crabgrass	Grass	Poacea	Putnam & DeFrank, 1983
Echinochloa colona (L.) Link	Junglerice	Grass	Poaceae	Yar et al., 2020
Echinochloa crus-galli (L.) P. Beauv.	Barnyard grass	Grass	Poaceae	Panasiuk et al., 1986
Eclipta prostrata (L.) L.	False daisy	Broadleaf	Asteraceae	Uddin et al., 2010
Eleusine indica (L.) Gaertn.	Goose grass	Grass	Poaceae	Murimwa et al., 2019
Erigeron canadensis (L.) Cronquist	Canadian fleabane	Broadleaf	Asteraceae	Uddin et al., 2010
Euphorbia heterophylla L.	Wild poinsettia	Broadleaf	Euphorbiaceae	Ayeni & Kayode, 2013
Fumaria indica Hauskn.	Fumitory	Broadleaf	Fumariaceae	Ashraf & Akhlaq, 2007
Galium spurium L.	False cleavers	Broadleaf	Rubiaceae	Uddin et al., 2010
Ipomoea triloba L.	Three-lobe morning glory	Broadleaf	Convolvulaceae	Kim et al., 1993
Lemna minor L.	Common duckweed	Grass-like	Lemnaceae	Einhellig & Souza, 1992
Lolium rigidum Gaudin	Rigid ryegrass	Grass	Poaceae	Rashid et al., 2020
Lolium perenne (L.) ssp. multiflorum (Lam.) Husnot	Italian ryegrass	Grass	Poacea	Forney & Foy, 1985
Lolium temulentum L.	Darnel ryegrass	Grass	Poacea	Jassim et al., 2022
Medicago polymorhha L.	Bur clover	Broadleaf	Fabaceae	Ashraf & Akhlaq, 2007
Parthenium hysterophorus L.	Famine weed	Broadleaf	Asteraceae	Javaid et al., 2006
Phalaris minor Retz.	Littleseed canarygrass	Grass	Poaceae	Khan et al., 2018
Plantago asiatica L.	Chinese plantain	Broadleaf	Plantaginaceae	Uddin et al., 2014
Portulaca oleracea L.	Purslane	Broadleaf	Portulacaceae	Uddin et al., 2014
Rottboellia cochinchinensis Lour. W.D. Clayton	Itchgrass	Grass	Poaceae	Kim et al., 1993
Rumex acetosella L.	Sheep’s sorrel	Broadleaf	Polygonaceae	Panasiuk et al., 1986
Rumex crispus L.	Curly dock	Broadleaf	Polygonaceae	Forney & Foy, 1985
Rumex dentatus L.	Toothed dock	Broadleaf	Polygonaceae	Cheema, 1988
Rumex japonicus Houtt.	Japanese dock	Broadleaf	Polygonaceae	Uddin et al., 2010
Senebiera didyma L. Pers.	Lesser swinecress	Broadleaf	Brassicaceae	Cheema & Ahmed, 1992
Setaria viridis (L.) P. Beauv.	Green foxtail	Grass	Poaceae	Uddin et al., 2013
Trianthema portulacastrum L.	Horse purslane	Broadleaf	Aizoaceae	Khaliq et al., 2011
Xanthium strumarium L.	Common cocklebur	Broadleaf	Asteraceae	Alsaadawi et al., 2015

Allelopathy studies conducted under controlled environments have demonstrated that sorghum allelopathy can suppress weed germination and growth (Mandumbu et al., 2016; Tibugari et al., 2020c), suggesting that sorghum allelopathy can be a useful component of integrated weed management. However, as reported by Inderjit et al. (2001) and Duke (2015), most laboratory studies on allelopathy have not been backed up with field experiments that confirm laboratory findings under natural conditions. Under field conditions, environmental factors may influence production, bioavailability and bioactivity of allelochemicals (Tibugari et al., 2019b; Trezzi et al., 2016). Facenda et al. (2023) found that in natural and agricultural ecosystems, soil processes can reduce the allelopathic activity of the allelopathic phenolic acids hydroxycoumarins, which are produced by sorghum. Field performance of allelopathic sorghum accessions may influence how farmers handle sorghum stover after harvesting grain. How farmers handle sorghum residues after harvest will affect availability and field performance of allelochemicals (Tibugari et al., 2020b). Studies that have so far examined sorghum allelopathy under field conditions have mostly tested commercial sorghum varieties (Alsaadawi et al., 2015; Einhellig & Rasmussen, 1989) whereas many smallholder farmers in southern Africa grow landraces and sweet sorghums, and this warrants investigating allelopathic potential of landrace sorghums in the field.

Literature on the potential of sorgoleone to suppress weeds in the field is still scarce. Sorghum has been known to have inhibitory effects on weeds for many years. In a report first published in 1907, Breazeale (1924) reported that sorghum caused injurious after-effects in the early stages of some other crop that follows sorghum in a rotation; and suggested that the injurious effects could be caused by either exhaustion of essential nutrients in the soil, or toxic substances left in the soil by the sorghum crop. Breazeale also concluded that the action of sorghum caused soil deflocculation. Alsaadawi et al. (2015) tested if the variation in weed population and biomass between the stands of two sorghum varieties producing different concentrations of sorgoleone, Enkath and Rabeh, could be due to differences in their allelopathic potential. Their field experiment showed that Enkath, which produced 8 mg/g dry weight of sorgoleone, significantly suppressed weed density and dry weight biomass over Rabeh, which produced about 6.8 mg/g dry weight of sorgoleone. In addition to sorgoleone Enkath also produced several phenolic acids in greater quantities compared to Rabeh. Uddin et al. (2010) did not plant sorghum varieties with known sorgoleone concentrations. Rather, they sprayed sorgoleone on weeds in a greenhouse and in the field. They found that sorgoleone was more effective for broadleaf weed species followed by sedge and grasses. Of interest was the observation by the authors, that growth inhibition of weeds was slightly lower in field conditions compared to greenhouse conditions. Einhellig and Rasmussen (1989) concluded that prior cropping with grain sorghum inhibited weeds after conducting field experiments for three consecutive years from 1985 to 1987 at a farm in northeastern Nebraska. Prior cropping with sorghum did not totally eradicate weeds, but caused delayed emergence and growth inhibition of weeds. However, the study does not attribute the allelopathic effects to sorgoleone. Other studies that have tested allelopathic effects of sorgoleone on weeds and other crops have been done under controlled environments (Uddin et al., 2013; 2014).

When Tibugari et al. (2019b) quantified sorgoleone in 353 southern African sorghum accessions, 97% of which were landraces; they found that most of the sorghum accessions produced sorgoleone in varying concentrations, suggesting that the sorghum accessions have potential to suppress weeds through allelopathy. Follow-up studies that quantified sorgoleone in sorghum accessions suspected by farmers to be allelopathic indicated that some of the varieties produced very low concentrations of sorgoleone (Tibugari et al., 2020b), suggesting that under field conditions, sorghum allelopathy may not solely be caused by sorgoleone, but also by water soluble allelochemicals. Follow up studies using part of the sorghum germplasm from southern Africa, under controlled conditions; have also indicated that there is potential to exploit sorghum allelopathy using aqueous extracts alone, and in mixture with reduced doses of atrazine in controlling Bidens pilosa (L.) and Eleusine indica (L.) Gaertn. (Tibugari et al., 2022). Under laboratory conditions, allelopathic sorghum aqueous root extracts from southern African sorghum accessions inhibited germination and seedling growth of crops and weeds (Tibugari & Chiduza, 2022). Therefore, a study testing the allelopathic potential of sorghum accessions whose sorgoleone contents are known; and under field conditions, could confirm the possible involvement of other allelochemicals in weed suppression.

The Southern Africa regional station of the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) based in Bulawayo, Zimbabwe maintains a sorghum germplasm repository with 2584 sorghum accessions (International Crops Research Institute for the Semi-Arid Tropics [ICRISAT], 2018). The sorghum accessions include landraces, wild sorghum, sweet sorghum and commercial sorghums (ICRISAT, 2018) whose allelopathic potential can be exploited under field conditions for weed control. The potential allelopathic effects of these sorghum accessions on weeds under field conditions have not been examined. Olofsdotter et al. (2002) established that in rice, it is possible to use allelopathy to improve overall crop competitive ability against weeds, and that allelopathy accounted for 34% of overall competitive ability. Apart from aiding in weed control, allelochemicals produced by sorghum can also have other beneficial effects. Research has shown that rapid nitrification can increase loss of nitrogen in agricultural systems (Gao et al. 2020). Sorgoleone can reduce loss of nitrogen fertilizers in soil by inhibiting biological nitrification (Tesfamariam et al., 2014). Biological nitrification inhibition can result in nitrogen use efficiency of sorghum (Subbarao et al., 2015). Sorgoleone strengthens the sorghum arbuscular mycorrhizal fungi symbiosis, nitrogen uptake and reduces the ammonia pool subjected to nitrification, and the loss of nitrogen (Sarr et al., 2021). Increasing nitrogen use efficiency provides opportunities to enhance crop productivity (Govindasamy et al., 2023), and improve sorghum yield and grain quality (Ostmeyer et al., 2022). Physiological processes connected to biomass production and grain yield, including the development and maintenance of photosynthetic activity are affected by the availability, absorption, and utilization of nitrogen (Wanga et al., 2022). In a study, Gao et al. (2022) found that high sorgoleone producing sorghum genetic stocks suppress soil nitrification and N2O emissions better than low-sorgoleone producing genetic stocks. We hypothesized that by inhibiting different physiological functions of weeds, the sorgoleone produced by sorghum accessions could enhance sorghum emergence, final crop stand, height, head weight, grain weight and stover biomass. The objectives of the current study were to:

1. Determine the effect of weeding on growth and yield of sorghum, and on weed density and biomass.

2. Determine if sorghum growth and yield, and weed density and biomass are correlated with sorgoleone content of the 11 sorghum accessions.

Materials and methods

Location

The experiment was conducted at Panmure Experiment Station (17°35’S, and 31°47’E) in Shamva, Zimbabwe in 2017/18 summer and 2018 winter seasons. Panmure Experiment Station lies 881 metres above sea level and receives annual rainfall ranging from 650 to 800 mm. The soil pH, which was slightly acidic (5.8), was determined from soil samples collected from five randomly selected positions in the field, at a depth of 20 cm. The samples were air-dried at room temperature (23 °C) for seven days before being ground and sieved through a 2 mm sieve. Chemical analysis was carried out using a Hanna 2210 pH meter in a 1:25 (wt:wt) water suspension, at the Soil and Plant Analysis Laboratory, University of Zimbabwe. The soil was medium-grained sandy clay loam and is classified as Chromic Luvisols (Zimbabwean classification) or Rhodexeralf Alfisols (USDA classification) (Nyamapfene, 1991). The fields used for the summer and winter trials had been fallow for the previous year and no herbicide had been applied.

Sorgoleone content of sorghum accessions

The 11 sorghum accessions were part of 353 sorghum accessions whose sorgoleone content was quantified in 2019 (Tibugari et al., 2019b).

Quantification of sorgoleone in the sorghum accessions

Quantification of sorgoleone content was done following procedures described by Tibugari et al. (2019b) and Tibugari et al. (2020b). Three hundred and fifty three sorghum accessions were obtained from the regional station of the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) at Matopos based in Bulawayo, Zimbabwe, through a Standard Material Transfer Agreement, as stipulated by the International Treaty on Plant Genetic Resources for Food and Agriculture, of the FAO (Food & Agriculture Organization of the United Nations) (2009).

Seed germination

Seeds were tested for germinability and then treated with benomyl, a broad-spectrum systemic fungicide, before planting. These were rinsed with distilled water after which three replicates of each sorghum accession, each consisting of 50 seeds, were planted in sterile 100 mm × 40 mm petri dishes on the surface of double layers of sterile Whatman No. 1 filter paper (90 mm diameter). Distilled water (15 mL) was applied to each dish using a pipette. The petri dishes were covered with a black polyethylene plastic sheet to exclude light. The seedlings were grown in the dark, with temperature maintained at 28 °C (Baerson et al., 2008; Netzly & Butler, 1986). Watering was done as need arose until seedlings were 6 d old.

Fresh root processing and solvent extraction

Six days after germination, roots of seedlings were excised from the shoots using sharp sterile, carbon steel surgical blades (Elite Healthcare, Harare, Zimbabwe) (Figure 1). The roots of each accession replicate were harvested separately and stored in sterile 22 mL universal bottles. The bottles were kept in a refrigerator at 4 °C until all root harvesting was complete. Root extraction was done following the procedures of Dayan (2006) and Baerson et al. (2008) with modifications. Extraction involved immersing the excised roots in high-performance liquid chromatography (HPLC)-grade methanol (Lab-Scan Analytical Sciences, Poland, supplied locally by Lastmark Laboratories, Harare, Zimbabwe) (1:20, w/v), as recommended by Uddin et al. (2010), for 3 min. Roots were removed from the methanol solution using forceps and allowed to dry for approximately 5 min at room temperature, and weighed using a digital scale (Mettler PC 180, Mettler Instrumente AG, Zurich, Switzerland) to determine fresh weights. The crude solvent extract was sieved using Whatman No.1 filter paper. The filtrate, whose colour ranged from brown to greyish white, was kept sealed in the universal bottles in a refrigerator at 4 °C until all samples were ready for drying.

Figure 1. Fresh root processing and drying of solvent extract.

Drying of solvent extract

One technical challenge that was encountered with drying the large number of samples using the standard rotary evaporator was that the available rotavapor (Büchi Rotavapor R-114, Büchi Instruments, Warsaw, Poland) could only dry eight samples per day, and drying the solvent extract would take about 1.5 months to complete. It was desired to dry the extract in a short space of time. A comparison of drying the filtrate using a rotavapor and drying by placing open universal bottles containing the extract directly in a water bath (Scientific Instruments, South Africa), with the water temperature set at 45 °C, was made. Sorgoleone starts to melt at 50–51 °C and therefore a water bath temperature of 45 °C was considered safe for the compound. In addition, methanol has a low boiling point of 64.7 °C. Low boiling point solvents preclude the degradations or modifications that may be induced by solvents of slightly higher boiling point (Vattuone et al., 2009). Using the water bath, an average of 20 samples could be dried in about 30 min. The latter option was therefore preferred and used (Figure 1). The universal bottles containing the extract were immersed in a water bath and the extract was allowed to dry. Bottles with the dry product were then removed from the water bath and left to cool at room temperature. This protocol was tested for the first time in this study. The dried extract was dissolved in the mobile phase (1 mg mL − 1) and the solution filtered through a poly filter (0.45 μm) prior to HPLC analysis.

HPLC quantification of sorgoleone

Each sample was prepared in 70% acetonitrile/30% water acidified with 0.1% acetic acid (Sigma-Aldrich, South Africa). Samples were subjected to HPLC analysis using an Agilent HPLC 1260 system (Agilent Technologies, Santa Clara, CA) equipped with a binary pump. The analytical column used was a Phenomenex® Luna^® column with dimensions 3 μm, 50 mm length and 2 mm internal diameter. The flow rate was 0.6 mL min − 1. The injection volume was 10 μL. Sorgoleone was eluted at 2.588 min and the total run time was 5 min. The variable wavelength detector was monitored at 280 nm. Quantification was based on a calibration curve using purified sorgoleone as an external standard. The sorgoleone standard was supplied by Professors Stephen O Duke and Frank E Dayan (US Department of Agriculture–Agricultural Research Service, University, MS, USA). HPLC quantification of sorgoleone was done at Microlab, Marlborough, Harare, Zimbabwe.

Statistical analysis of sorgoleone quantification data

The determinations of sorgoleone contents were replicated three times for each sorghum accession in a group. Data from each country was evaluated to determine whether it was normally distributed using the Shapiro–Wilk test. Data acquisition and analysis was done using the Agilent MassHunter Workstation software version B.07.03 (509) (Agilent Technologies, 2007). One-way ANOVA was conducted to determine differences in sorgoleone content among the sorghum accessions. Standard error of the difference was used to separate treatment means at the 5% level of significance.

Selection of the 11 sorghum accessions for the field experiment

To test if differences in sorgoleone content among sorghum accessions influences sorghum emergence and growth, stratified sampling was done to create 11 groups of sorghum accessions based on sorgoleone concentrations. The 11 accessions used in the study were randomly picked from the 11 groups. The eleven sorghum accessions originated from different countries, and comprised landraces, one open pollinated variety (OPV), and one sweet sorghum (Tables 2 and 3).

Table 2. Characteristics of sorghum accessions used in the field experiment.

Accession	Description	Origin	Sorgoleone content (µg/mg r.f.w)	Days to flowering post-rainy	Days to flowering rainy	100 seed weight (g)
Macia	OPV	Botswana, Mozambique, Tanzania, Zimbabwe	2.5	60	65	2.0
IS35583	Landrace	Namibia	104.3	73	85	3.72
IS13807	Landrace	South Africa	50.0	73	54	2.5
IS9409	Landrace	South Africa	152.3	84	67	2.67
IS9362	Landrace	South Africa	252.9	89	62	2.3
IS14002	Landrace	South Africa	381.2	82	62	3.35
IS14003	Landrace	South Africa	472.7	84	58	2.96
IS9456	Landrace	South Africa	584.7	69	56	3.2
IS19462	Landrace	Botswana	302.8	70	55	3.82
IS23342	Landrace	Zambia	207.1	98	133	2.13
IBS718	Sweet	Zimbabwe	20.1	*	*	*

* Details omitted since this accession is not cultivated for grain.

Table 3. Sorgoleone content of the eleven sorghum accessions evaluated for allelopathic effects on summer and winter weeds at Panmure Experiment Station, Zimbabwe.

Accession	Description	Origin	Sorgoleone content (µg/mg r.f.w)
Macia	Commercial (OPV)	Botswana, Mozambique, Tanzania, Zimbabwe	2.5
IBS718	Sweet stem	Zimbabwe	20.1
IS13807	Landrace	South Africa	50.0
IS35583	Landrace	Namibia	104.3
IS9409	Landrace	South Africa	152.3
IS23342	Landrace	Zambia	207.1
IS9362	Landrace	South Africa	252.9
IS19462	Landrace	Botswana	302.8
IS14002	Landrace	South Africa	381.2
IS14003	Landrace	South Africa	472.7
IS9456	Landrace	South Africa	584.7

Source: Tibugari et al., 2019b.

Treatments and experimental layout

Two factors: weeding regime at two levels (weeded and unweeded) and eleven sorghum accessions with known sorgoleone content, were tested in a factorial combination. The experiment was laid out as a randomised complete block design with three replications. The trial was a 2 x 11 factorial in a randomized complete block design plus two control treatments (unweeded without sorghum, and weeded without sorghum) replicated thrice. Control treatments were an unweeded plot without sorghum and a weeded plot without sorghum.

Land preparation, field layout and trial management

The field was ploughed to a depth of 35 cm in November 2017 using a tractor drawn disc plough and then disced to improve soil tilth and infiltration capacity. Plots consisted of four rows spaced 0.75 m apart and 1.5 m long. Pathways measuring 1.5 m and 2 m wide were maintained between plots and blocks respectively. A basal compound fertiliser, Compound D (7% N, 14% P₂O₅, 7% K₂O) was band applied in the rows at the rate of 200 kg ha⁻¹. Planting stations that were 25 cm apart were marked out using a dibble resulting in a plant population of 53 333 plants ha⁻¹. Two sorghum seeds were planted per planting station, and seedlings were thinned to one per station 2 weeks after emergence (WAE). Ammonium Nitrate (AN) (34% N) was applied as top dressing at the rate of 150 kg ha⁻¹ 4 WAE. The summer trial was largely rainfed while the winter trial was exclusively irrigated. Planting of the summer experiment was done on 28 January 2018 and harvesting on the 1st of June 2018. The winter experiment was planted on 17 July 2018 and harvested on the 8th of December 2018. It is possible to plant winter field trials at Panmure in because of considerably high winter and spring temperatures that are experienced at the station. The net plot consisted of two centre rows, each measuring 1 metre long.

Data collection

Data on weed density and weed biomass were recorded 65 days after sowing. Weed density and biomass per sub-plot were determined from two randomly placed 0.5 m² quadrats. Weed biomass data were recorded after clipping weeds at the soil surface and oven drying them at 70 °C for 72 h. Weeds that were classified as minor occurred in very low densities and infrequently among plots. Data on percentage emergence were recorded 10 days after sowing. Final crop stand was determined three weeks after sorghum emergence. Head weight, grain weight and stover biomass were measured after sorghum grain reached physiological maturity and dried down in the field. Physiological maturity was attained when a black spot appeared at the point where the seed attaches the plant. At that time, leaves had started turning yellowish and were beginning to dry up naturally. Harvesting was done manually by cutting the heads with a sickle. Head weight was determined by harvesting all panicles with grains and weighing on a digital scale. The average panicle yield for each plot was determined by dividing the total weight by the number of panicles for each plot, as described by Atokple et al. (2014). Dried sorghum plants were hand-harvested from the net plot consisting of two central rows. Sorghum heads were dried in perforated harvesting bags for 18 days. The heads were threshed for grain yield determination. Grain weight was measured using a digital scale. Grain moisture content after threshing was measured using a John Deere TY9304 moisture meter. Sorghum grain yield was adjusted to 12.5% moisture content.

Statistical analysis

All weed density data were expressed as number m⁻² and square root transformed (x + 0.5) to homogenize variances (Gomez & Gomez, 1984), before statistical analysis (Steel & Torrie, 1984). Data were subjected to analysis of variance for a 2 × 11 factorial in a randomized complete block design plus two control treatments using GenStat Discovery 14.1 (VSN-International, 2011). Standard errors of difference (s.e.d.) were used for mean separation where treatment effects were significant at p < 0.05. PAleontological STatistics (PAST) package version 3.25 (Natural History Museum) (Hammer et al., 2001) was used to compute Pearson correlational analyses examining relationships between sorgoleone content of the sorghum accessions and weed density, weed biomass, sorghum emergence, final crop stand, height, head weight, grain weight and stover biomass. Stacked bar charts were used to make a pictorial presentation of the sorghum emergence, final crop stand, height, head weight, grain weight and stover biomass results.

Results

Effect of sorgoleone content on emergence and growth of sorghum

Results on temperature and rainfall/irrigation pattern during the summer and winter seasons are presented in Figure 2. The low rainfall that was received in December was not sufficient for planting and early sustenance of the crop and planting was done using irrigation in January. High rainfall was experienced in February. In March and April, the rains tailed off, signalling the end of the rainy season. The rainy season was short. In winter, no rains were received, and the crop had to be fully sustained by irrigation applied at 53 mm per week.

Figure 2. Rainfall received and irrigation applied in summer and winter months of the trial. Source: Panmure Experiment Station Weather Station, Shamva, Zimbabwe. Temperatures ranged from 5 °C to about 20 °C (Figure 3).

Figure 3. Average maximum and minimum monthly temperatures for the summer (A) and winter (B) seasons. Source: Panmure Experiment Station Weather Station, Shamva, Zimbabwe.

Pictorial presentation of results

A pictorial representation of the summer and winter data was made using stacked charts (Figure 4). Macia maintained the highest grain weight consistently in summer and winter. High grain weight was also recorded in IS19462, IS23342 and IS9409 in summer. Landraces and the sweet sorghum performed better than Macia in terms of stover biomass in both summer and winter.

Figure 4. Stacked bar charts for summer (A) and winter (B).

Sorghum performance in summer

Results showing interaction of sorghum accession and weeding regime and their main effects on percentage emergence, final crop stand, height, head weight, grain weight and stover biomass in summer are presented in Table 4.

Table 4. Effect of sorghum accession and weeding regime on sorghum growth and yield in summer (January to June 2018).

Sorghum accession	% emergence	Final crop stand	Height (cm)	Head weight (g)	Grain weight (g)	Stover biomass (g plant^−1)
IBS718	76.4ab	85.0ab	154.3ab	535abc	241ab	138.1
IS13807	48.6ab	72.7a	190.5ab	407ab	181a	100.7
IS14002	38.9a	73.3ab	131.2a	218a	192a	153.5
IS14003	83.3ab	91.0ab	234.2bc	444ab	189a	156.7
IS19462	75.0ab	83.7ab	196.2abc	1126cd	681bc	110.4
IS23342	84.7b	88.7ab	177.3ab	959bcd	578abc	151.1
IS35583	57.0ab	76.3ab	195.7abc	400ab	178a	144.1
IS9362	43.1ab	77.5ab	228.5bc	348ab	207a	150.8
IS9409	47.2ab	73.2ab	194.8abc	594abc	422abc	135.2
IS9456	52.8ab	75.7ab	275.0c	346ab	130a	139.3
Macia	75.0ab	91.7b	158.0ab	1281d	837c	140.4
p Value	p < 0.05	p < 0.05	p < 0.001	p < 0.001	p < 0.001	P > 0.05
s.e.d.	12.67	5.48	23.06	178.6	133.6	23.46
Weeding regime
Unweeded	59.6	79.8	190.2	499a	295	129.7
Weeded	64.4	81.7	198.1	712b	403	146.7
P value	P > 0.05	P > 0.05	P > 0.05	p < 0.05	P > 0.05	P > 0.05
s.e.d.	5.40	2.34	9.83	76.1	56.9	10.00
Sorghum accession × weeding regime interaction
P value	P > 0.05	P > 0.05	P > 0.05	p < 0.05	P > 0.05	P > 0.05
s.e.d.	17.92	7.76	32.61	252.5	188.9	33.18

Means within a column followed by the same letter are not significantly different at P > 0.05.

There was a significant sorghum accession ˟ weeding regime interaction effect (p < 0.05) on head weight (Figure 5). Macia had significantly heavy panicles (p < 0.05) in the weeded plots compared to all the sorghum accessions. Weeding significantly increased panicle weight of Macia. In contrast weeding significantly reduced panicle weight of IS9362.

Figure 5. Sorghum accession × weeding regime interaction.

The main effects of sorghum accession were significant for percentage emergence and final crop stand (p < 0.05); and highly significant (p < 0.001) for height and grain weight. The main effects of sorghum accession were not significant (P > 0.05) on stover biomass.

Sorghum performance in winter

Results (Table 5) show effect of sorghum accession and weeding regime on percentage emergence, final crop stand, height, head weight, grain weight and stover biomass in winter. The main effect of sorghum accession was significant (p < 0.05) on panicle and grain weight, and highly significant (p < 0.001) on height. The main effect of sorghum accession was not significant (P > 0.05) on percentage emergence, final crop stand and stover biomass. The main effect of weeding regime was not significant (P > 0.05) on percentage emergence, final crop stand, height, panicle weight, grain weight and stover biomass. There was no significant sorghum accession ˟ weeding regime interaction effect (P > 0.05) on percentage emergence, final crop stand, height, panicle weight, grain weight and stover biomass.

Table 5. Effect of sorghum accession and weeding regime on sorghum growth and yield in warm winter (July–December 2018).

Sorghum accession	% emergence	Final crop stand	Height (cm)	Head weight (g)	Grain weight (g)	Stover biomass (g plant^−1)
IBS718	84.72	88.0	166.8a	526a	274a	132.6
IS13807	83.32	86.5	179.8a	648ab	341ab	141.1
IS14002	90.28	92.7	158.0a	719ab	363ab	139.7
IS14003	84.70	87.8	203.7ab	678ab	378ab	140.7
IS19462	87.50	89.5	165.2a	622ab	381ab	118.1
IS23342	86.10	88.8	152.2a	556ab	252a	135.9
IS35583	86.12	90.2	156.7a	504a	267a	150.3
IS9362	84.72	88.3	207.8ab	556ab	244a	134.4
IS9409	80.57	84.8	170.7a	526a	248a	102.2
IS9456	83.35	88.8	248.5b	459a	185a	147.8
Macia	80.55	87.0	142.8a	1007b	570b	103.0
P value	P > 0.05	P > 0.05	p < 0.001	p < 0.05	p < 0.05	P > 0.05
s.e.d.	4.354	3.911	18.47	131.5	84.4	25.94
Weeding regime
Unweeded	83.83	87.7	178.0	605	309	131.8
Weeded	85.61	89.2	177.0	631	328	131.0
P value	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05
s.e.d.	1.856	1.668	7.87	56.1	36.0	11.06
Sorghum accession ˟ weeding regime interaction
P value	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05
s.e.d.	6.157	5.531	26.12	185.9	119.3	36.69

Means within a column followed by the same letter are not significantly different at P > 0.05.

Correlation analysis

Loadings plot correlations for summer and winter are presented in Figure 6.

Figure 6. Loadings plot correlations for summer (A) and winter (B).

Pearson correlations showed a weak negative correlation between sorgoleone content and percentage emergence in summer (r = −.10, p = 0.761) (Figure 3). There was a weak negative correlation between sorgoleone content and final crop stand in summer (r = −.09, p = 0.792). There was a weak negative relationship (r = −.36, p = 0.278) between sorgoleone content and head weight, and a weak negative relationship (r = −.37, p = 0.259) between sorgoleone content and grain weight in summer. There was a weak positive relationship (r = .24, p = 0.486) between sorgoleone content and stover biomass in summer. There was a weak positive correlation between sorgoleone content and percentage sorghum emergence in winter (r = .34, p = 0.300). There was a weak positive correlation between sorgoleone content and final crop stand in winter (r = .39, p = 0.242). There was a weak positive relationship (r = .40, p = 0.221) between sorgoleone content and stover biomass in winter. Sorgoleone content and sorghum height had a significant moderate positive relationship in summer (r = .61, p < 0.05) and a significant high positive relationship in winter (r = .71, p < 0.05). There was a weak negative relationship (r = −.28, p = 0.413) between sorgoleone content and head weight, and a weak negative relationship (r = −.31, p = 0.357) between sorgoleone content and grain weight in winter.

Effect of sorghum presence on weed density and biomass

Weeds recorded in the field

Seventeen weed species comprising five grasses and 12 broadleaf weeds were recorded in summer and winter (Table 6).

Table 6. Weed species recorded in summer and winter.

Weed species	Family name	Common name(s)	Summer	Winter
Grasses
Digitaria sanguinalis	Poaceae	Crab finger grass	p (m)	a
Eleusine indica	Poaceae	Goosegrass	p (m)	a
Rottboellia cochinchinensis	Poaceae	Itchgrass/Shamva grass	p (m)	a
Hyparrhenia filipendula	Poaceae	Hyparrhenia	p (m)	a
Cynodon nlemfuensis	Poaceae	African Bermudagrass	p (m)	a
Broadleaf
Acanthospermum hispidum	Asteraceae	Upright starbur	p (m)	a
Ageratum conyzoides	Asteraceae	Billygoat weed	p (d)	p
Bidens pilosa	Asteraceae	Hairy beggarticks	p (m)	p
Richardia scabra	Rubiaceae	Mexican clover	p (d)	p
Sida alba	Malvaceae		p (m)	p
Commelina benghalensis	Commelinaceae	Wandering jew	p (m)	a
Amaranthus hybridus	Amaranthaceae	Slim amaranth	p (m)	p
Ipomoea involucrata	Convolvulaceae	Morning-glory	p (m)	a
Euphorbia heterophylla	Euphorbiaceae	Mexican fireplant	p (m)	a
Physalis angulata	Solanaceae	Wild gooseberry	p (m)	a
Sesbania sesban	Fabaceae	Egyptian riverhemp	p (m)	p (m)
Leucas martinicensis		Bobbin weed	p (m)	p (m)

Key: p = present; a = absent; (m) = minor weed; (d) = dominant weed.

Grass weed species were only recorded in summer. The broadleaf weeds A. conyzoides, B. pilosa, R. scabra, S. alba, A. hybridus, S. sesban, and L. martinicensis occurred in both summer and winter while A. hispidum, C. benghalensis, I. involucrata, E. heterophyla, and P. angulata were only recorded in summer.

Weed density

Summer

There was a significant sorghum presence ˟ weeding regime interaction on A. conyzoides (p < 0.001), R. scabra (p < 0.001) and total weed density in summer (Figure 7).

Figure 7. Interaction between sorghum presence and weeding regime on A. conyzoides (A), R. scabra (B) and total weed density (C) in summer 65 DAS (Error is for comparison for no sorghum and sorghum presence).

In the weeded treatment, there was no significant difference in the A. conyzoides and R. scabra density between the treatments where sorghum was present; and control treatment where sorghum was absent. In contrast, in the unweeded treatment, a significantly higher A. conyzoides and R scabra density was recorded in the control treatment where sorghum was not present than in treatments where sorghum was present (Figure 7). In both weeded and unweeded treatments, there was a significant difference in total weed density between the treatments where sorghum was present, and control treatment where sorghum was absent.

There was a significant effect of sorghum presence on weed density in the summer. The presence of sorghum significantly reduced A. conyzoides (P = 0.002), R. scabra (p < 0.001), minor weeds (p < 0.05) and total weed density (p < 0.001) compared to the unweeded control treatment without sorghum at 65 DAS (Table 7).

Table 7. Effect of sorghum presence, sorghum accession and weeding regime on weed density (square root (x + 0.5) transformed weed number m⁻²) in summer 65 DAS.

	A. conyzoides	R. scabra	Minor weeds	Total
Sorghum presence
With sorghum	2.208a (4.61)^1	2.142a (4.35)	1.800a (2.82)	3.447 (11.78)
With no sorghum (control)	2.638b (6.67)	2.675b (7.00)	2.075b (3.83)	4.192 (17.5)
P value	P = 0.002	p < 0.001	p < 0.05	p < 0.001
s.e.d.	0.13	0.1402	0.1195	0.1608
Sorghum presence × Sorghum accession interaction
P value	P > 0.05	P > 0.05	P > 0.05	P > 0.05
s.e.d.	0.1784	0.1898	0.1619	0.2177
Sorghum presence ˟ Weeding regime interaction
P value	p < 0.001	p < 0.001	P > 0.05	p < 0.001
s.e.d.	0.0.1863	0.1982	0.1691	0.2274
Sorghum presence ˟ Weeding regime ˟ sorghum accession interaction
P value	P > 0.05	P > 0.05	P > 0.05	P > 0.05
s.e.d.	0.2522	0.2684	0.2289	0.3079

•Means (square root (x + 0.5) transformed weed numbers m⁻²) within a column followed by the same letter are not significantly different at p < 0.05.

•¹Data in brackets are back-transformed actual weed numbers per m⁻².

There was no significant sorghum presence ˟ sorghum accession interaction (P > 0.05) on A. conyzoides, R. scabra, minor weeds and total weed density in summer (Table 7). There was no significant sorghum presence ˟ weeding regime interaction (P > 0.05) on density of minor weeds in summer at 65 DAS (Table 7). There was no significant sorghum presence ˟ weeding regime ˟ sorghum accession interaction (P > 0.05) on density of A. conyzoides, R. scabra, minor weeds and total weed density in summer at 65 DAS (Table 7).

Winter

There was a significant sorghum presence ˟ sorghum accession interaction on S. alba density (P = 0.021) in winter at 65 DAS, meaning the effect of sorghum accession on S. alba density in the weeded and unweeded plots varied with sorghum accession (Figure 8).

Figure 8. Interaction between sorghum presence and sorghum accession on S. alba density in winter at 65 DAS.

Three sorghum accessions (IS13807, IS14002 and IS35583) had similar S. alba density as the control treatment where no sorghum was planted (Figure 8). Eight sorghum accessions (IBS718, IS14003, IS19462, IS23342, IS9362, IS9409, IS9456 and Macia) resulted in significantly lower S. alba density than the control treatment (Figure 8).

There was a significant sorghum presence × weeding regime interaction on A. conyzoides (p < 0.001), A. hybridus (p < 0.001), B. pilosa (p < 0.001) and total weed density (p < 0.001) in winter at 65 DAS (Figure 9). In the weeded and unweeded plots, sorghum presence significantly reduced A. conyzoides, A. hybridus and total weed density (p < 0.001). Density of B. pilosa was not significantly reduced by sorghum presence in the weeded plots (Figure 9(C)). However, in the unweeded plots, sorghum presence significantly (p < 0.001) reduced B. pilosa density.

Figure 9. Effect of sorghum presence and weeding regime on A. conyzoides (A), A. hybridus (B), B. pilosa (C) and total weed density (D) in winter 65 DAS (Error is for comparison for no sorghum and sorghum presence).

Figure 10. Interaction between sorghum presence and sorghum accession on A. conyzoides (A) and total weed biomass (B) in summer at 65 DAS.

Data on weed density recorded in winter are shown in Table 8.

Table 8. Effect of sorghum presence, sorghum accession and weeding regime on weed density in winter 65 DAS.

	A. conyzoides	A. hybridus	B. pilosa	R. scabra	S. alba	Total
Sorghum presence
With sorghum	2.147a (4.36)^1	1.951a (3.62)	2.044a (3.94)	1.729a (2.56)	1.709a (2.485)	4.112 (16.95)
With no sorghum (control)	2.901b (8.50)	2.700b (7.00)	2.578b (6.83)	1.985b (3.50)	1.985b (3.500)	5.374 (29.33)
P value	p < 0.001	p < 0.001	p < 0.001	p < 0.05	p < 0.05	p < 0.001
s.e.d.	0.0938	0.1461	0.1082	0.1102	0.1004	0.1105
Sorghum presence ˟ Sorghum accession interaction
P value	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P = 0.021	P > 0.05
s.e.d.	0.1270	0.1978	0.1465	0.1492	0.1360	0.1497
Sorghum presence ˟ Weeding regime interaction
P value	p < 0.001	p < 0.001	p < 0.001	P > 0.05	P > 0.05	p < 0.001
s.e.d.	0.1327	0.2066	0.1530	1.559	0.1420	0.1563
Sorghum presence ˟ Weeding regime ˟ Sorghum accession interaction
P value	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05
s.e.d.	0.1797	0.2798	0.2072	0.2110	0.1923	0.2117

•Means (square root (x + 0.5) transformed weed numbers m⁻²) within a column followed by the same letter are not significantly different at p < 0.05.

•¹Data in brackets are back-transformed actual weed numbers per m⁻².

The presence of sorghum significantly reduced A. conyzoides (p < 0.001), A. hybridus (p < 0.001), B. pilosa (p < 0.001), R. scabra (p < 0.05), S. alba (p < 0.05) and total weed density (p < 0.001) in winter at 65 DAS (Table 8).

There was no significant sorghum presence ˟ sorghum accession interaction (P > 0.05) on A. conyzoides, A. hybridus, B. pilosa, R. scabra and total weed density in winter at 65 DAS (Table 8).

There was no significant sorghum presence ˟ weeding regime interaction (P > 0.05) on R. scabra and S. alba density in winter (Table 8). There was no significant sorghum presence ˟ weeding regime ˟ sorghum accession interaction on A. conyzoides, A. hybridus, B. pilosa, R. scabra, S. alba and total weed density (P > 0.05) in winter at 65 DAS.

Weed biomass

There was a significant sorghum presence × sorghum accession interaction on A. conyzoides (P = 0.003) and total weed biomass (P = 0.041) in summer at 65 DAS (Figure 10 A and B).

Figure 11. Effect of sorghum presence and weeding regime on biomass of minor weeds (A) and total weed biomass (B) in summer at 65 DAS.

Biomass of A. conyzoides in nine sorghum accessions (IBS718, IS13807, IS14003, IS19462, IS23342, IS35583, IS9362, IS9409 and IS9456) was similar to the control treatment where no sorghum was planted (Figure 6(A)). Two sorghum accessions (IS14002 and Macia) resulted in significantly higher A. conyzoides biomass than the control treatment (Figure 6(A)). All the 11 sorghum accessions (IBS718, IS13807, IS14002, IS14003, IS19462, IS23342, IS35583, IS9362, IS9409, IS9456 and Macia) had lower total weed biomass compared to the control treatment where no sorghum was planted (Figure 6(B)).

Sorghum presence did not significantly reduce A. conyzoides biomass (P > 0.05) in summer at 65 DAS (Table 9).

Table 9. Effect of sorghum presence, accession and weeding regime on weed biomass (g m⁻²) in summer 65 DAS.

	A. conyzoides	R. scabra	Minor weeds	Total
Sorghum presence
With sorghum	6.53	3.59a	11.25a	21.37b
With no sorghum (control)	5.65	5.12b	20.42b	31.18a
P value	P > 0.05	P = 0.028	p < 0.001	p < 0.001
s.e.d.	0.586	0.674	1.175	1.615
Sorghum presence × Sorghum accession interaction
P value	P = 0.003	P > 0.05	P > 0.05	P = 0.041
s.e.d.	0.793	0.913	1.591	2.187
Sorghum presence × Weeding regime interaction
P value	P > 0.05	P > 0.05	p < 0.001	p < 0.001
s.e.d.	0.829	0.953	1.662	2.284
Sorghum presence × Weeding regime × Sorghum accession interaction
P value	P > 0.05	P > 0.05	P > 0.05	P > 0.05
s.e.d.	1.122	1.291	2.251	2.324

• Means within a column followed by the same letter are not significantly different at p < 0.05.

Summer

Sorghum presence significantly reduced R. scabra (P = 0.028), minor weeds (p < 0.001) and total weed biomass (p < 0.001) by 42.6%, 81.5% and 45.9% respectively in summer at 65 DAS (Table 9). There was no significant sorghum presence × sorghum accession interaction on biomass of R. scabra and minor weeds (P > 0.05).

There was no significant sorghum presence × weeding regime interaction on A. conyzoides and R. scabra biomass in summer (P > 0.05) at 65 DAS (Table 9).

The presence of sorghum in weeded and unweeded plots significantly reduced minor weeds (p < 0.001) and total weed (p < 0.001) biomass in summer at 65 DAS (Figure 11).

There was no significant sorghum presence × weeding regime × sorghum accession interaction on A. conyzoides, R. scabra, minor weed and total weed biomass in summer at 65 DAS (Table 9).

Winter

There was a significant sorghum presence × sorghum accession interaction on B. pilosa (p < 0.001) and R. scabra biomass (P = 0.008) in winter at 65 DAS (Figure 12).

Figure 12. Interaction between sorghum presence and sorghum accession on B. pilosa (A) and R. scabra biomass (B) in winter at 65 DAS.

Only one sorghum accession, Macia, had higher B. pilosa biomass than the control treatment where there was no sorghum planted (Figure 12(A)). Seven sorghum accessions (IBS718, IS14002, IS19462, IS23342, IS35583, IS9362 and IS9456) had similar B. pilosa biomass as the control treatment where no sorghum was planted. In contrast, IS13807, IS14003 and IS9409 had lower B. pilosa biomass than the control treatment where there was no sorghum planted. IS9456, had higher R. scabra biomass than the control treatment where there was no sorghum planted while all the other 10 sorghum accessions had similar R. scabra biomass as the control treatment where no sorghum was planted (Figure 12(B)).

There was no significant effect of sorghum presence on A. conyzoides, A. hybridus, B. pilosa, R. scabra, S. alba and total weed biomass (P > 0.05) in winter at 65 DAS (Table 6). There was no significant sorghum presence ˟ sorghum accession interaction on A. conyzoides, A. hybridus, S. alba and total weed biomass in winter at 65 DAS (Table 10).

Table 10. Effect of sorghum presence, sorghum accession and weeding regime on weed biomass (g m⁻²) in winter 65 DAS.

	A. conyzoides	A. hybridus	B. pilosa	R. scabra	S. alba	Total
Sorghum presence
With sorghum	5.60	5.41	5.38	5.52	5.41	27.32
With no sorghum (control)	4.65	4.50	5.53	4.82	4.13	23.63
P value	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05
s.e.d.	0.781	0.819	0.416	0.686	0.651	1.985
Sorghum presence ˟ Sorghum accession interaction
P value	P > 0.05	P > 0.05	p < 0.001	P = 0.008	P > 0.05	P > 0.05
s.e.d.	1.057	1.109	0.563	0.929	0.881	2.687
Sorghum presence ˟ Weeding regime interaction
P value	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05
s.e.d.	1.104	1.158	0.588	0.970	0.920	2.807
Sorghum presence ˟ Weeding regime ˟ Sorghum accession interaction
P value	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05	P > 0.05
s.e.d.	1.495	1.568	0.796	1.314	1.246	3.800

There was no significant sorghum presence × weeding regime interaction on A. conyzoides, A. hybridus, B. pilosa, R. scabra, S. alba and total weed biomass (P > 0.05) in winter at 65 DAS (Table 10). There was no significant sorghum presence × sorghum accession × weeding regime interaction on A. conyzoides, A. hybridus, B. pilosa, R. scabra, S. alba and total weed biomass (P > 0.05) in winter at 65 DAS.

Correlation between sorgoleone content and weed density

There was no significant correlation between sorgoleone content of the 11 sorghum accessions and density of A. conyzoides (P > 0.05), R. scabra (P > 0.05), minor weeds (P > 0.05) and total weed density (P > 0.05) in summer.

There was no significant correlation between sorgoleone content and A. conyzoides (P > 0.05), A. hybridus (P > 0.05), B. pilosa (P > 0.05), R. scabra (P > 0.05), S. alba (P > 0.05) and total weed density (P > 0.05) in winter.

Correlation between sorgoleone content of sorghum accessions and weed biomass

There was no significant correlation between sorgoleone content and A. conyzoides (P > 0.05), R. scabra (P > 0.05), minor weeds (P > 0.05) and total weed biomass (P > 0.05) in summer. There was no significant correlation between sorgoleone content and A. conyzoides (P > 0.05), A. hybridus (P > 0.05), B. pilosa (P > 0.05), R. scabra (P > 0.05), S. alba (P > 0.05) and total weed biomass (P > 0.05) in winter.

Discussion

Differences in sorgoleone content among sorghum accessions

Studies on sorgoleone content produced by local and hybrid varieties have generally shown that hybrid sorghum varieties have low sorgoleone compared to local and wild sorghum accessions. A study which quantified sorgoleone in 353 sorghum accessions which comprised local landrace varieties, wild sorghum and commercial varieties revealed that the cultivated commercial cultivars as well as sweet stem sorghum produced low levels of sorgoleone compared to wild and unimproved sorghum genotypes (Tibugari et al., 2019b). Through breeding and adaptation for arable cropping, the ability of hybrid sorghum to produce sorgoleone is lost. When sorghum is grown as an arable crop it is protected from excessive weed competition by weeding activities and eventually genes that were active in stimulating the production of sorgoleone for allelopathic protection of sorghum are switched off (Tibugari et al., 2019b). Wild sorghums are more subject to environmental stress and this possibly explains their higher sorgoleone content. Differences in sorgoleone production among sorghum varieties can also be caused by genetic differences of the varieties. Yang et al. (2004) reported that the gene responsible for sorgoleone production, SOR1 is differentially expressed in sorghum varieties. Varietal differences in allelochemical production have also been reported by other authors (Alsaadawi et al., 2015; Baerson et al.,2008; Belz, 2007; Tibugari et al., 2020b).

Effect of sorgoleone on sorghum emergence and growth

The result that from the random selection of sorghum accessions for use in the experiment, more landraces were used in the study compared to commercial varieties, was expected. In a previous study which quantified sorgoleone in 353 sorghum accessions from southern Africa, landraces, which originated from different southern African countries, constituted the bulk (92%) of the sorghum accessions (Tibugari et al., 2019b). In a variety of crops, landraces are grown in a number of African countries and a number of factors contribute to the low usage of hybrid seed. For example, in Zimbabwe, a large number of maize farmers do not grow hybrid seed due to its high cost (Tibugari et al., 2019a). In some parts of Africa, improved varieties are simply lacking (Andiku et al., 2021). Adoption of improved varieties is low in other parts of Africa (Okuthe et al. 2013; Ifie et al., 2022; Kalema et al., 2022; Kaliba et al., 2018; Kimbi et al., 2020; Miriti et al., 2022; Sissoko et al., 2019; Smale et al., 2018; Tibamanya et al., 2022). Farmers prefer growing landraces over hybrids (Wanga et al., 2022) because landraces are believed to be more drought-tolerant and better adapted to marginal production conditions (Cavatassi et al., 2011). Farmers also grow traditional landraces to reduce costs and harness the benefits of locally evolved genetic traits (Mwololo, 2010). Ficiciyan et al. (2018) also observed that landraces can be resilient under harsh environmental conditions, and can achieve stable crop yield. In Ethiopia, low adoption of hybrid sorghum was attributed to lack of adaptive traits, short plant stature and small grain size (Mindaye et al., 2016).

Both grass and broadleaf weeds were recorded in the summer trial, suggesting that sorghum is associated with both broadleaf and grass weeds. A number of studies have shown that sorghum is associated with both grass and broadleaf weeds (Ferrell et al., 2022; Galon et al., 2018; Mamudu et al., 2019; Pandian et al., 2021; Tibugari et al., 2020a). In summer, most of the grass and broadleaf weeds that were recorded in the field were sparsely distributed and were minor weeds. However, in summer, two broadleaf weeds, A. conyzoides and R. scabra, which coincidentally have not been reported to be suppressed by sorghum allelopathy in Table 1, were dominant. This may suggests that the two weeds tolerate sorghum allelopathy. A study by Idu (2014) showed that root exudates and extracts of A. conyzoides actually inhibit sorghum growth by releasing phenolic allelochemicals into the soil rhizosphere.

In winter, no grass weeds were recorded and only a few broadleaf weeds were recorded. The absence of grass weeds and the presence of just a few broadleaf weeds in the winter-spring season might have been caused by seasonal dormancy. Most summer annual weeds do not germinate during winter because growth factors will not be favourable for their germination, growth and survival (Qasem, 2019). Although allelopathy studies have proved that sorgoleone suppresses broadleaf weed species compared to grass weeds (Alsaadawi et al., 2015; Uddin et al., 2010; 2013; 2014), the probability that sorgoleone produced by the sorghum accessions suppressed weeds in winter might be low. Under controlled conditions, Dayan (2006) found that low temperatures caused low sorgoleone synthesis. He established that optimum sorgoleone production occurred at temperatures between 25 to 35 °C, with maximum levels obtained at 30 °C. When we conducted the experiments, the temperatures at Panmure Experiment Station ranged from a mean minimum of 5 °C to about 20 °C, which were low.

Macia had significantly heavy heads in weeded plots compared to all the sorghum accessions. In contrast weeding significantly reduced head weight of IS9362. Unlike all the other sorghum accessions that were used in the study, Macia has undergone genetic improvement and, as reported by Saadan et al. (2000), large head size is one of its important useful characteristics. When 26 randomly selected farmers in northern Tanzania rated the sorghum varieties Pato, SV 1 and Macia for different characteristics that included earliness, grain yield and head size, they rated Macia as having an excellent head size, which was the best of all the three varieties. The result that IS9362, which produces fairly high quantities of sorgoleone (252.9 µg/mg r.f.w) produced heavier heads in unweeded than in weeded plots suggests that, IS9362 can highly compete for resources against weeds. IS9362 possibly has high capacity to capture more resources and limit resources that will be available for utilisation by weeds. It is not clear why weeding reduced head weight of IS9362. As reported by Fiorucci and Fankhauser (2017) plants are able to use multiple photosensory receptors to sense the existence of competitors, and once they detect competitors, they can adjust their growth and developmental strategies. The presence of weeds around the crop might have stimulated rapid canopy development and growth in height, allowing IS9362 canopy to intercept and absorb photosynthetically active radiation (PAR) for photosynthesis and growth. As reported by Bai et al. (2016) the capacity to absorb and convert PAR immediately reflects crop biomass productivity. The result that head weight of IS9362 was low in weeded plots compared to the head weight in unweeded plots may seem to defy logic. However, it may be important to note that the crop was hand weeded. It may be possible that accidental injury of the crop might have occurred while removing weeds close to the crop, resulting in weakening of the crop. Variation in competitive ability against weeds among sorghum cultivars offers opportunities to select and breed for competitive cultivars that can be adopted by farmers in integrated weed management programmes.

Although there was a significant sorghum accession ˟ weeding regime interaction on panicle weight, there was no sorghum accession ˟ weeding regime interaction effect on grain weight. This result suggests that high panicle weight may not always lead to high grain yield. It is therefore likely that some panicles were not productive. In a study on the interrelationships between panicle weight, grain yield, and grain yield components in oat (Avena sativa L.), Chapko and Brinkman (1991) found that high panicle weight was not consistently associated with high grain yield. Laza et al. (2004) also observed that large panicle is not always associated with high yield as large panicle often results in reduced panicle number and poor grain filling percentage. Our results therefore differ with findings by Omanya et al. (1997) who found that grain yield was positively and significantly correlated with panicle weight per plant when they studied variation for adaptability to dryland conditions in sorghum in Kenya.

The result that sorgoleone content and sorghum height had a significant moderate positive relationship in summer and a significant high positive relationship in winter may suggest that high sorgoleone content makes sorghum accessions grow tall. This can make sorghum intercept and absorb photosynthetically active radiation (PAR) for photosynthesis and growth, allowing the crop to compete against weeds for resources.

Effect of sorghum presence on weed density and weed biomass

Temperatures during summer and winter were ideal for sorghum germination and growth. Winter temperatures were slightly lower than summer temperatures. However, these temperatures were still within the optimum required for sorghum germination and growth. Sorghum germinates at temperatures ranging from (7 °C and 10 °C) and optimum growth and development can occur at temperatures ranging from 20 °C to 30 °C (DAFF 2010). Effective planting rainfall was only received in January, and the rains tailed off only two months later. This agrees with early warning reports by FAO. (2019) that predicted a delay in the onset of the rain season and moisture stress from November to March in Southern African countries such as eSwatini, Zambia and Zimbabwe. Erratic rains and shifts in rainfall patterns are associated with climate change (Davis, 2011; FAO., 2019). Sorghum, which tolerates drought (Mundia et al., 2019), can be an ideal crop to grow under such conditions.

Five grass and 12 broadleaf weed species were recorded in the experimental plots. All the five grass weed species and a few broadleaf weeds were confined to the summer season, while no grass weeds were recorded in winter. This suggests that in winter, the wetting and drying cycles that normally help to break weed seed dormancy (Zimdahl, 2007) were not adequate to induce germination of the weeds in winter. It is also possible that those weeds that were absent or that occurred in small numbers were suppressed by allelopathic compounds exuded by sorghum. For example, sorgoleone, which acts selectively on weeds (Nimbal et al., 1996), inhibits germination of certain weed species (Uddin et al., 2014).

The presence of sorghum significantly reduced A. conyzoides, R. scabra, minor weeds and total weed density in summer and A. conyzoides, A. hybridus, B. pilosa, R. scabra and S. alba densities in winter. Reduction in weed densities might have been caused by allelochemicals that are produced by sorghum. All the 11 sorghum accessions that were tested in the field produced different quantities of sorgoleone (Tibugari et al., 2019b) and therefore this compound might have contributed to the allelopathic inhibition of weed germination and emergence. Overhead irrigation water that was applied throughout the winter season, as well as rainfall that was experienced in summer might have washed water soluble allelopathic compounds (dhurrin and phenolic acids) from the shoots into the soil. Both water soluble and hydrophobic allelochemicals produced by sorghum can inhibit weed germination (Alsaadawi et al., 2015; Uddin et al., 2014). The presence of sorghum might also have suppressed weed density by shading weed seedlings in the understorey with its canopy. Additionally, applying basal and top-dressing fertilisers close to the crop row (Everaarts, 1993) as well as sorghum’s high nutrient (Sigua et al., 2018) and water efficiency (Ajeigbe et al., 2018) might have made sorghum more competitive, resulting in rapid sorghum growth and development at the expense of the weeds.

Results showed that there was a significant sorghum presence ˟ weeding regime interaction on A. conyzoides and R. scabra density in summer. There was also a significant sorghum presence ˟ weeding regime interaction on A. conyzoides, A. hybridus, and B. pilosa density in winter at 65 DAS, implying that the effect of sorghum presence varied with weeding regime. There was no difference in A. conyzoides and R. scabra density in summer and B. pilosa density in winter between sorghum presence and no sorghum when the plots were weeded. In contrast, in the unweeded treatments, sorghum absence had a significantly higher A. conyzoides and R. scabra density in summer and B. pilosa density in winter than where there was sorghum. These results suggest that disturbing the soil by weeding possibly weakened the activity of allelochemicals. Weeding possibly exposed dissolved water soluble allelochemicals to rapid vaporisation, degradation, leaching and mineralisation by soil microbes such that the critical concentration of allelochemicals capable of inhibiting weed germination and emergence was reduced. Blum (2002) reported that evapotranspiration could reduce phytotoxicity of allelochemicals. When Dayan (2006) studied the factors that regulate sorgoleone production, one of his findings was that exposure to light reduced the quantity of the compound by nearly 50%.

Three sorghum accessions (IS13807, IS14002 and IS35583) had similar S. alba density as the control treatment where no sorghum was planted, possibly because S. alba tolerated allelochemicals produced by the three sorghum accessions. On the other hand, eight sorghum accessions (IBS718, IS14003, IS19462, IS23342, IS9362, IS9409, IS9456 and Macia) caused significantly lower S. alba density than the control treatment where there was no sorghum, suggesting that the eight sorghum accessions possibly released allelochemicals that effectively suppressed germination, emergence and early growth of S. alba. Although IBS718 has low sorgoleone content, it may produce water soluble allelopathic compounds that suppress weed growth. A study by Kakar et al. (2023) showed that the phenolic acids p-Coumaric and protocatechuic acids may play an important role in the allelopathy of sweet sorghum. Where S. alba is a problematic weed, farmers may grow these eight sorghum accessions for its effective control.

The result that biomass of A. conyzoides in nine sorghum accessions (IBS718, IS13807, IS14003, IS19462, IS23342, IS35583, IS9362, IS9409 and IS9456) was similar to the control treatment where no sorghum was planted suggests that A. conyzoides is tolerant to allelochemicals produced by these sorghum accessions. It may also suggest that upon release into the rhizosphere, allelochemicals exuded by these sorghum accessions underwent rapid transformation that weakened their bioavailability and bioactivity. The result that IS14002 and Macia resulted in significantly higher A. conyzoides biomass than the control treatment suggests that allelochemicals from these sorghum accessions stimulated growth and development of A. conyzoides. The study found that all the 11 sorghum accessions had lower total weed biomass compared to the control treatment where no sorghum was planted. All the sorghum accessions possibly exuded allelochemicals that were sufficient to suppress total weed growth and development.

The interaction of sorghum presence and sorghum accession showed that only Macia had higher B. pilosa biomass than the control treatment where there was no sorghum planted. The interaction of sorghum presence and sorghum accession also showed that seven sorghum accessions (IBS718, IS14002, IS19462, IS23342, IS35583, IS9362 and IS9456) had similar B. pilosa biomass as the control treatment where no sorghum was planted. In contrast, IS13807, IS14003 and IS9409 had lower B. pilosa biomass than the control treatment where there was no sorghum planted, suggesting that these three sorghum accessions had higher allelopathic activity against B. pilosa compared to the other eight sorghum accessions. These results agree with findings by other scholars that there are cultivar differences in allelopathic activity (Alsaadawi et al., 2015; Tibugari et al. 2020c).

One sorghum accession, IS9456, had higher R. scabra biomass than the control treatment where there was no sorghum planted while all the other 10 sorghum accessions had similar R. scabra biomass as the control treatment where no sorghum was planted. These results suggest that possibly R. scabra was tolerant to sorghum allelopathy from the 10 sorghum accessions. The high R. scabra biomass that was recorded in IS9456 suggests that allelochemicals produced by this sorghum accession stimulated R. scabra biomass production. Reports that allelochemicals can cause hormesis have been made by other researchers (An et al., 1993; Duke et al., 2006; Ghassan et al., 2016; Viator et al., 2006).

The result that weeds differed in response to sorghum presence may suggest that not all weed species are susceptible to sorghum allelopathy. Weeds that thrive in the presence of sorghum may escape from being harmed by allelopathic compounds by absorbing and translocating fewer amounts of allelopathic compounds or by effectively degrading the allelochemicals to non-toxic levels (Dayan et al., 2010). This suggests that farmers will need to use other weed management techniques against weeds that are not suppressed by sorghum allelopathy.

Correlation analyses also showed that there was no significant relationship between sorgoleone production and weed density and biomass both in summer and winter. Therefore, other allelopathic compounds produced by sorghum (dhurrin and phenolic acids) may have contributed to the suppression of weed density and biomass.

It is still possible that there might have been minor allelopathic effects on the different parameters that we tested in weeds and sorghum. As argued by Ribeiro (2011) when parameters used to infer allelopathic effects, such as percentage and average time of seed germination, size, or biomass of the plant are analyzed individually, the global effects resulting from the cumulative effect of each parameter may be underestimated or completely ignored. Ribeiro also argues that it is unrealistic to expect that isolated parameters used to infer allelopathic effects used to infer allelopathic effects could be used to explain allelopathy, and this is one of the reasons why in many cases laboratory bioassays fail to predict responses in the field (Inderjit and Weston 2000). The author proposes that analyzing all PIAEs together as they occur in nature could lead to a more accurate analysis of what happens in the natural environment.

Conclusions and recommendations

The study investigated the effect of sorghum presence and weeding regime on sorghum emergence, final stand, height, panicle weight, grain weight, stover biomass, weed density and weed biomass under field conditions. The study also examined if these parameters could be correlated to sorgoleone production. The observation that weeding regime did not significantly affect percentage emergence, final crop stand, height, grain weight and stover biomass in summer and winter, suggests that sorghum may have an ability to withstand stress from weeds. The weak negative relationships between sorgoleone content and head weight and between sorgoleone content and grain weight in summer and winter suggests that, in the present study, sorgoleone played an insignificant role in enhancing head weight and grain weight. It is also possible that sorgoleone does not instantly influence yield upon its release from sorghum root hairs since it is strongly bound to soil particles, making its release into the soil rhizosphere very slow. Sorgoleone’s hydrophobicity, its strong sorption to soil colloids and its slow release from soil particles are ideal properties for the allelochemical’s soil persistence and weed suppression over an extended period, similar to long lasting herbicides such as Lockstar and Round Up Pro Active. This suggests the need to complement allelopathy with other weed control methods. However, farmers may need to complement allelopathy with other weed control methods for timely weed control. The presence of sorghum did not inhibit density and biomass of all weeds and therefore allelopathy still has to be complemented with other weed management techniques. The result that there was no correlation between sorgoleone production and weed density and biomass suggests that under field conditions, sorgoleone may not be actively involved in the allelopathic suppression of germination, emergence and growth of weeds. Rather, other compounds (dhurrin and phenolic acids) could be more actively involved. It is possible that inhibition of density and biomass in some weeds could have resulted from the ability of sorghum to outcompete the weeds for resources, or from shading of weeds in the understorey by the sorghum canopy. Future studies may investigate the uptake of both the water soluble and lipophilic allelopathic compounds by weeds under field conditions and relate the absorbed allelopathic compounds to the resultant damage symptoms.

Acknowledgements

The authors are thankful to staff and management at Panmure Experiment Station, including Mr Kiven Garutsa and Mr Dumisani Sibanda for providing resources and advice on the trials. The research was partially funded by the Govan Mbeki Research and Development Centre. The International Crops Research Institute for the Semi-Arid Tropics, based at Matopos Research Station, Bulawayo, Zimbabwe, provided the sorghum germplasm. Gloria Hoshiki, Naume Humbe and Zivanai Sigauke assisted with root excision of sorghum seedlings. Mr Cosmas Mutsimhu, Chief Analytical Chemist at the University of Zimbabwe’s School of Pharmacy, Pharmaceutical Laboratories assisted with all the HPLC-MS analysis in a seasoned manner.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data will be made available upon request.

Additional information

Notes on contributors

Handsen Tibugari

Handsen Tibugari is an Associate Professor of Crop Science, and Chairperson of the Department of Crop and Soil Sciences in the Faculty of Agricultural Sciences at Lupane State University in Zimbabwe. His research interests are in Integrated Weed Management.

Cornelius Chiduza

Cornelius Chiduza is a Professor of Agronomy and Head of Agronomy Department in the Faculty of Science and Agriculture at the University of Fort Hare in South Africa. His research interests include agronomy and conservation agriculture.