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Article

Irrigation Scheduling and Weed Management: A Sustainable Approach for Managing Broomrape and Other Weeds in Tomato Crop

1
Department of Weed Science and Botany, Faculty of Crop Protection Sciences, The University of Agriculture, Peshawar 25130, Pakistan
2
Department of Agriculture, University of Swabi, Swabi 94640, Pakistan
3
Department of Horticulture, Faculty of Crop Production Sciences, The University of Agriculture, Peshawar 25130, Pakistan
4
Department of Soil and Environmental Sciences, Faculty of Crop Production Sciences, The University of Agriculture, Peshawar 25130, Pakistan
5
Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy
*
Authors to whom correspondence should be addressed.
Horticulturae 2022, 8(8), 676; https://doi.org/10.3390/horticulturae8080676
Submission received: 18 June 2022 / Revised: 17 July 2022 / Accepted: 18 July 2022 / Published: 25 July 2022

Abstract

:
Broomrape (Orobanche cernua L.) is an obligate root parasitic weed that significantly reduces the qualitative and yield attributes of tomatoes globally. The efficient management of broomrape is challenging because of its complicated parasitic nature. Field trials were conducted to assess the influence of various irrigation scheduling and weed control strategies on broomrape, weed presence, and tomato productivity. The experiment was conducted with a randomized complete block design (RCBD) with a split-plot arrangement and was replicated three times. Three irrigation intervals (3, 6, and 9 days) were assigned to the main block, while sub-blocks including treatments and year were taken as the source of variance (year × irrigation timing × treatments). The experiment comprised sixteen treatments, including transparent polythene, black polythene, weedy check (Control), sole weeding of broomrape only, weeding of all weeds, weeding except broomrape, humic acid 25 kg ha−1+ copper oxychloride in single and split doses, copper oxychloride (1.5 kg a.i ha−1 in single and split doses), ammonium sulphate 200 kg ha−1 in single and split doses, copper sulfate (2 kg ha−1 in single/split doses), and glyphosate 48 SL (1.5 kg a.i ha−1) and pendimethalin 33 EC (1.44 kg a.i ha−1). The results revealed that among the various irrigation intervals, the highest broomrape intensity (4.34 plant−1) was observed with a9-day irrigation interval. Similarly, the highest weed density (35 m−2) resulted in a3-day irrigation interval. Furthermore, irrigation at a 6-day interval increased the plant height by 11%, fruit yield tons ha−1 by 24.9 %, and produced the highest cost/benefit ratio (CBR) of (1:4). Black polythene, transparent polythene, and pendimethalin reduced the weed density by 92%, 89%, and 84%;weed dry biomass by 97%, 95%, and 91%; and broomrape intensity by 67%, 77%, and 28%. Conversely, the plant height increased by 24%, 23%, and 23.6%; and fruit yield by 286%, 270%, and 191%; and had the highest CBR of 1:5, 1:4, and 1:4, respectively, as compared to the weedy check. Consequently, an increase in irrigation frequency increases other weed densities and decreases the broomrape intensity plant−1 of tomato. Therefore, black polythene could be recommended in a severely broomrape-infested field. Moreover, irrigation at 6-day intervals combined with pendimethalin and ammonium sulfate fertilizers revealed the lowest incidence of broomrape and other weeds and produced an economic yield.

1. Introduction

Tomato, technically known as Solanum lycopersicum (Mill.), belongs to the family Solanaceae, which is an important commercial vegetable crop cultivated worldwide, particularly in temperate climates [1]. It is a day-neutral plant and thus can be cultivated in any frost-free season [2]. However, it is more sensitive to frost and high temperatures and is best grown at temperatures between 18 and 32 °C [3]. Recent innovations in agricultural technologies and improved varieties provide tomatoes with resilience in diverse climatic conditions. It is globally cultivated in 178 countries across 4.7 million hectares of land, yielding about 177 M tons of fresh fruits annually [4]. The leading contributors are China, Turkey, the United States, India, and Egypt.
Pakistan ranked 33rd globally in tomato production and tomato is cultivated in a 55,258-hectare area, yielding 561,293 ha−1, with an average yield of 10.15 tons ha−1 [4]. The average yield per hectare is relatively low. Many factors contribute to the low productivity of tomatoes; nonetheless, weeds are a major biotic constraint, which causes significant yield reduction in tomato crops [1].Weeds resulted in a 75% reduction in tomato yield when compared with weed-free conditions [5]. The critical period of weed competition (CPWC) is the stage in the crop growth cycle in which weeds must be controlled to avoid yield losses. CPWC in tomatoes is very important for timely weed management to achieve an economical yield. The CPWC of tomato is estimated to be at about 3.3–5.8 weeks after transplantation (WAT) [6]. Nonetheless, the implementation of weed management practices after the critical period is uneconomical. Moreover, the degree of yield loss in tomato crops greatly depends on the type of weeds, duration, and intensity of infestation. Hence, timely integrated weed management practices could represent a feasible strategy for reducing weed infestations, particularly broomrape infection in tomato crops.
Broomrapes (Orobanche spp) are achlorophyllous obligate root parasitic weeds, belonging to the family Orobanchaceae. Almost 150 species of these weeds have been identified to affect vegetable crops globally [7]. The species reportedly infested a 2.6-million-hectare area in North Africa, and the Mediterranean region; in Asia, these weeds have led to a financial loss of USD 1.3–2.6 billion in solanaceous vegetables [8]. This weed directly contacts the host plant’s roots through the haustorium, absorbs water and nutrients from them, and considerably decreases the productivity and quality of tomato fruits. The cause of the broomrape epidemic could be its prolific seed production; they produce tiny seeds which can be easily dispersed through irrigation water and farm machinery with a lack of preventive and quarantine measures. Moreover, the mono-cropping of solanaceous host crops, particularly tomato and tobacco, considerably increases the incidence of broomrape species in Pakistan and causes severe yield losses in tomato. Additionally, the degree of yield losses depends on the climatic conditions, type of host plant, broomrape species, and intensity of infestation [9].
In Pakistan, the average yield per hectare for tomato is relatively low, particularly because of weeds, and specifically due to broomrape infestation. The efficient management of broomrape is very challenging because of its parasitic nature, prolific seed production, host specificity, and mono-cropping. Many researchers have extensively studied broomrape–tomato interaction to develop an effective and efficient management approach [10]. While several management strategies have been implemented, only a few of them are feasible and economical; still, there is a lack of information in the published literature about the efficient management of broomrape weed. Therefore, this study aimed to verify whether different irrigation intervals and weed management strategies can control the infestation of broomrape weed. This study also used ammonium sulfate for broomrape inhibition and developed a cost-effective weed control method to help farmers increase their tomato yield.

2. Materials and Methods

2.1. Experimental Site and Pedo-Climatic Conditions

Field trials were carried out during the growing seasons (2018 and 2019). The study area was situated in District Mardan, Pakistan (34°15′38″ N, 72°06′36″ E; 310 m above sea level (Figure 1)). District Mardan is a major tomato-producing area where tomato is cultivated on an area of 339 hectares, with a net production of 4431 tons and an average yield of 13 tons ha−1 [11]. The field soil was silty clay loam (sand 18%; silt 49%; clay 33%) in texture, with a pH of 7.75, non-saline in nature with an EC of 0.45 dS m−1, and a low organic matter content (0.54%); in addition, the soil was less fertile and had a nitrogen content of 0.07%, adequate availability of phosphorus (4.44 mg kg−1) and a high potassium content (120.2 mg kg−1). Weather data shows that the maximum and minimum mean temperatures during 2018 were 2.85 °C and 1.02 °C, which were higher than 2019, respectively, exhibiting a considerable variation of 1.93 °C in the mean temperature. Similarly, total rainfall during the growing season in 2019 was 174.7 mm higher than in 2018 (Figure 2).

2.1.1. Experimental Procedure

Determinate tomato seeds (Taj F1 Hybrid), with lot number: LTPS058B, were purchased from Suntech Agribusiness, Pakistan. These seeds possessed a 99% purity level with 90% germination rates. The average tomato fruit weight of this variety is 114 g with an average production of 12 tons ha−1 in Pakistan. In Pakistan, the growing season of tomato spans from January to June. We began with nursery bed preparation and seeds were sown at the rate of 296 g ha−1 for seedling growth during January; the nursery bed was covered with transparent polythene film to avoid frost injury, and the seedlings were transplanted during the second week of March. The field was ploughed extensively, leveled, and then prepared for raised beds (4.45 m2). The experiment was set up in Randomized Complete Block (RCBD) and replicated three times with a split-plot arrangement. The main block was assigned three irrigation timings of 3, 6, and 9 (days), while the sub-block was assigned 16 different weed management treatments. The area of each experimental unit (treatment) was 4.45 m2. Tomato seedlings (40 days old) were transplanted on March 7th and 15th, 2018 and 2019, respectively. The difference in the transplanting time was due to variations in the rainfall patterns between the two years (Figure 2). The blocks (replications) were kept at a distanceof 90 cm from each other. The main plots were separated by 50 cm and were further divided into subplots kept 50 cm apart from each other as well. The plant-to-plant and row-to-row distances were kept 30 cm and 90 cm respectively. Furrow irrigation was used to supply water and a complete fertilizer dose of NPK at a ratio of 120:80:80 kg ha−1 was applied 2 weeks after transplantation (WAT).

2.1.2. Weed Management Treatments

The experiment included sixteen treatments, viz, T1: black polythene, T2: transparent polythene, T3: weeding except broomrape, T4: weeding of broomrape only, T5: complete weeding, T6: copper oxychloride[manufacturer: Hextar: trade name: Shine, 50% wettable powder (WP)] rate: 1.5 kg ha−1 (single dose), T7: copper oxychloride as (split dose), T8: humic acid [manufacturer: Syngenta, trade name: Enrich, granular (G), active ingredient (HA 40%, K 7%)] rate: 25 kg ha−1 + copper oxychloride (single dose), T9: humic acid + copper oxychloride (split dose), T10: copper sulfate 2 kg ha−1 (single dose), T11: copper sulfate, (split dose), T12: ammonium sulfate [manufacturer: FMC, granular (G), formulation (N 21%, S 24%)], rate: 200 kg ha−1 (single dose), T13: ammonium sulfate (split dose), T14: Pendimethalin 33% emulsifiable concentrate (EC), (manufacturer: Engro), rate: 1.44 kg a.i ha−1, T15: Glyphosate 48% Soluble liquid (SL) (Manufacturer: FMC), rate: 1.5 kg a.i ha−1 and T16 control (weedy check).

2.1.3. Irrigation Scheduling and Treatment Application

Tomato was irrigated one week after transplantation (WAT) and on days 3, 6, and 9. Black and transparent polythene film was applied on moist soil before tomato transplantation. The film size was slightly longer to cover each respective experimental unit. All sides of the film were buried 6 inches deep inside the soil. Holes were made inside the film at an equal plant-to-plant distance and subsequently, tomato seedlings were transplanted. Pendimethalin was applied to the moist soil one week before seedlings transplantation. A Knapsack sprayer—a battery and manual hand-operated sprayer pump with a deflector nozzle—was used to spray herbicides/chemicals. Glyphosate was applied for post-emergence at 4 and 8 weeks after transplantation (WAT). Glyphosate is a non-selective and translocated herbicide.Thus, to avoid crop damage it was sprayed selectively on weeds between the rows and in the root zone of the crop with a deflector nozzle and a 30 cm wide protective cover. Humic acid, ammonium sulfate, copper oxychloride, and copper sulfate were applied and hand weeding was performed at 4 and 8 WAT in single and split doses, respectively.

2.2. Measurements and Data Collection

2.2.1. Weed Density

The weed density reflects the extent of competition with the crop. The quadrate method was used to record the weed density. The quadrate (0.5 m2) was thrown three times randomly in each treatment, and the weeds inside it were recorded. The mean data of quadrates for each treatment were converted to weed density using the following formula of Holm et al. [12].
Weed   Density   m 2   =   Total   No .   of   individual   of   a   species   in   all   quadrates Total   No .   of   quadrates

2.2.2. Broomrape Intensity of Attack Plant−1 of Tomato

Data on broomrape intensity of attack were recorded by classifying tomato plants according to the number of broomrapes attached to the plant. Final data of (I.A) for each main and sub-plot were calculated using the following formula of Abdel-Kader et al. and Chastagner et al. [13,14].
Broomrape   Intensity   of   attack   ( I . A )   =     ( n × c ) N
where I.A = Intensity of attack, n = Number of infected plants per plot, c = Category number, C1 = two broomrape, C2 = four broomrape, C3 = six broomrape, C4 = eight broomrape, C5 = more than eight broomrape plant−1 of tomato, and N = Total number of plants examined.

2.2.3. Dry Weed Biomass

The collected weed fresh biomass was dried in an oven at 65 degrees Celsius for 72 h, and the data were converted into dry weed biomass kg ha−1.

2.2.4. Plant Height, Number of Fruits Plant−1 of Tomato and Fruit Yield

A measuring tape was used to measure the height of tomato plants from the ground level to the tip of the main stem. Plant height data were collected from five randomly selected plants at the early fruiting stage, and an average plant height was calculated. Total numbers of fruit were recorded in each main-plot and sub-plot treatments and then the average number of fruits was computed. Tomato fruits were picked six times during the growing season from all the randomly selected plants. The fruits were weighed and the average yield was recorded. The cumulative fruit yield was computed using the following equation:
Tomato   fruit   yield   ( t   ha 1 )   =     Fruits   yield   from   net   plot   ( kg ) Area   harvested   ( m 2 ) × 10,000

2.2.5. Cost/Benefit Ratio

The cost/benefit ratio for each treatment and irrigation interval was calculated using the equation below.
Cos t / Benefit   Ratio   = Added   income Added   cos t
where added income was calculated as the average annual market price of tomato fruits (tones) and added cost was computed as the sum of inputs (field rent, nursery preparation, insecticides, herbicides, polythene, labor, seed costs, irrigation, etc.) [15].

2.2.6. Statistical Analysis

The experimental data for each parameter were individually analyzed using a combined year Analysis of Variance (ANOVA) procedure with Statistix 8.1 software (Analytical Software, Tallahassee, FL, USA). Where the F data were found to be significant, and the means were separated using the Least significant differences (LSD) test at a 5% probability level as performed by Steel and Torrie [16]. GraphPad Prism 6 software was used for the graphical presentation of the mean data and interactions data for each parameter (GraphPad Software Inc., San Diego, CA, USA).

3. Results

3.1. Weed Density

The effect of various irrigation intervals and treatments significantly (p ≤ 0.05) influenced the weed density m−2 (Figure 3). Data concerning various irrigation intervals revealed the highest weed density (35.4 m−2) at the 3 days irrigation interval while the lowest weed density (25.9 m−2) was found in irrigation at the 9-day interval. Among various weed control treatments, the data show that the lowest weed density (3.8 m−2) was found in black plastic which is closely followed by transparent plastic having (5.7 m−2) weed density while the highest weed density (50.1 m−2) was noted in the weedy check. The effect of year was found to be significant on weed density, and data showed that the lowest weed density was obtained in 2018 while the highest weed density was observed during 2018. Results further revealed that various interactions significantly affect weed density (Figure 4). Moreover, the interaction of 9 days irrigation interval × black polythene produced the lowest weed density. Moreover, the maximum weed density was produced at 3 days irrigation × weedy check for both years.

3.2. Broomrape Intensity of Attack Plant−1 of Tomato

The broomrape intensity was significantly (p ≤ 0.05) affected by various irrigation intervals and weed management practices (Figure 5). Among the irrigation intervals, the maximum broomrape intensity (4.34) was recorded at the 9 days irrigation interval, while minimum broomrape intensity (0.60) was found at the 3 days irrigation interval. Data concerning weed management treatments revealed that the lowest broomrape intensity (0.78) was obtained in the transparent polythene followed by black polythene with a broomrape intensity of 1.11, while the highest broomrape intensity (3.39) was noted in the control (weedy check). Year as a source of variance was significant, whereas the broomrape intensity during 2018 was significantly higher than 2019. Likewise, various interactions significantly affected broomrape intensity (Figure 6). Moreover, among the irrigation × treatments interactions, the lowest broomrape intensity was recorded at the 3 days irrigation interval × black polythene, while the highest was produced at 9 days irrigation × weedy check.

3.3. Dry Weeds Biomass

Various irrigation intervals and treatments significantly (p ≤ 0.05) influenced the weed dry biomass (Figure 7). The highest dry weed biomass (1440.67 kg ha−1) was produced at the 6 days irrigation interval which was statistically on par with the biomass produced at the 3 days irrigation interval, while the lowest dry weed biomass (894.79 kg ha−1) was recorded at the 9 days irrigation interval. Among the various weed management treatments, the lowest dry biomass (265.35 kg ha−1) was obtained using the black plastic treatment followed by transparent plastic with dry weed biomass of 397.97 kg ha−1, while the highest weed dry biomass (8015.05 kg ha−1) was found in the weedy check. Year as a source of variance significantly influenced the weed dry biomass. Various interactions significantly affected weed dry biomass (Figure 8). Moreover, the interaction of the 9 days irrigation interval × black polythene resulted in the lowest dry weed biomass, while the highest dry weed biomass was noted at 3 days irrigation × weedy check for both years.

3.4. Plant Height

The statistical analysis shows that different irrigation intervals and treatments significantly (p < 0.05) influenced the plant height of tomato (Figure 9). Maximum plant height (94.44 cm) was recorded at the 6 days irrigation interval followed by the 3 days irrigation interval, with a plant height of 90.35 cm, while the lowest plant height (84.43 cm) was recorded at the 9 days irrigation interval. Among various weed management treatments, black polythene produced taller tomato plants (98.1 cm) followed by pendimethalin and transparent polythene, leading to a plant height of 97.6, 96.8, and 96.6 cm, respectively, which were statistically comparable values, while the lowest plant height (74.6 cm) was observed in the weedy check. Year as a source of variance and the interactions significantly influenced the plant height of tomato. However, the interaction of 6 days irrigation interval × black polythene produced taller tomato plants (Figure 10).

3.5. Number of Fruits Plant−1 of Tomato

The statistical analysis of the data revealed that different irrigation intervals and treatments significantly (p ≤ 0.05) influenced the number of fruits plant−1 of tomato (Figure 11). The maximum number of fruits (15.48) was noted at the 6 days irrigation interval, while the lowest fruit numbers of 11.95 and 12.24 were noted at the 3 and 9 days irrigation intervals, respectively, which were statistically comparable. Among the various weed control treatments, black polythene obtained the highest number of fruits (22.11), closely followed by transparent plastic (20.89), whereas the minimum fruit numbers (7.78) were found in the weedy check treatment. The number of fruits produced by tomato plants was considerably influenced by the year as a source of variation. Moreover, the highest fruit numbers were obtained in 2018. Various interactions significantly influenced the number of fruit plants−1 of tomato (Figure 12). However, the interaction of black polythene × 6-day irrigation interval produced the maximum number of fruits plant−1.

3.6. Fruit Yield of Tomato

The fruit yield of tomato was significantly influenced by various irrigation intervals and different treatments. The highest fruit yield (12.55 tons ha−1) was recorded at the 6 days irrigation interval, while the lowest yield (9.53 and 9.63 tons ha−1) was produced during the 3 and 9 days irrigation intervals which were statistically similar (Figure 13). The treatments showed that black polythene produced the highest yield (17.85 tons ha−1) followed by pendimethalin and transparent polythene, while the lowest yield (6.23 tons ha−1) was noted in the weedy check treatment. Year as a source of variance and various interactions significantly affect the fruit yield of tomato (Figure 14). Furthermore, 6 days irrigation × black polythene produced the maximum fruit yield.

3.7. Cost/Benefit Ratio

Various irrigation intervals and treatments significantly affect the cost/benefit ratio. The highest CBR values (1:4.23) were recorded for the 6 days irrigation interval, while the lowest CBR values (1:3.10) were noted for the 3 days irrigation interval (Figure 15). Moreover, the broomrape intensity of 8.7 plant−1 found in the 9 days irrigation interval causes economic losses of 36.43%. Furthermore, the economic loss at a broomrape intensity of 23.8 plant−1 could be predicted as 100%. Similarly, among the treatments, the highest CBR (1:5.23) was obtained for black polythene followed by pendimethalin with CBR (1:4.48), whereas the lowest CBR (1:2.41) was obtained in the weedy check as shown in Figure 15a. Both the growing seasons and various interactions significantly affected the CBR values (Figure 16). Net Income% vs Economic Losses% for all the weed management treatments is presented in Figure 17a. Moreover, the lowest broomrape intensity of 4.5 plant−1 was recorded at the 3 days irrigation interval which resulted in 19.4% economic losses (Figure 17b). Likewise, other weeds at a 35.36 m−2 density at the 3 days irrigation interval caused yield losses of 45.9%, 33%, and 37% at 6 and 9 days irrigation intervals (Figure 17c). Furthermore, the highest CBR was achieved during the year 2018 compared to 2019. Additionally, the highest CBR values were recorded for 6 days irrigation interval × black polythene during the year 2018, and 6 days irrigation interval × pendimethalin during 2019.

4. Discussion

We observed that the 3 days irrigation interval produced the highest weed density m−2 compared to the 9 and 6 days irrigation interval. This might be due to the high moisture availability in the soil which encouraged weed germination and increased weed composition. In contrast, the lowest weed density m−2 produced by the 9 days irrigation interval could be due to the low soil moisture content and drought stress. Frequent irrigation enhanced weed composition in the field [17]. Moreover, 120% evapotranspiration (ET) increased the weed count m2, whereas a decrease in the irrigation at 60% (ET) reduced the weed count m2 [18]. Moreover, irrigation at the 6 days interval could be optimum for tomato crops where the weeds could also be precisely managed. However, black polythene significantly suppressed weeds. Much of the evidence supports that black polythene had a lower weed count [19,20]. Hence, black polythene is an effective weed management approach and can be suggested for use in broomrape and other weeds control in tomato crop.
Likewise, the results also indicated that a decrease in the irrigation interval decreased the broomrape intensity of the plant−1. In addition, irrigation at a 6 days interval is adequate for tomato crop and broomrape incidence can be ecologically managed. Among the treatments, black/transparent polythene, ammonium sulfates (split doses), and pendimethalin substantially reduced the broomrape incidence in tomato. This might be because plastic mulch increased soil temperature and consequently decreased broomrape and other weeds’ infestation. Similar studies show that transparent polythene eradicates broomrape and also prevents herbicide contamination [21,22]. Conversely, transparent polythene seems to be ineffective in the control of other weeds, particularly C4 physiology weeds, i.e., Cyperus rotundus, and Sorghumhalepense which are tolerant to high temperatures. In addition, transparent polythene also encourages summer weeds during the late winter. Consequently, the 6 days irrigation interval combined with black polythene considerably reduced the broomrape intensity in tomato crops.
The data indicated that a decrease in irrigation intervals increases the weeds count m−2 which ultimately increases the weed dry biomass m−2. A previous study shows that frequent irrigation considerably increases the weed biomass [17]. Furthermore, the biomass of weeds is precisely proportional to the loss in crop biomass [9,23]. Hence, the greater the weed infestation, the greater the weed biomass which will reduce the crop yield correspondingly. Moreover, black polythene followed by pendimethalin significantly reduced weeds biomass. Furthermore, black polythene mulch is a long-term weed control strategy, which suppresses weed growth throughout the crop growing season. As suggested previously, the polythene mulches reduced 98% of weed biomass [24].
Plant height is a good index for assessing tomato growth in response to stress. Weeds infestation and inadequate irrigation practices cause stress in plants, which affects the growth dynamics of tomato. Among the various irrigation practices, the 6 days irrigation interval produced taller plants than the 3 and 9 days irrigation intervals. Moreover, irrigation at the 3 days interval caused water saturation, whereas the 9 days irrigation interval was extensive enough to cause water stress symptoms in tomato. Consequently, either an unprecedented increase or decrease in irrigation frequency as opposed to optimum irrigation practices might affect the growth and plant height of tomato. It was previously reported that over-irrigation significantly reduced the plant height of tomato [25]. All the weed management treatments produced taller plants compared to the weedy check. Furthermore, taller plants harvest more sunlight and attain higher growth and productivity. In contrast, the dwarf plant detected in the control (weedy check) could be a result of the higher weed incidence. Consequently, black/transparent polythene, ammonium sulfate fertilizers, and pendimethalin along with 6 days irrigation intervals produced taller and healthier tomato plants.
The number of fruits plant−1 is a good index for predicting the final productivity of tomato. The results for irrigation practices revealed that a 6 days irrigation interval produced a higher number of fruits than the 3 and 9 days intervals. Additionally, the 3 days interval caused water saturation; furthermore, highly humid soil during the rainy season makes tomato vulnerable to fungal infection and reduces fruiting. Likewise, the lowest fruit number plant−1 at the 9 days irrigation interval might be due to the water stress and high broomrape incidence. Hence, our two-year study revealed that irrigation at a 6 days interval is optimal for tomato plants to produce higher fruit numbers. Previous reports demonstrated that a 6 days irrigation interval ensures maximum fruit numbers as opposed to 2 and 8 days irrigation intervals [25]. Again, the black polythene produced maximum fruit numbers. Our results are consistent with previous findings [26,27,28].
The final productivity of tomato was also higher at the 6 days interval. Moreover, any drastic increase or decrease in the irrigation regime or variation in weather conditions reduces tomato growth and productivity [29]. Moreover, appropriate irrigation timing is necessary for high-yield and quality vegetables [30]. The yield tons ha−1 is always higher when there is less weed interference. Moreover, evidence suggested that the solarization approach, particularly the black polythene, increased under soil temperature which suppressed weeds and also prevented sunlight penetration, which was required for weed growth [31]. These observations are in accordance with the previous reports stating that the highest yield and quality of fruit was obtained in tomato grown under plastic mulches [32].
Among the irrigation practices, the 6 days irrigation interval was cost-effective and an eco-friendly strategy for broomrape management in tomato. The results justify that at the lowest weed density of 25 m−2, the maximum economic losses at the 9 days irrigation interval could be due to water stress. Similarly, the 3 days’ irrigation interval also led to water saturation during the rainy season and negatively affected tomato growth. Moreover, 3 days of irrigation had the highest weed density and were also expensive in terms of water management. The treatment of black polythene was more economical than transparent polythene which failed to control perennial weeds, i.e., Cyperus rotundus and Sorghum helapense. Furthermore, the light penetration through transparent polythene increased the temperature during late winter which alleviated the early emergence of summer weeds. An economic analysis of the results further highlighted that a broomrape intensity of 3 plant−1 of tomato caused 20.18% in terms of economic losses. Moreover, the predicted economic losses could be 100% or whole crop failure could even occur at 12–16 broomrape intensity plant−1. Likewise, the average economic loss in tomato due to all other weeds at 33 weed density m−2 was 38.73%. Hence, black polythene was economical because of its highest weed control efficiency followed by pendimethalin which controlled all weeds except the broomrape. Furthermore, the combination of pendimethalin with the 6 days irrigation interval proved economical. Overall, the CBR values indicate that black polythene is more economical in arid conditions, which could conserve irrigation water and also suppress weeds growth. Previous findings stated that plastic mulch is a successful weed management approach for achieving the highest revenue [33]. Hence, combining the 6 days irrigation interval with black polythene or pendimethalin is an economical weed control strategy for tomato crop.
The results for weeds, broomrape, and tomato agronomic attributes show a significant response in both the studied years and their interactions. The reason for the significant variation in weed composition and tomato growth performance during both the growing seasons could be due to the substantial variation in the weather conditions. Moreover, the average temperature during 2018 was 1.93 °C higher than 2019; moreover, the average precipitation was 174.70 mm higher in 2019 than in 2018. Interestingly, the difference in the weather conditions was prominent which might individually or collectively have affected the irrigation scheduling, treatment performance, weed composition, broomrape incidence, and tomato yield attributes. Earlier studies suggested that weather conditions and soil fertility gradients affected the weed composition, morphological traits as well as final productivity of tomato crop [17]. Furthermore, the interaction among the 6 days irrigation interval × black polythene followed by pendimethalin resulted in a higher yield during both the growing season.

5. Conclusions

Based on the findings, it can be concluded that the irrigation frequency and weed management treatments are agronomic factors that could alleviate tomato from weed pressure, particularly broomrape infestation, and ultimately increase tomato productivity. The broomrape incidence showed a significant decline with decreasing irrigation intervals; however, other weeds’ density considerably increased with decreasing irrigation intervals. Moreover, the yield loss caused by the broomrape alone was higher. Among all the treatments, the broomrape incidence was lowest in the transparent polythene.However, the overall weed control efficiency of black polythene was higher and more cost-effective. The order of revenue resulting for treatments from highest to lowest was as follows: black polythene > pendimethalin > transparent polythene. The black polythene mulch was more cost-effective at a broomrape intensity of attack I.A > 8 plant−1 of tomato. A broomrape intensity of< 8 plant−1 and irrigation at a 6 days interval × pendimethalin resulted in a profitable yield. Additionally, black polythene could also conserve soil moisture which might reduce the number of required irrigations in an arid region and also suppress weeds. Consequently, our two-year field study findings revealed that a combination of a 6 days irrigation interval × black polythene, pendimethalin, and glyphosate, hand weeding and the application of ammonium sulfate eradicate broomrape and other weeds and enhance tomato yield. These outcomes are also very beneficial for areas where broomrape infestation is higher.

Author Contributions

Conceptualization, M.A.K. and M.F.; methodology, M.A.K. and M.F.; software, M.F., M.A.K., H.K. and B.G.; validation, A.J., M.F. and F.W.; formal analysis, M.F. and M.A.K.; investigation, M.A.K., A.M.K. and M.F.; resources, M.A.K.; data curation, M.F. and M.A.K.; writing—original draft preparation, M.F., M.A.K.,A.J. and F.W.; writing—review and editing, M.F., A.J., M.A.K. and F.W.; visualization, M.F.; supervision, M.A.K. and A.M.K.; project administration, M.A.K.; funding acquisition, A.M., A.J. and M.A.K. All authors have read and agreed to the published version of the manuscript.

Funding

This work was carried out as part of a research project on “Integrated approaches to manage Broomrape (Orobanche sp.) in major cash crops in KPK and Balochistan Provinces, Pakistan. This project was sponsored by USAID under the Agricultural Innovation Program (AIP) for Pakistan, CIMMYT, Pakistan Agricultural Research Council (PARC), and the University of Brescia by funding of Dr. Andrea Mastinu.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The technical support provided by the faculty at the Department of Weed Science & Botany for this study is greatly appreciated. The authors would like to thank Muhammad Farhan Saeed and Adil Mihoub for constructive criticism and for improving the language of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Figure 1. Study area map. (Adopted from Fawad and Khan [9]).
Figure 1. Study area map. (Adopted from Fawad and Khan [9]).
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Figure 2. Monthly mean Rainfall (mm) and temperature (°C) of the study area.
Figure 2. Monthly mean Rainfall (mm) and temperature (°C) of the study area.
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Figure 3. Response of weed density (m−2) to various irrigation intervals and weed management treatments. (a) Effect of treatments on weed density. (b) Effect of irrigation intervals on weed density. (c) Effect of different years on weed density. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at 5% level of probability.
Figure 3. Response of weed density (m−2) to various irrigation intervals and weed management treatments. (a) Effect of treatments on weed density. (b) Effect of irrigation intervals on weed density. (c) Effect of different years on weed density. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at 5% level of probability.
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Figure 4. Influence of various interactions on weed density (m−2). (a) Interaction effect of year × treatments on weed density. (b) Interaction effect of irrigation × treatments on weed density. (c) Interaction effect of year × irrigation × treatments on weed density.
Figure 4. Influence of various interactions on weed density (m−2). (a) Interaction effect of year × treatments on weed density. (b) Interaction effect of irrigation × treatments on weed density. (c) Interaction effect of year × irrigation × treatments on weed density.
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Figure 5. Response of broomrape intensity of attack plant−1 of tomato to various irrigation intervals and weed management treatments. (a) Effect of various treatments on broomrape intensity of attack. (b) Effect of Irrigation intervals on broomrape intensity of the attack. (c) Influence of years on broomrape intensity of the attack. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability.
Figure 5. Response of broomrape intensity of attack plant−1 of tomato to various irrigation intervals and weed management treatments. (a) Effect of various treatments on broomrape intensity of attack. (b) Effect of Irrigation intervals on broomrape intensity of the attack. (c) Influence of years on broomrape intensity of the attack. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability.
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Figure 6. Influence of various interactions on broomrape intensity plant−1 of tomato. (a) Interaction of year × treatments on broomrape intensity. (b) Interaction of year × irrigation on broomrape intensity. (c) Interaction of irrigation × treatments on broomrape intensity.
Figure 6. Influence of various interactions on broomrape intensity plant−1 of tomato. (a) Interaction of year × treatments on broomrape intensity. (b) Interaction of year × irrigation on broomrape intensity. (c) Interaction of irrigation × treatments on broomrape intensity.
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Figure 7. Influence of various irrigation intervals, weed management treatments, and years on dry weeds biomass (kg ha−1). (a) Effect of treatments on dry weed biomass. (b) Effect of irrigation intervals on dry weed biomass. (c) Effect of different years on dry weed biomass. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability.
Figure 7. Influence of various irrigation intervals, weed management treatments, and years on dry weeds biomass (kg ha−1). (a) Effect of treatments on dry weed biomass. (b) Effect of irrigation intervals on dry weed biomass. (c) Effect of different years on dry weed biomass. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability.
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Figure 8. Impact of various interactions on dry weeds biomass (kg ha−1). (a) Interaction of year × treatments on dry weed biomass. (b) Interaction of irrigation × treatments on dry weed biomass. (c) Interaction of year × irrigation × treatments on dry weed biomass.
Figure 8. Impact of various interactions on dry weeds biomass (kg ha−1). (a) Interaction of year × treatments on dry weed biomass. (b) Interaction of irrigation × treatments on dry weed biomass. (c) Interaction of year × irrigation × treatments on dry weed biomass.
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Figure 9. Impact of irrigation intervals and weed management treatments and years on plant height (cm) of tomato. (a) Effect of various treatments on plant height of tomato. (b) Effect of different irrigation intervals on plant height of tomato. (c) Impact of years on plant height of tomato. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability.
Figure 9. Impact of irrigation intervals and weed management treatments and years on plant height (cm) of tomato. (a) Effect of various treatments on plant height of tomato. (b) Effect of different irrigation intervals on plant height of tomato. (c) Impact of years on plant height of tomato. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability.
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Figure 10. Influence of various interactions on plant height of tomato. (a) Interaction effect of year × treatments on plant height of tomato. (b) Interaction of year × irrigation effect on plant height of tomato. (c) Interaction effect of irrigation × treatments on plant height of tomato. (d) Interaction of year × irrigation × treatments on plant height of tomato.
Figure 10. Influence of various interactions on plant height of tomato. (a) Interaction effect of year × treatments on plant height of tomato. (b) Interaction of year × irrigation effect on plant height of tomato. (c) Interaction effect of irrigation × treatments on plant height of tomato. (d) Interaction of year × irrigation × treatments on plant height of tomato.
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Figure 11. Effect of irrigation intervals and weed management treatments on the number of fruits plant−1 of tomato. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability. (a) Effect of treatments on the number of fruits plant−1 of tomato. (b) Effect of irrigation intervals on the number of fruits plant−1 of tomato. (c) Effect of different years on the number of fruits plant−1 of tomato.
Figure 11. Effect of irrigation intervals and weed management treatments on the number of fruits plant−1 of tomato. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability. (a) Effect of treatments on the number of fruits plant−1 of tomato. (b) Effect of irrigation intervals on the number of fruits plant−1 of tomato. (c) Effect of different years on the number of fruits plant−1 of tomato.
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Figure 12. Impact of various interactions on the number of fruits plant−1 of tomato. (a) Interaction effect of year × treatments on the number of fruits plant−1. (b) Interaction effect of year × irrigation number of fruits plant−1. (c) Interaction effect of irrigation × treatments on the number of fruits plant−1. (d) Interaction effect of year × irrigation × treatments on the number of fruits plant−1.
Figure 12. Impact of various interactions on the number of fruits plant−1 of tomato. (a) Interaction effect of year × treatments on the number of fruits plant−1. (b) Interaction effect of year × irrigation number of fruits plant−1. (c) Interaction effect of irrigation × treatments on the number of fruits plant−1. (d) Interaction effect of year × irrigation × treatments on the number of fruits plant−1.
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Figure 13. Effect of irrigation intervals and weed management treatments on net fruit yield of tomato. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability. (a) Effect of treatments on net fruit yield of tomato. (b) Effect of irrigation intervals on net fruit yield of tomato. (c) Effect of different years on net fruit yield of tomato.
Figure 13. Effect of irrigation intervals and weed management treatments on net fruit yield of tomato. Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability. (a) Effect of treatments on net fruit yield of tomato. (b) Effect of irrigation intervals on net fruit yield of tomato. (c) Effect of different years on net fruit yield of tomato.
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Figure 14. Influence of various interactions on tomato fruit yield tons ha−1 of tomato. (a) Interaction effect of year × treatments on tomato fruit yield. (b) Interaction effect of year × irrigation tomato on fruit yield. (c) Interaction effect of irrigation × treatments on tomato fruit yield.
Figure 14. Influence of various interactions on tomato fruit yield tons ha−1 of tomato. (a) Interaction effect of year × treatments on tomato fruit yield. (b) Interaction effect of year × irrigation tomato on fruit yield. (c) Interaction effect of irrigation × treatments on tomato fruit yield.
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Figure 15. Effect of irrigation intervals and weed management treatments on cost/benefit ratio (CBR). Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability. (a) Effect of treatments on CBR. (b) Effect of irrigation intervals on CBR. (c) Effect of different years on CBR.
Figure 15. Effect of irrigation intervals and weed management treatments on cost/benefit ratio (CBR). Based on the Least significant difference test, line and column ± standard error followed by different alphabetical letters are significantly different from each other at a 5% level of probability. (a) Effect of treatments on CBR. (b) Effect of irrigation intervals on CBR. (c) Effect of different years on CBR.
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Figure 16. Impact of various interactions on cost/benefit ratio. (a) Interaction effect of year × treatments on CBR. (b) Interaction effect of year × irrigation on CBR. (c) Interaction effect of irrigation × treatments on CBR.
Figure 16. Impact of various interactions on cost/benefit ratio. (a) Interaction effect of year × treatments on CBR. (b) Interaction effect of year × irrigation on CBR. (c) Interaction effect of irrigation × treatments on CBR.
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Figure 17. Net income vs economic losses% (a). Horizental red-color line in (a) shows the income level of top five treatments, above the red line indicates highest income and vice versa. Five different arrows, categorized in four different colors shows the highest income. BLP: dark-green color arrow indicates the highest income, followed by WAW: blue-color arrow, PE: light-green color arrow, where TRP and GL with red-color arrow indicated lowest income than BLP, WAW and PE respectively. Impact of various irrigation intervals on broomrape intensity plant−1 and economic losses% (b). Influence of various irrigation intervals on weed density m−2 and economic losses% (c). BLP: Black plastic; TRP: Transparent plastic; WEB: Weeding except broomrape; WOB: Sole Weeding of broomrape; WAW: Weeding of all weeds; COF: Copper oxychloride (Single dose) @ 2kg ha−1; COS: Copper oxychloride (Split doses); COHF: Copper oxychoride + Humic acid (Single dose); COHS: Copper oxychoride + HA (split doses); CSF: Copper sulphate (single dose) @ 2kg; CSS: Copper sulphate (split doses); AF: Ammonium sulphate (single dose); AS: Ammonium (split doses); PE: Pendimethaline @ 1.4 a.i ha−1; GL: Glyphosate48 SL @ 1.5 a.i ha−1; WC: Weedy check (Control).
Figure 17. Net income vs economic losses% (a). Horizental red-color line in (a) shows the income level of top five treatments, above the red line indicates highest income and vice versa. Five different arrows, categorized in four different colors shows the highest income. BLP: dark-green color arrow indicates the highest income, followed by WAW: blue-color arrow, PE: light-green color arrow, where TRP and GL with red-color arrow indicated lowest income than BLP, WAW and PE respectively. Impact of various irrigation intervals on broomrape intensity plant−1 and economic losses% (b). Influence of various irrigation intervals on weed density m−2 and economic losses% (c). BLP: Black plastic; TRP: Transparent plastic; WEB: Weeding except broomrape; WOB: Sole Weeding of broomrape; WAW: Weeding of all weeds; COF: Copper oxychloride (Single dose) @ 2kg ha−1; COS: Copper oxychloride (Split doses); COHF: Copper oxychoride + Humic acid (Single dose); COHS: Copper oxychoride + HA (split doses); CSF: Copper sulphate (single dose) @ 2kg; CSS: Copper sulphate (split doses); AF: Ammonium sulphate (single dose); AS: Ammonium (split doses); PE: Pendimethaline @ 1.4 a.i ha−1; GL: Glyphosate48 SL @ 1.5 a.i ha−1; WC: Weedy check (Control).
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Fawad, M.; Khan, M.A.; Wahid, F.; Khan, H.; Gul, B.; Khattak, A.M.; Jamal, A.; Mastinu, A. Irrigation Scheduling and Weed Management: A Sustainable Approach for Managing Broomrape and Other Weeds in Tomato Crop. Horticulturae 2022, 8, 676. https://doi.org/10.3390/horticulturae8080676

AMA Style

Fawad M, Khan MA, Wahid F, Khan H, Gul B, Khattak AM, Jamal A, Mastinu A. Irrigation Scheduling and Weed Management: A Sustainable Approach for Managing Broomrape and Other Weeds in Tomato Crop. Horticulturae. 2022; 8(8):676. https://doi.org/10.3390/horticulturae8080676

Chicago/Turabian Style

Fawad, Muhammad, Muhammad Azim Khan, Fazli Wahid, Haroon Khan, Bakhtiar Gul, Abdul Mateen Khattak, Aftab Jamal, and Andrea Mastinu. 2022. "Irrigation Scheduling and Weed Management: A Sustainable Approach for Managing Broomrape and Other Weeds in Tomato Crop" Horticulturae 8, no. 8: 676. https://doi.org/10.3390/horticulturae8080676

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