Colored plastic mulch impacts on soil properties, weed density and crop productivity: A Metanalysis

Colored plastic mulch impacts on soil properties, weed density and crop productivity: A Metanalysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Colored plastic mulch impacts on soil properties, weed density and crop productivity: A Metanalysis Asanda Sokombela, Ashwell Rungano Ndhlala, Moshibudi Paulina Bopape-Mabapa, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5951398/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted 6 You are reading this latest preprint version Abstract Soil degradation, climate change, and water scarcity worsen the declining crop productivity. Plastic mulches provide a sustainable solution, yet comprehensive evaluations of their effects, particularly in vegetable production, remain limited. This meta-analysis synthesizes 97 studies and 789 observations across 25 vegetable species to assess the influence of plastic mulch colour on crop yields and soil properties. Ten plastic mulch colors were analyzed: black, blue, green, gray, yellow, transparent, white, silver, brown, and red. Results show that all mulch colors improved crop productivity and soil parameters compared to non-mulched soil. Green (ES = 5.73, CI = 3.92–7.93), transparent (ES = 6.52, CI = 5.17–7.87), and black (ES = 1.95, CI = 1.49–2.42) mulches produced the highest significant increase in yield, plant height, and stem diameter, respectively. The highest reduction in weed biomass occurred with red mulch (ES = -9.04, CI = -13.33–-4.76). Increases in soil temperature and water use efficiency were noted from black (ES = 0.82, CI = 0.69–0.94) and silver (ES = 0.68, CI = -3.16–4.53), while the black (ES = 0.19, CI = 0.03–0.35), blue (ES = 2.62, CI = 0.44–4.80), and gray (ES = 2.03, CI = 0.06–4) mulches exhibited improved soil organic carbon, pH, total nitrogen, available phosphorus, and potassium, respectively. Besides black, the impacts of other colors are still under-explored, which limits the understanding of their effects on soil properties. Further studies are essential, as soil chemical characteristics are essential in agricultural productivity. Earth and environmental sciences/Environmental social sciences/Climate change adaptation Earth and environmental sciences/Environmental social sciences/Sustainability Biological sciences/Plant sciences/Light responses Biological sciences/Plant sciences/Plant development Biological sciences/Plant sciences/Plant domestication Plastic mulch crop productivity climate mitigation soil-nutrition Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Climate change exacerbates agricultural system challenges such as increased land degradation, pests, disease, weed resistance, floods, drought, high temperatures, and changes in areas suitable for cultivation [1; 2; 3; 4]. As a result, sustainable and innovative agricultural initiatives are being implemented to overcome these challenges and meet the projected 10 billion global population by 2050 [ 3 ]. Plastic mulching (PM) is an effective approach in managing soil and crop micro-environments, thereby increasing agricultural output. This technique was first employed in the 1950s for commercial vegetable production [ 5 ]. Approximately 30 million hectares of land are currently under PM, with 60% of which in China, Spain, France and Italy contributing about 120,000, 100,000, and 85,000 hectares, respectively [16; 5]. According to Ham et al. [ 8 ] and Shah and Wu, [ 9 ], PM can potentially enhance agricultural productivity by changing temperature and moisture regimes within the soil. Plastic mulching reduces evaporation from the soil, thus improving water use efficiency and reducing the need for irrigation [ 4 ]. This is particularly important in arid regions with scarce water resources and low precipitation [10; 11]. Plastic mulching also lowers competition for resources by effectively controlling weed populations, thus improving crop productivity [ 12 ]. Furthermore, PM reduces the incidence of soil-borne diseases Shiukhy et al. [ 13 ] and hinders the growth of weeds that attract diseases [ 14 ]. The increased soil temperature significantly accelerates germination rate and plant growth [ 9 ]. However, there are challenges associated with PM including the high cost of materials and labour, the environmental impact of plastic waste, and the potential for increased pest and disease pressures if not managed properly [ 3 ]. Despite these challenges, the overall potential benefits on crop productivity have made PM a valuable tool in sustainable agriculture [ 3 ]. Nevertheless, continuous research on this practice is crucial to optimize its benefits and mitigate the potential drawbacks [ 9 ]. Although PM is widely utilized, various factors, like color, perforation, thickness, and application method, can potentially affect the benefits from its use. Among these, the color is considered the most critical, as it influences differences in thermal regimes, which subsequently alter soil dynamics and crop productivity [12; 15]. Different plastic colors create distinct microclimates around the soil and crop, consequently impacting productivity[12; 15]. The most common black PM exhibits a high capacity for absorption across the ultraviolet and infrared wavelengths of solar radiation Amare and Desta [ 7 ]] and it is known for its exceptional weed suppression and soil warming characteristics. Transparent PM also increases soil temperatures, which might be advantageous in colder regions but can also intensify the proliferation of weeds. Bright-colored PMs, e.g. red, green, and blue, are more reflective and can potentially enhance plant processes such as photosynthesis and discourage certain insect pest invasions [18;19;1]. Further research on colored PM is vital as it aids in optimizing the specific conditions required for growing crops, potentially resulting in higher yields and improved quality [20;21;22]. Moreover, understanding the efficacy of diverse colored mulches in varied climates, soil types, and crop species will assist farmers in making well-informed choices, thereby promoting more effective and environmentally friendly agricultural methods. Researchers extensively examine the impact of various PM colors on crop productivity in vegetable production systems. For instance, a study conducted in Spain on loam soil under semi-arid conditions found that black PM significantly increased tomato yields by 98.3 t/ha in 2005, 62.8 t/ha in 2006 and 89 t/ha in 2007 growing seasons compared to the control [ 23 ]. However, a study conducted in Brazil in clay soil under tropical conditions reported that the green and silver PM mulches resulted in a 33 and 34% increase in yield based on the total number of fruits of tomatoes [ 24 ]. Al-Zohiri [ 25 ] reported that potatoes grown in clay loam soil with a subtropical climate in Egypt under a red PM had significantly high yield of 20.36 t/fed. And 20.34 t/fed and vegetative growth compared to blue PM and the control (bare soil), though not differing significantly from black PM. In contrast, a study in Iran under a semi-arid climate on sandy clay soil reported that different colored PM did not significantly affect the total yield of potatoes [ 26 ]. The performance inconsistency of different colored PM across different regions, soils, and seasons, indicates the need for a comprehensive and systematic assessment. Such an approach can be effectively achieved through meta-analysis first-targeting vegetable production system. While meta-analyses have explored the impact of plastics on soil properties and productivity of field crop, focusing predominantly on studies from China [11; 27; 28; 29; 30], to date, no meta-analysis has consolidated findings specifically on the effects of different PM colors on soil and crop productivity under vegetable production. Therefore, this study aimed to conduct a meta-analysis to systematically assess the effects of PM color on selected soil properties and crop productivity under vegetable production, filling this gap in the existing literature. 2. Methodology 2.1 Literature search A comprehensive search of literature was conducted to collect data on the influence of different colored PM on selected soil properties, weed density, growth, and yield of vegetable crops. Research reports were collected from different databases, such as Scopus, Science Direct, Cab Abstracts, Web of Science, and PubMed, which were accessed through the library of the University of Fort Hare. Other reports were downloaded from Google Scholar, after obtaining them from the reference section of some articles. The keywords used for searching articles in these databases were “colored plastic”, “mulch color”, “crop”, “nutritional quality”. The literature search was done between the 10th of December 2023 and the 6th of January 2024. For an article to be considered in the meta-analysis, the following criteria was used: The study should have been conducted on a vegetable crop and compared at least one treatment of PM color with a control (bare soil). The study should have been conducted only under field conditions. The study should have data on at least one of the selected response variables (yield, weeds, soil properties). The study should have been conducted in English language. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) were followed for screening of all articles. The publication year was restricted to the period between January 1990 – December 2023, and any article published beyond this period was not included. Details of articles that could not be downloaded were sent to the Librarian to assist in acquiring them. Out of approximately 20 articles sent to the librarian, only 13 were acquired. 2.2 Data collection and grouping The study collected data on 13 response variables for crop parameters and soil properties. Crop parameters included crop yield, biomass (dry weight basis), plant height, stem diameter, and weed biomass. Soil properties included soil temperature, water use efficiency (WUE), moisture content, soil organic carbon (SOC), pH, total nitrogen, available phosphorus, and available potassium. The selection of these parameters included in this study was based on their significance in explaining the study aims, and their availability from the articles finally included in the study. Crop yield, biomass, and weed biomass were expressed as t ha − 1 as the base unit; WUE in kg ha − 1 mm − 1 ; plant height and stem diameter in cm; soil organic carbon and total nitrogen in %, and available phosphorus and potassium in g kg − 1 . Thus, if the parameter was originally given in another form, it was converted to fit the base units used in this study. For instance, in cases where crop yield, biomass and weed biomass were expressed in kg/ha, it was converted into to t/ha by dividing by 1000. When the crop yield and biomass were given as weight per plant, the plant population was used for converting to t/ha. For plant height, and stem diameter where it was given as mm or m it was converted to cm by dividing by 10 and 100 respectively. Mulch color was the independent variable for all variables. The study consisted of about 25 vegetables, which including tomato, chilli, eggplant, pepper, cucumber, bottle gourd, melon, musk melon, watermelon, okra, pumpkin, squash, Swiss chard, lettuce, spinach, broccoli, cabbage, cauliflower, potato, sweet potato, radish, onion, ginger, cocoyam, and sugar beets, where mulch colours were chosen based on their impact on soil temperature, weed suppression, and crop productivity. The studies included in this meta-analysis covered a range of environmental and agronomic conditions to assess the effects of coloured plastic mulches. Climatic conditions varied from humid to semi-arid and arid regions, with mean annual temperatures ranging from 1.1°C to 34.5°C and precipitation between 19.1 mm and 4907 mm. The soil types across the studies included clay, loam, sandy clay loam, and sandy loam, influencing mulch effectiveness in heat retention, moisture conservation, and nutrient availability. Mulch application methods varied, with most studies applying mulch before planting and keeping it in place throughout the growing season. These conditions provide a broader context for understanding the findings of this meta-analysis and their applicability to different agricultural systems. The following additional variables from the articles were incorporated if provided: country, regional location, geographic coordinates (longitude and latitude), mean annual precipitation, temperature of the study site, climate zone, soil texture, and initial soil properties (including soil organic carbon, pH, total nitrogen, available phosphorus, and available potassium). The mean (M), standard deviation (SD), and sample size/replication (N) of the selected response variables were collected as the values required for the meta-analysis. The results presented in figures or charts were extracted using the GetData Graph Digitizer Software version 2.25 ( http://getdata-graph-digitizer.com/ ). Some of the articles did not report standard deviations but reported other related metrics such as standard error (SE) and coefficient of variation (CV) or did not report anything at all. Therefore, if the CV was given, the SD was calculated using Eq. 1. SD = \(\:\frac{\text{C}\text{V}}{100}\:\text{X}\:\text{M}\text{e}\text{a}\text{n}\) ………………………………………………………………………. Eq. 1 If SE was given, the SD was calculated using Eq. 2.: SD = SE X \(\:\sqrt{N}\) …………………………………………………………………………. Eq. 2 For studies that did not report SD, SE, or CV, we assumed that the SD was 10% of the mean, and the mean was multiplied by 0,1 to get the SD [ 31 ]. Although efforts were made to obtain additional information for a specific article, no response was received from any of the corresponding authors contacted. 2.3 Statistical Analysis The metanalysis was done using the “metafor package” of the R Studio Software (version 4.0.3) ( https://www.r-project.org/ ). The natural log (ln R) of the response ratio (R) was calculated as the effect size based on the relationship of the mean values of treatment (Mt) and control response variables (Mc) as in Eq. 3. ln RR = \(\:\frac{Mt}{Mc}\) = ln Mt - ln Mc ……………………………………………………………Equation 3 Where Mt and Mc are the mean values of the treatment and control response variables, respectively. A 95% confidence interval (CI) was used to determine if there were any significant differences. Thus, if the CI did not overlap with zero, a significant difference was observed between the treatment and control groups. Conversely, if the CI overlapped by zero, it implied that there was no significant difference between the control and treatment groups [32; 11; 30]. The random-effects model using residual maximum likelihood (REML) was used to assess group differences using the “rma” function of the metafor package. Cochran’s Q and Higgins’ I 2 were used to determine the heterogeneity of the effect size. I 2 > 75%, 25–75%, and I 2 < 25% indicated high, medium, and low heterogeneity, respectively[28; 30]. The results were presented as forest plots using the “forest rma” function. 3. Results 3.1 Overview of the study The meta-analysis ultimately included 97 articles with 788 observations that satisfied the criteria ( Fig. 1 ). The research encompassed 25 countries from four continents, namely Africa, Asia, Europe, and North America. A significant number of studies were conducted in Asia and America, and the countries where most studies were carried out were the USA (21), India (17), Mexico (10), and China (6). The mean annual temperature and precipitation ranged between 1.1–34.5°C and 19.1–4907 mm, respectively, while the major climatic zones where data were collected were mostly humid and semi-arid. The soil consisted of a range of textures, including clay, loam, clay loam, sand, sandy clay, sandy clay loam, sandy loam, and silt loam. Data was extracted from 25 vegetable crops; tomato was the most extensively studied crop and accounted for the largest dataset in the fruit crop category. Lastly, the study identified 10 PM, which were black, blue, green, grey, yellow, transparent, white, silver, brown, and red. Black PM was the most studied among the different PMs and was examined in almost every article. 3.2 Study heterogeneity and the overall effect The Higgins and Thompson I 2 heterogeneity test indicated varied results with respect to the response variables assessed in this study ( Table 1 ) . Heterogeneity was highly significant ( p < 0.001) in yield, biomass, height, stem diameter, WUE, stem diameter, weed biomass, moisture content, temperature, pH, AP, and K. Weed biomass showed the highest heterogeneity (I 2 = 93.03) while temperature, SOC, pH, and TN had the least heterogeneity. Table 1 Statistics for heterogeneity report of effect sizes of all studied variables in the metanalysis Parameter df Q I 2 I 2 level I 2 p value Yield 83 1762.52 80.53 high *** Biomass 12 295.48 77.22 high *** Height 36 479.93 46.03 moderate *** Stem diameter 3 41.94 84.17 high *** WUE 3 217.84 55.16 moderate *** Weed biomass 18 1029.24 93.03 high *** Temperature 50 618.68 0 low *** Moisture content 16 738.12 87.26 high *** Soi organic carbon 2 33.68 0 low ns pH 2 190.33 0 low *** Total Nitrogen 1 1.22 0 low ns Available Phosphorus 3 291.35 8.33 low *** Potassium 4 205.16 42.39 moderate *** DF: degree of freedom, Q: test for heterogeneity, I 2 : total heterogeneity and P < 0.05. The results indicated high significant difference ( p < 0.001) in the general effect of PM on most crop productivity parameters while pH ( p 0.05) where the only soil properties showing significant differences ( Table 2 ). Table 2 Overall effects of the study of effect sizes of all studied variables in the metanalysis Parameter Estimate SE ci.lb ci.ub n k p value Yield 2.81 0.13 2.55 3.07 82 413 *** Biomass 3.42 0.28 2.85 3.98 13 84 *** Height 1.33 0.10 1.13 1.53 37 177 *** Stem diameter 2.97 0.85 1.29 4.64 4 12 *** Weed biomass -5.13 0.58 -6.26 -3.99 19 122 *** Temperature 0.69 0.04 0.61 0.78 51 337 *** WUE 2.06 0.19 1.69 2.44 4 78 *** Moisture content 0.14 0.20 -0.25 0.54 17 174 ns SOC 0.19 0.08 0.03 0.35 3 80 * pH -0.25 0.08 -0.42 -0.08 3 84 ** TN 0.77 0.42 -0.07 1.61 1 4 ns AP 0.09 0.09 -0.31 0.27 4 85 ns K -0.18 0.11 -0.04 0.04 5 88 ns SE: standard error, ci.lb and ci.ub: confidence interval (upper and lower levels) n: number of observations, p < 0.05. 3.3 Effects of plastic mulch color on vegetable crop productivity The use of colored PM significantly increased the yield of all vegetables compared to the control (Fig. 2 a). The green PM showed highest yield increase (ES = 5.73, CI = 3.92–7.93) and it significantly differed from that of black PM (ES = 2.53, CI = 2.14–2.92), white PM (ES = 2.33, CI = 1.47–3.19), and transparent PM (ES = 2.03, CI = 1.63–2.45). Yellow and brown PM did not have biomass data for evaluation. Similar to the yield, the assessed PM significantly increased the biomass of all vegetables compared to the control ( Fig. 2 b ) . The highest increase in biomass was observed on the transparent PM. The biomass increases were significantly higher on transparent PM (ES = 6.52, CI = 5.17–7.87) than on the black PM (ES = 3.53, CI = 2.39–4.67). The lowest increase in biomass, were observed from silver PM (ES = 6.52, CI = 0.98–3.54), white PM (ES = 2.65, CI = 1.80–3.50) and blue PM (ES = 2.73, CI = 0.28–5.17). No plant height data was available with respect to grey PM. Plant height of all crops was significantly increased by all PM colors compared to the control except for brown and yellow PM ( Fig. 3 a ) . The highest increase in height of all plants was observed on the black PM (ES = 1.95, CI = 1.49–2.42) which was significantly higher than the transparent PM (ES = 0.9, CI = 0.62–1.19) white PM (ES = 0.93, CI = 0.35–1.5) and yellow PM (ES = 0.9, CI = -0.71–2.67). Only the black PM significantly increased stem diameter of vegetable crops compared to the control ( Fig. 3 b ) . The black PM demonstrated the greatest increase (ES = 6.60, CI = -6.60–19.24), while the lowest increase was found on the red PM (ES = 0.46, CI = -1.17–2.08). The weed biomass did not have all the plastic mulch colors included in the study. Among the included plastic mulch colors, the results revealed that all the PM colors decreased the weed biomass compared to the control, although the biomass on the brown and green PM did not significantly differ from that on the control (Fig. 4 ) . The largest decrease in weed biomass was observed on the red PM (ES = -9.04, CI =-13.33 – (-4.76)) and did not significantly differ with all other PM colors. The brown (ES = -3.88, CI = -9.12 – (-1.35)) and white (ES = -3.79, CI = -6.78 – (-0.79)) PM had the least decrease in weed biomass. In addition, other P colors such as transparent, red and blue also had larger decrease in weed biomass after the red PM color. 3.4 Effects of plastic mulch color on soil properties The assessment of all ten PMs in this study showed that only the yellow PM had absent data pertaining to soil temperature ( Fig. 5 ) . The black, blue, green, red, silver, transparent, and white PMs showed significant variations compared to the control, while brown, and grey PM did not show significant differences from the control. Among the PM, the black (ES = 0.82, CI = 0.69–0.94) and brown (ES = 0.85, CI = -0.02–1.71) plastic mulching demonstrated the highest increase in soil temperature, although they were not significantly different from other PM. On the other hand, grey (ES = 0.28, CI = -2.5–0.80), and white (ES = 0.38, CI = 0.12–0.63) plastic mulching had a lower increase in soil temperature compared to other PM. The study included four PM colors (black, silver, transparent, and white) on water use efficiency of vegetables. The results revealed that all four PMs exhibited a significant improvement in water use efficiency compared to the control ( Fig. 6 ) . Among these PMs, the black PM demonstrated the most significant increase in water use efficiency, with an effect size (ES) of 1.95 (confidence interval [CI] = 1.49–2.42). Moreover, the black P significantly differed from the transparent PM (ES = 0.90, CI = 0.62–1.19) and the white PM (ES = 0.93, CI = 0.35–1.50). Regarding soil moisture, only the colored PM, such as black, blue, green, red, silver, transparent, and white had data collected ( Fig. 7 ) . The black PM (ES = 0.40, CI = 0.03–0.77) was found to have a significant increase in moisture content compared to the control. However, the other PM colors such as green (ES = 0.28, CI = -0.25–0.80), and silver (ES = 0.68, CI = -3.16–4.53) also increased soil moisture content. In contrast, the blue PM (ES = -0.48, CI = -3.93–2.96), red PM (ES = -2.71, CI = -6.70–1.28), transparent PM (ES = -0.29, CI = -2.01–1.44), and white PM (ES = -0.08, CI = -0.85–0.69) were found to decrease moisture content, with the greatest decrease observed in the red PM. Soil chemical properties indicated significant changes when plastic mulches were applied ( Table 3 ). For instance, the soil organic carbon was significantly higher in the black PM than the control, with an ES of 0.19 (CI = 0.03–0.35). However, the black PM had a significant negative effect on soil pH compared to the control, with an ES of -0.31 (CI = -0.48 – (-0.14)). On the other hand, the blue, silver, and white PMs significantly increased soil pH, with ES values of 2.62 (CI = 0.44–4.80), 3.21 (CI = 0.79–5.63), and 2.62 (CI = 0.44–4.80), respectively. On the available phosphorus, the grey (ES = 2.03, CI = 0.06–4) and silver (ES = 2.04, CI = 0.64–3.43) PM demonstrated the greatest increase, which also significantly differed from the control. Conversely, the black, blue, and white PMs showed the lowest increase in soil phosphorus content and did not significantly differ from the control. Regarding the available potassium, only the grey PM was found to significantly increase the available potassium, with an ES value of 2.03 (CI = 0.06–4.00). This increase was higher than that observed for the other PM. However, no increase was observed for the blue PM, with an ES of 0 (CI = -0.65–2.77). Additionally, the black, silver, and white PMs had a similar increase, with an ES of 1.06 (CI = -0.65–2.77). Table 3 Effects of different PMs under vegetable production on soil chemical properties. Soil Properties Mulch Color Effect Size Confidence Interval SOC (n = 3, k = 80) Black (n = 3, k = 80) 0.19 0.03–0.35 pH (n = 4, k = 84) Black (n = 4, k = 81) -0.31 -0.48 – (-0.14) Blue (n = 1, k = 1) 2.62 0.44–4.80 Silver (n = 1, k = 1) 3.21 0.79–5.63 White (n = 1, k = 1) 2.62 0.44–4.80 Total Nitrogen (n = 4, k = 84) Black (n = 1, k = 1) 1.06 -0.65–2.77 Blue (n = 1, k = 1) 0 -1.60–1.60 Silver (n = 1, k = 1) 1.06 -0.65–2.77 White (n = 1, k = 1) 1.06 -0.65–2.77 Available Phosphorus (n = 4, k = 86) Black (n = 15, k = 131) 0.02 -0.16–0.20 Blue (n = 3, k = 4) 1.03 -0.66–2.74 Grey (n = 1, k = 1) 2.03 0.06–4.00 Silver (n = 4, k = 9) 2.04 0.64–3.43 White (n = 3, k = 6) 1.08 -0.63–2.79 Available Potassium (n = 5, k = 88) Black (n = 5, k = 83) 1.06 -0.65–2.77 Blue (n = 1, k = 1) 0.00 -1.60–1.60 Grey (n = 1, k = 1) 2.03 0.06–4.00 Silver (n = 2, k = 2) 1.06 -0.65–2.77 White (n = 1, k = 1) 1.06 -0.65–2.77 The letter “n” and “k” indicate the number of studies and observations respectively. 4. Discussion The current metanalysis study was aimed at assessing the effects of different PMs on crop and soil productivity under vegetable production based on several studies conducted across the world that met our study criteria. The choice to focus on vegetables only was because that is the crop category in which PMs are mainly used and has immensely contributed to the yield increases. The current study consolidated several published articles ( Fig. 1 ) , providing a sufficient basis for conducting a meta-analysis. However, it is important to note that many of these studies originate from a limited number of countries, with a significant concentration in the USA, India, Mexico, and China. Although we observed 10 different PM colors, the black and transparent PMs were the most studied [19; 1]. This is because the black PM is the most popular choice as it is the most cost-effective option [ 7 ]. The application of PM, regardless of its color, resulted in significant improvements in all crop productivity parameters, including yield, biomass, height, stem diameter, while significantly reduced weed biomass ( Table 2 ). This is corresponding with several other studies in the literature that PMs enhance growth and development of numerous crops [20; 21; 22]. Plastic mulches regulate the microclimate and rhizosphere temperature of plants which significantly improves physiological and morphological activities such as cell expansion and enlargement [12; 7; 15]. Plastic mulches absorb substantial quantities of solar radiations, while preserving soil moisture content by reducing evaporation [ 33 ]. In addition, the meta-analysis showed that yield ( Fig. 2 a ) , biomass ( Fig. 2 b ) and water use efficiency ( Fig. 4 ) irrespective of the PM color was significantly different from the control which depicts the superiority of any PM color in improving these crop parameters. The impact of different PM colors on crop productivity is expected to vary. This is because colors absorb, transmit, radiate and reradiate, and reflect solar radiation differently, which heavily influences soil temperature dynamics and, ultimately, differences in crop growth, development and yield [ 34 ]. However, although differences are expected and were observed in this study, the modus operandi is that anything that strongly influence crop growth and development (for instance stem diameter and height in this study) will also strongly influence biomass and yield. But in this study, that was not the case. For instance, yield, biomass, height, and stem diameter increased the most, compared to the control, on green, transparent, black, and silver PMs, respectively. It was not observed that any specific color had a trend in dominating crop growth parameters, which in turn affected yield and biomass production. The reason for these inconsistencies could be the limited number of datasets collected for the several colors (blue, brown, green, red, silver, white and yellow) included in the study Wei et al. [ 29 ]; Zhang et al. [ 30 ], where the meta-analysis results were based on a few studies rather than in the case of black PM, where datasets were based on several studies. Another possible reason could be the disparities in edaphic and climatic factors encountered in the various study locations, such as soil texture, initial soil properties (including nutrient content, pH, and organic matter), climate (including rainfall and temperature), topography and the type of crops grown. In addition, weed biomass decreased as a result of PM, even though the brown and green mulch color did not differ significantly with the control. It is well known that PM acts as a barrier to weeds which reduce their germination and suppress their growth. This is one of the significant uses of PMs in vegetable production as weeds are problematic. PM has long been recognized as an effective means of controlling weed growth in vegetable production. Its capacity to impede weed germination and suppress their development is a key advantage in this context [ 35 ]. Temperature had the highest effect (n = 40), followed by moisture content. The significant impact of soil temperature under PMs, as noted by Shiukhy et al. [ 13 ], is primarily due to the direct influence of PMs on soil temperature. Plastic mulches alter soil temperature because they affect how solar radiation interacts with the soil [ 36 ]. This interaction depends on specific thermal properties of the plastic material used, such as reflectivity, absorptivity, and transmittance. These properties collectively determine the net effect of the PM on soil temperature. Changes in soil temperature can subsequently influence other soil properties and processes, such as moisture content, microbial activity, and nutrient availability, thus impacting overall crop growth and productivity [ 37 ]. This study observed a general increase in soil temperature, although brown, green, and grey PM did not differ significantly from that of the control. Among the mulch colors, black and transparent PM colors showed the highest increase in soil temperature compared to other colors. The reason for the increase with black PM is its ability to improve the efficiency of increasing minimum, mean, and maximum soil temperatures [ 5 ]. This occurs through black PM’s ability to absorbs energy, which it will pass through the soil by conduction [ 38 ]. The efficiency of PM in enhancing water use efficiency is attributed to its capacity to reduce evaporation, thereby increasing the availability of water for plant growth. Furthermore, PM plays a crucial role in reducing the evapotranspiration of crops which also improves water use efficiency [ 38 ]. Practices that promote water use efficiency in agriculture have been applauded for their crucial role in boosting crop productivity with less water, particularly in arid and semi-arid regions where conserving water is essential [ 39 ]. Among the various PM colors, black mulch demonstrated the greatest increase, indicating its strong impact in enhancing water use efficiency. However, our meta-analysis observed an unexpected trend on the moisture content compared to what is typically reported in literature. It was found that PM colors such as blue, red, and transparent were associated with a decrease in moisture content, whereas the green and silver PM colors did not significantly differ from the control. Upon tracing the articles, we noted that the articles reporting this trend attributed it to the high rainfall and vegetation cover in the non-mulched plots [ 1 ]. This explanation is particularly relevant, especially regarding the timing of sampling, as it is expected that there would be higher moisture content in bare soil than in covered soil following a rainfall event, as the plastic mulch acts as a barrier preventing water from penetrating into the soil. The soil’s chemical properties comprised of few PM colors because of a few articles and datasets. This implies that there are still limited studies that have investigated the influence of PM color on soil chemical properties. Thus, further studies are needed to fill this gap, as soil chemical properties are central to crop production and yield. Soil organic carbon had only one color (black), soil pH and total nitrogen had four colors (black, blue, silver, and white), while available phosphorus and available potassium had five colors (black, grey, blue, silver, and white). Nevertheless, the few studies observed in this study generally showed that almost all PM colors improved soil properties compared to the control. However, the PM colors did not differ significantly from the control, except in few cases in pH, available phosphorus, and available potassium. The increase in SOC and pH is because PM increases the decomposition of organic matter due to an increase in soil temperature and moisture content. However, other authors MingFu et al. [ 40 ] argued that PMs facilitate root and microbial respiration, which intensifies organic matter decomposition and significantly increases the CO 2 concentration. This, in turn, reduces the soil pH, which could be the reason why black PM decreased the pH. Regarding soil nutrients, it has been argued that PM increases soil nutrients in the soil, but the reduction in nutrients is due to plant uptake at the end of the season [41; 42]. This is also because PMs reduce nutrient loss by both leaching and surface runoff erosion, as the ground will be covered. Black plastic mulch is particularly effective due to its ability to efficiently absorb ultraviolet (UV), visible, and infrared wavelengths of solar radiation [ 7 ]. This absorption significantly increases soil temperature by capturing high levels of radiation, thereby raising the minimum, maximum, and mean soil temperatures. The warmer soil, in turn, enhances weed suppression by inhibiting weed growth, particularly in weed-infested areas [43; 44]. This contributes to improved plant performance compared to other mulch colors. Furthermore, black plastic mulch enhances water use efficiency by reducing evapotranspiration from the soil surface [ 45 ]. This results in less moisture loss, making it a key factor in protected agriculture by decreasing the need for frequent irrigation [46; 47]. In comparison to other mulch colors, such as white or transparent, black mulch has been shown to provide better thermal regulation and weed control, which are crucial for crop yield optimization. Additionally, the dark color creates an ideal environment for maintaining optimal soil temperatures, which contributes to healthier plant growth and higher productivity. Overall, the combination of heat retention, moisture conservation, and superior weed suppression makes black plastic mulch the preferred choice in many agricultural systems. 5. Conclusion The study aimed at conducting a comprehensive meta-analysis to consolidate information on the effects of different colored PM on selected soil properties, weeds biomass and vegetable productivity. The results of the meta-analysis demonstrated that the application of PM with respect to crop parameters resulted on increased yield, biomass, plant height, and stem diameter compared to non-mulched. While on the other hand, the weed biomass was considerably reduced, which indicates a reduction in competition for available soil nutrients between the main crops and weeds, resulting in improved crop productivity. The chemical properties of soil have not been thoroughly studied which translates to a limited number of studies included in the dataset. Even though soil chemical properties, such as soil organic carbon, soil pH, total nitrogen, available phosphorus, and available potassium, have been under studied, the available reports indicated improved soil properties compared to non-mulched. In the context of these results, plastic mulching is anticipated to be a successful strategy for improving food security, mitigating the negative effects of soil degradation, climate change, and water resource scarcity in arid and semi-arid regions. Declarations Author contributions Asanda Sokombela: Conceptualisation, Writing - Initial Draft, Writing - Revisions, Methodology, Data Curation, Investigation, Visualisation. Ashwell R. Ndhlala: Conceptualisation, Writing - Review and Editing, Supervision, Resources, Project Administration and Funding Acquisition. Bahlebi K. Eiasu: Conceptualisation, Writing - Review and Editing, Supervision and Resources. Moshibudi P. Bopape-Mabapa: Conceptualisation, Writing - Review and Editing, Supervision and Resources Patrick Nyambo: Writing - Review and Editing, Methodology, Supervision, Validation. Semakaleng Mpai: Writing - Review and Editing, Methodology, Supervision, Validation. All authors have read and agreed to the submitted version of the manuscript. Funding statement This study was funded by the Department of Science and Innovation (DSI), South African Government (Grant number DSCI/CONC2235/2021) Data availability The data will be available from the corresponding author upon reasonable request. Conflict statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. References Nyochembeng LM, Mankolo RN (2021) Colored plastic mulch effects on plant performance and disease suppression in organically grown bell pepper (Capsicum annuum). Journal of Agricultural Science (Toronto) 13: 11–17. https://doi.org/10.5539/jas.v13n6p11 Aly M, Ahmed N, El-Zawawy HAH, Ali B (2023) Effect of Nostoc clacicola as bio-fertilizer with plastic mulch on the growth and economic value of sweet pepper. Egyptian Journal of Agricultural Research 101: 119–130. DOI:10.21608/ejar.2023.165324.1286 Hofmann T, Ghoshal S, Tufenkji N, Adamowski JF, Bayen S, Chen Q, Demokritou P, Flury M, Hüffer T, Ivleva NP, Ji R, Leask RL, Maric M, Mitrano DM, Sander M, Pahl S, Rillig MC, Walker TR, White JC, Wilkinson KJ (2023) Plastics can be used more sustainably in agriculture. Communications Earth and Environment 4: 1–11. https://doi.org/10.1038/s43247-023-00982-4 Karaer M, Gültaş HT, Kuşçu H (2023). The Effects of Plastic Mulched Drip Irrigation on Yield, Fruit Quality and Water Productivity of Table Tomatoes. Gesunde Pflanzen 75: 1591–1599. https://doi.org/10.1007/s10343-023-00848-x Saini J, Mirza AA (2022). Impact of colored plastic mulches on soil characteristics and strawberry crop productivity : A review. The Pharma Innovation Journal 2022; 11: 1117–1123. https://doi.org/10.21273/hortsci.40.5.1371 Ibarra-Jiménez L, Lira-Saldivar RH, Valdez-Aguilar LA, Río JL-D (2011). Colored plastic mulches affect soil temperature and tuber production of potato. Acta Agriculturae Scandinavica Section B: Soil and Plant Science 61: 365–371. https://doi.org/10.1080/09064710.2010.495724 Amare G, Desta B (2021) Colored plastic mulches: impact on soil properties and crop productivity. Chemical and Biological Technologies in Agriculture 8. DOI:10.1186/s40538-020-00201-8 Ham JM, Kluitenberg GJ, Lamont WJ (2019) Optical Properties of Plastic Mulches Affect the Field Temperature Regime. Journal of the American Society for Horticultural Science 118: 188–193. https://doi.org/10.21273/jashs.118.2.188 Shah F, Wu W (2020) Use of plastic mulch in agriculture and strategies to mitigate the associated environmental concerns . (1st ed.). Vol. 164. Elsevier Inc. https://doi.org/10.1016/bs.agron.2020.06.005 Iqbal R, Raza MAS, Valipour M, Saleem MF, Zaheer MS, Ahmad S, Toleikiene M, Haider I, Aslam MU, Nazar MA (2020). Potential agricultural and environmental benefits of mulches—a review. Bulletin of the National Research Centre 44. https://doi.org/10.1186/s42269-020-00290-3 Wang L, Coulter JA, Li L, Luo Z, Chen Y, Deng X, Xie J (2020). Plastic mulching reduces nitrogen footprint of food crops in China: A meta-analysis. Science of the Total Environment 748: 141479. https://doi.org/10.1016/j.scitotenv.2020.141479 Kader MA, Nakamura K, Senge M, Mojid MA, Kawashima S (2020). Effects of colored plastic mulch on soil hydrothermal characteristics, growth and water productivity of rainfed soybean. Irrigation and Drainage 69: 483–494. https://doi.org/10.1002/ird.2431 Shiukhy S, Raeini-Sarjaz M, Chalavi V (2015) Colored plastic mulch microclimates affect strawberry fruit yield and quality. International Journal of Biometeorology 59: 1061–1066. https://doi.org/10.1007/s00484-014-0919-0 Ngosong C, Okolle JN, Tening AS (2019) Mulching: A sustainable option to improve soil health. Soil fertility management for sustainable development, pp.231-249. https://doi.org/10.1007/978-981-13-5904-0_11 Spaldon S, Namgyal D, Hussain A, Tundup P, Angmo D, Kendra KV (2023) Effect of different mulch colors on the yield of cabbage in the cold arid region of Ladakh ( UT ), India. Eco. Env. & Cons 71–75. https://doi.org/10.5958/2454-552x.2021.00161.4 Kasirajan, S. and Ngouajio M. 2012. Polyethylene and biodegradable mulches for agricultural applications: a review Agronomy for Sustainable Development. 32: pp. 501-529 Lalitha, M., Thilagam, V. K., Balakrishnan, N. & Mansour, M. (2010). Effect of plastic mulch on soil properties and Crop growth - a review. Agricultural Review, 31 (2): 145 – 149. Canul-Tun CE, Ibarra-Jiménez L, Valdez-Aguilar LA, Lozano-del Río AJ, Cárdenas-Flores A, Zermeño-González A, Lozano-Cavazos CJ, Valenzuela-Soto JH, Torres-Olivar V (2017) Influence of colored plastic mulch on soil temperature, growth, nutrimental status, and yield of bell pepper under shade house conditions. Journal of Plant Nutrition 40: 1083–1090. DOI:10.1080/01904167.2016.1263331 Mostafa H, Khater ES, Hamouda R (2020) Changes of root zone temperature, growth and productivity of broccoli cultivated with colored plastic mulches. Research in Agricultural Engineering 66: 112–121. https://doi.org/10.17221/84/2019-rae Chang DC, Cho JH, Jin YI, Im JS, Cheon CG, Kim SJ, Yu HS (2016) Mulch and planting depth influence potato canopy development, underground morphology, and tuber yield. Field Crops Research 197: 117–124. https://doi.org/10.1016/j.fcr.2016.05.003 Agyare RY, Abdulai MS, Buah SS, Ayipio E, Bonsu SK, Kamga RT (2017) Growth and Fruit Yield of Okro as Influenced by Genotypes and Mulch in the Guinea Savannah Conditions of Ghana. International Journal of Agronomy 2017. DOI:10.1155/2017/9840130 Liang ZY, FengXin W, Shock CC, KaiJing Y, ShaoZhong K, JingTao Q, SiEn L, Zhang Y-L, Wang F-X, Shock CC, Yang K-J, Kang S-Z, Qin J-T, Li S-E (2017) Effects of plastic mulch on the radiative and thermal conditions and potato growth under drip irrigation in arid Northwest China. Soil and Tillage Research 172: 1–11. https://doi.org/10.1016/j.still.2017.04.010 Anzalone AA, Cirujeda A, Aibar J, Pardo G, Zaragoza C (2016) Effect of Biodegradable Mulch Materials on Weed Control in Processing Tomatoes Published by : Weed Science Society of America and Allen Press Linked references are available on JSTOR for this article : Weed Management - Techniques ï ^^ ï ^ a ^ i ^^ ï . ^^. Weed Technology 24: 369–377. DOI:10.1614/WT-09-020.1 Mendonça SR, Ávila MCR, Vital RG, Evangelista ZR, de Carvalho Pontes N, dos Reis Nascimento A (2021) The effect of different mulching on tomato development and yield. Scientia Horticulturae, 275, p.109657. https://doi.org/10.1016/j.scienta.2020.109657 Al-Zohiri S (2013) Influence of Colored Plastic Mulches on Germination, Growth and Marketable Yield of Potato. Journal of Productivity and Development 18: 405–420. DOI:10.21608/jpd.2013.42585 Azad B, Hassandokht MR, Parvizi K (2015) Effect of mulch on some characteristics of potato in Asadabad, Hamedan. International Journal of Agronomy and Agricultural Research (IJAAR), 6(3), pp.139-147. https://doi.org/10.1007/s40093-017-0189-z Mak-Mensah E, Obour PB, Essel E, Wang Q, Ahiakpa JK (2021) Influence of plastic film mulch with biochar application on crop yield, evapotranspiration, and water use efficiency in northern China: A meta-analysis. PeerJ 9. https://doi.org/10.7717/peerj.10967 Qin Y, Chai Y, Li R, Li Y, Ma J, Cheng H, Chang L, Chai S (2022) Evaluation of straw and plastic film mulching on wheat production: A meta-analysis in Loess Plateau of China. Field Crops Research 275: 108333. https://doi.org/10.1016/j.fcr.2021.108333 Wei H, Zhang F, Zhang K, Qin R, Zhang W, Sun G, Huang J (2022). Effects of soil mulching on staple crop yield and greenhouse gas emissions in China: A meta-analysis. Field Crops Research 284: 108566. https://doi.org/10.1016/j.fcr.2022.108566 Zhang D, Mak-Mensah E, Zhou X, Wang Q, Obour PB (2023). Impact of Plastic Film with Wheat Straw Mulching on Maize Water Use Efficiency, Evapotranspiration, and Grain Yield in Northern China: a Meta-analysis. Journal of Soil Science and Plant Nutrition 23: 867–880. https://doi.org/10.1007/s42729-022-01089-z Acutis M, Tadiello T, Perego A, Di Guardo A, Schillaci C, Valkama E (2022) EX-TRACT: An excel tool for the estimation of standard deviations from published articles. Environmental Modelling and Software 147: 105236. https://doi.org/10.1016/j.envsoft.2021.105236 Gao H, Yan C, Liu Q, Ding W, Chen B, Li Z (2019) Effects of plastic mulching and plastic residue on agricultural production: A meta-analysis. Science of the Total Environment 651: 484–492. https://doi.org/10.1016/j.scitotenv.2018.09.105 Ming ZZ, Yuan L, JianFei L, JingWei W, ZhenXing Z, Na X (2022) Changes of soil water and heat transport and yield of tomato (Solanum lycopersicum) in greenhouses with micro-sprinkler irrigation under plastic film. Agronomy 12. https://doi.org/10.3390/agronomy12030664 Tofanelli MBD, Wortman SE (2020). Benchmarking the agronomic performance of biodegradable mulches against polyethylene mulch film: A meta-analysis. Agronomy 10. https://doi.org/10.3390/agronomy10101618 Rajablarijani HR, Mirshekari B, AghaAlikhani M, Rashidi V, Farahvash F (2014). Sweet corn weed control and yields in response to sowing date and cropping systems. HortScience 49: 289–293. Pramanik P, Bandyopadhyay KK, Bhaduri D, Bhattacharyya R, Aggarwal P (2015) Effect of mulch on soil thermal regimes-a review. International Journal of Agriculture, Environment and Biotechnology , 8 (3), pp.645-658. https://doi.org/10.5958/2230-732x.2015.00072.8 Ibarra-Jiménez L, Zermeño-González A, Munguía-Lopez J, Rosario Quezada-Martín MA, De La Rosa-Ibarra M (2008). Photosynthesis, soil temperature and yield of cucumber as affected by colored plastic mulch. Acta Agriculturae Scandinavica Section B: Soil and Plant Science 58: 372–378. https://doi.org/10.1080/09064710801920297 Singh A, Kaushal A, Garg S, Chawla N (2017) Effect of different colored plastic mulches on growth, yield and quality of drip fertigated bell pepper (Capsicum annum var. grossum). Indian Journal of Horticulture 74: 292–294. https://doi.org/10.5958/0974-0112.2017.00059.7 Khan MN, Ayub G, Ilyas M, Haq FU, Ali J, Alam A (2016) Effect of different mulching materials on weeds and yield of Chili cultivars. Pure Appl. Biol 5: 1160–1170. https://doi.org/10.19045/bspab.2016.50139 MingFu S, YiChen K, WeiNa Z, XinYu Y, YanLing F, HuiFang Y, RuYan Z, AiXia G, ShuHao Q (in press). Plastic film mulching with ridge planting alters soil chemical and biological properties to increase potato yields in semi-arid Northwest China. Chemical and Biological Technologies in Agriculture 9: (21 January 2022). https://doi.org/10.1186/s40538-022-00284-5 Díaz-Pérez JC, Phatak SC, Giddings D, Bertrand D, Mills HA (2005) Root zone temperature, plant growth, and fruit yield of tomatillo as affected by plastic film mulch. HortScience 40: 1312–1319. DOI:10.21273/HORTSCI.40.5.1312 Sintim HY, Bandopadhyay S, English ME, Bary AI, DeBruyn JM, Schaeffer SM, Miles CA, Reganold JP, Flury M (2019) Impacts of biodegradable plastic mulches on soil health. Agriculture, Ecosystems and Environment 273: 36–49. https://doi.org/10.1016/j.agee.2018.12.002 Getachew, A. and Bizuayehu, D., 2021. Coloured plastic mulches: impact on soil properties and crop productivity. Chemical and Biological Technologies in Agriculture , 8 (1). Nwagwu, F.A., Obok, E.E., Umunnakwe, O.C. and Akpan, J.F., 2023. Influence of polyethylene film colour and soil solarisation duration on weed dynamics and performance of hybrid maize (Zea mays L.). Yang, D., Li, S., Kang, S., Du, T., Guo, P., Mao, X., Tong, L., Hao, X., Ding, R. and Niu, J., 2020. Effect of drip irrigation on wheat evapotranspiration, soil evaporation and transpiration in Northwest China. Agricultural Water Management, 232, p.106001. Prem, M., Ranjan, P., Seth, N. and Patle, G.T., 2020. Mulching techniques to conserve the soil water and advance the crop production—A Review. Curr. World Environ , 15 , pp.10-30. Demo, A.H. and Asefa Bogale, G., 2024. Enhancing crop yield and conserving soil moisture through mulching practices in dryland agriculture. Frontiers in Agronomy , 6 , p.1361697. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 03 Jul, 2025 Reviews received at journal 22 Apr, 2025 Reviewers agreed at journal 16 Apr, 2025 Reviewers invited by journal 16 Apr, 2025 Submission checks completed at journal 29 Mar, 2025 First submitted to journal 20 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5951398","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":443773828,"identity":"a4e5f712-69ad-450a-bee0-85e996343d4c","order_by":0,"name":"Asanda Sokombela","email":"","orcid":"","institution":"University of Limpopo","correspondingAuthor":false,"prefix":"","firstName":"Asanda","middleName":"","lastName":"Sokombela","suffix":""},{"id":443773830,"identity":"0dd0f8df-9319-4de4-a0b0-ae839ff3e7e6","order_by":1,"name":"Ashwell Rungano Ndhlala","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIie3PsUrDQBzH8V8IxOXQNUFpX+F/BGKFal8lpWCXq3QMFGpAcMoD6Fv4CFcOzBLJGsjkXqRjxA7eSQWXM2uH+w7HDffhf3/A5TrCAjB9LkcgKTyJJQY46SFnP4RCjKSABCGG30Oi/EDGBzLN+wjVb6/hzpByIWVHN/MXBW/XYT20kubuNnrSJKk+0k1Bs4UmflQg4LmVsKRlhjSCJCPfEJwDzLORSV0l7V6TWJPNnu7npKd8AeHEOkWKpDXrc00UI5VqEugpNLV/TFx+FhQyXm1JXVDJn5X3eFVQOrOSuoqpy8YDKgV/32ar4Wn5oJouW1/byG/sz90sTj3vXS6Xy/Vv32zuV6AIfOwaAAAAAElFTkSuQmCC","orcid":"","institution":"University of Limpopo","correspondingAuthor":true,"prefix":"","firstName":"Ashwell","middleName":"Rungano","lastName":"Ndhlala","suffix":""},{"id":443773831,"identity":"6b589ec3-8dfe-441e-94c1-9528aefc84f4","order_by":2,"name":"Moshibudi Paulina Bopape-Mabapa","email":"","orcid":"","institution":"University of Limpopo","correspondingAuthor":false,"prefix":"","firstName":"Moshibudi","middleName":"Paulina","lastName":"Bopape-Mabapa","suffix":""},{"id":443773832,"identity":"f975ef7d-53d4-4f89-b67b-d805e71d758b","order_by":3,"name":"Bahlebi Kiberab Eiasu","email":"","orcid":"","institution":"University of Fort Hare","correspondingAuthor":false,"prefix":"","firstName":"Bahlebi","middleName":"Kiberab","lastName":"Eiasu","suffix":""},{"id":443773833,"identity":"aedf3547-cd62-499c-b1b1-867af91b1db8","order_by":4,"name":"Semakaleng Mpai","email":"","orcid":"","institution":"University of Limpopo","correspondingAuthor":false,"prefix":"","firstName":"Semakaleng","middleName":"","lastName":"Mpai","suffix":""},{"id":443773843,"identity":"36a3bd9c-e321-425b-9ad7-f2d2eeef727a","order_by":5,"name":"Patrick Nyambo","email":"","orcid":"","institution":"Agricultural Research Council–Vegetables, Industrial and Medicinal Plants","correspondingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"","lastName":"Nyambo","suffix":""}],"badges":[],"createdAt":"2025-02-03 13:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5951398/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5951398/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-17237-1","type":"published","date":"2025-08-29T15:58:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80821533,"identity":"b4315028-82b4-4067-931f-ba32d60b0efe","added_by":"auto","created_at":"2025-04-17 12:17:26","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":55382,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the literature identification and screening. Adapted from PRISMA [30]\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951398/v1/2d48859eb1c7ca1edc3b276f.jpg"},{"id":80821532,"identity":"80c7cc6e-de9e-4216-ad88-7982eaf32e34","added_by":"auto","created_at":"2025-04-17 12:17:26","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":79901,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of PM on vegetable (a) yield and (b) biomass. The horizontal dotted vertical line is the zero line. The solid black square indicates the mean ES, while error bars represent 95% confidence intervals. The letter “n” and “k” indicate the number of studies and observations respectively.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951398/v1/7707033736870ab1eaaa4fd5.jpg"},{"id":80821534,"identity":"dc4cd030-7c05-42d7-b92a-bfed9ddc403a","added_by":"auto","created_at":"2025-04-17 12:17:26","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":62782,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of PM color on vegetable (a) height and (b) stem diameter. The dotted vertical line is the zero line. The solid black square indicates the mean ES, while error bars represent 95% confidence intervals. The letter “n” and “k” indicate the number of studies and observations respectively.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951398/v1/63bf4c558ebe3ef63c0482f6.jpg"},{"id":80821535,"identity":"e2bd89d8-5eb4-4787-91b3-a6c746d96ee5","added_by":"auto","created_at":"2025-04-17 12:17:26","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":57615,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of PM on vegetable weed biomass. The horizontal dotted vertical line is the zero line. The solid black square indicates the mean ES, while error bars represent 95% confidence intervals. The letter “n” and “k” indicate the number of studies and observations, respectively.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951398/v1/6dd5914ee878fb7d3d3b227b.jpg"},{"id":80821538,"identity":"4a84c7fd-a284-4386-a851-b67da35440ee","added_by":"auto","created_at":"2025-04-17 12:17:26","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":59347,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of PM under vegetable production on temperature. The horizontal dotted vertical line is the zero line. The solid black square indicates the mean ES, while error bars represent 95% confidence intervals. The letter “n” and “k” indicate the number of studies and observations respectively.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951398/v1/c1c6c94db12f1df5bd4d100b.jpg"},{"id":80822330,"identity":"3eba578a-3bb1-4f03-a081-fc38015346aa","added_by":"auto","created_at":"2025-04-17 12:25:26","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":23693,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of PM on vegetable water use efficiency. The horizontal dotted vertical line is the zero line. The solid black square indicates the mean ES, while error bars represent 95% confidence intervals. The letter “n” and “k” indicate the number of studies and observations, respectively.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951398/v1/199986f7e2f1ea6623fa6abd.jpg"},{"id":80821540,"identity":"810c8388-03ff-47a5-8f35-43e3fec36b07","added_by":"auto","created_at":"2025-04-17 12:17:26","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":49144,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of PM under vegetable production on soil moisture content. The horizontal dotted vertical line is the zero line. The solid black square indicates the mean ES, while error bars represent 95% confidence intervals. The letter “n” and “k” indicate the number of studies and observations, respectively.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5951398/v1/a92677a8502fbf99aab3e337.jpg"},{"id":90345658,"identity":"503e93d0-223f-43c6-af7e-31dd7841dfb8","added_by":"auto","created_at":"2025-09-01 16:10:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1242176,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5951398/v1/a88d1084-7f62-4b59-8c26-72687c9e4ba1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Colored plastic mulch impacts on soil properties, weed density and crop productivity: A Metanalysis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eClimate change exacerbates agricultural system challenges such as increased land degradation, pests, disease, weed resistance, floods, drought, high temperatures, and changes in areas suitable for cultivation [1; 2; 3; 4]. As a result, sustainable and innovative agricultural initiatives are being implemented to overcome these challenges and meet the projected 10\u0026nbsp;billion global population by 2050 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Plastic mulching (PM) is an effective approach in managing soil and crop micro-environments, thereby increasing agricultural output. This technique was first employed in the 1950s for commercial vegetable production [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Approximately 30\u0026nbsp;million hectares of land are currently under PM, with 60% of which in China, Spain, France and Italy contributing about 120,000, 100,000, and 85,000 hectares, respectively [16; 5].\u003c/p\u003e \u003cp\u003eAccording to Ham et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and Shah and Wu, [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], PM can potentially enhance agricultural productivity by changing temperature and moisture regimes within the soil. Plastic mulching reduces evaporation from the soil, thus improving water use efficiency and reducing the need for irrigation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This is particularly important in arid regions with scarce water resources and low precipitation [10; 11]. Plastic mulching also lowers competition for resources by effectively controlling weed populations, thus improving crop productivity [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Furthermore, PM reduces the incidence of soil-borne diseases Shiukhy et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and hinders the growth of weeds that attract diseases [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The increased soil temperature significantly accelerates germination rate and plant growth [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, there are challenges associated with PM including the high cost of materials and labour, the environmental impact of plastic waste, and the potential for increased pest and disease pressures if not managed properly [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Despite these challenges, the overall potential benefits on crop productivity have made PM a valuable tool in sustainable agriculture [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Nevertheless, continuous research on this practice is crucial to optimize its benefits and mitigate the potential drawbacks [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough PM is widely utilized, various factors, like color, perforation, thickness, and application method, can potentially affect the benefits from its use. Among these, the color is considered the most critical, as it influences differences in thermal regimes, which subsequently alter soil dynamics and crop productivity [12; 15]. Different plastic colors create distinct microclimates around the soil and crop, consequently impacting productivity[12; 15]. The most common black PM exhibits a high capacity for absorption across the ultraviolet and infrared wavelengths of solar radiation Amare and Desta [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]] and it is known for its exceptional weed suppression and soil warming characteristics. Transparent PM also increases soil temperatures, which might be advantageous in colder regions but can also intensify the proliferation of weeds. Bright-colored PMs, e.g. red, green, and blue, are more reflective and can potentially enhance plant processes such as photosynthesis and discourage certain insect pest invasions [18;19;1]. Further research on colored PM is vital as it aids in optimizing the specific conditions required for growing crops, potentially resulting in higher yields and improved quality [20;21;22]. Moreover, understanding the efficacy of diverse colored mulches in varied climates, soil types, and crop species will assist farmers in making well-informed choices, thereby promoting more effective and environmentally friendly agricultural methods.\u003c/p\u003e \u003cp\u003eResearchers extensively examine the impact of various PM colors on crop productivity in vegetable production systems. For instance, a study conducted in Spain on loam soil under semi-arid conditions found that black PM significantly increased tomato yields by 98.3 t/ha in 2005, 62.8 t/ha in 2006 and 89 t/ha in 2007 growing seasons compared to the control [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, a study conducted in Brazil in clay soil under tropical conditions reported that the green and silver PM mulches resulted in a 33 and 34% increase in yield based on the total number of fruits of tomatoes [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Al-Zohiri [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] reported that potatoes grown in clay loam soil with a subtropical climate in Egypt under a red PM had significantly high yield of 20.36 t/fed. And 20.34 t/fed and vegetative growth compared to blue PM and the control (bare soil), though not differing significantly from black PM. In contrast, a study in Iran under a semi-arid climate on sandy clay soil reported that different colored PM did not significantly affect the total yield of potatoes [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The performance inconsistency of different colored PM across different regions, soils, and seasons, indicates the need for a comprehensive and systematic assessment. Such an approach can be effectively achieved through meta-analysis first-targeting vegetable production system. While meta-analyses have explored the impact of plastics on soil properties and productivity of field crop, focusing predominantly on studies from China [11; 27; 28; 29; 30], to date, no meta-analysis has consolidated findings specifically on the effects of different PM colors on soil and crop productivity under vegetable production. Therefore, this study aimed to conduct a meta-analysis to systematically assess the effects of PM color on selected soil properties and crop productivity under vegetable production, filling this gap in the existing literature.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Literature search\u003c/h2\u003e \u003cp\u003eA comprehensive search of literature was conducted to collect data on the influence of different colored PM on selected soil properties, weed density, growth, and yield of vegetable crops. Research reports were collected from different databases, such as Scopus, Science Direct, Cab Abstracts, Web of Science, and PubMed, which were accessed through the library of the University of Fort Hare. Other reports were downloaded from Google Scholar, after obtaining them from the reference section of some articles. The keywords used for searching articles in these databases were \u0026ldquo;colored plastic\u0026rdquo;, \u0026ldquo;mulch color\u0026rdquo;, \u0026ldquo;crop\u0026rdquo;, \u0026ldquo;nutritional quality\u0026rdquo;. The literature search was done between the 10th of December 2023 and the 6th of January 2024. For an article to be considered in the meta-analysis, the following criteria was used:\u003c/p\u003e \u003cp\u003e \u003col style=\"list-style-type:lower-roman;\"\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe study should have been conducted on a vegetable crop and compared at least one treatment of PM color with a control (bare soil).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe study should have been conducted only under field conditions.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe study should have data on at least one of the selected response variables (yield, weeds, soil properties).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe study should have been conducted in English language.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) were followed for screening of all articles. The publication year was restricted to the period between January 1990 \u0026ndash; December 2023, and any article published beyond this period was not included. Details of articles that could not be downloaded were sent to the Librarian to assist in acquiring them. Out of approximately 20 articles sent to the librarian, only 13 were acquired.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data collection and grouping\u003c/h2\u003e \u003cp\u003eThe study collected data on 13 response variables for crop parameters and soil properties. Crop parameters included crop yield, biomass (dry weight basis), plant height, stem diameter, and weed biomass. Soil properties included soil temperature, water use efficiency (WUE), moisture content, soil organic carbon (SOC), pH, total nitrogen, available phosphorus, and available potassium. The selection of these parameters included in this study was based on their significance in explaining the study aims, and their availability from the articles finally included in the study. Crop yield, biomass, and weed biomass were expressed as t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e as the base unit; WUE in kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; plant height and stem diameter in cm; soil organic carbon and total nitrogen in %, and available phosphorus and potassium in g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Thus, if the parameter was originally given in another form, it was converted to fit the base units used in this study. For instance, in cases where crop yield, biomass and weed biomass were expressed in kg/ha, it was converted into to t/ha by dividing by 1000. When the crop yield and biomass were given as weight per plant, the plant population was used for converting to t/ha. For plant height, and stem diameter where it was given as mm or m it was converted to cm by dividing by 10 and 100 respectively.\u003c/p\u003e \u003cp\u003eMulch color was the independent variable for all variables. The study consisted of about 25 vegetables, which including tomato, chilli, eggplant, pepper, cucumber, bottle gourd, melon, musk melon, watermelon, okra, pumpkin, squash, Swiss chard, lettuce, spinach, broccoli, cabbage, cauliflower, potato, sweet potato, radish, onion, ginger, cocoyam, and sugar beets, where mulch colours were chosen based on their impact on soil temperature, weed suppression, and crop productivity. The studies included in this meta-analysis covered a range of environmental and agronomic conditions to assess the effects of coloured plastic mulches. Climatic conditions varied from humid to semi-arid and arid regions, with mean annual temperatures ranging from 1.1\u0026deg;C to 34.5\u0026deg;C and precipitation between 19.1 mm and 4907 mm. The soil types across the studies included clay, loam, sandy clay loam, and sandy loam, influencing mulch effectiveness in heat retention, moisture conservation, and nutrient availability. Mulch application methods varied, with most studies applying mulch before planting and keeping it in place throughout the growing season. These conditions provide a broader context for understanding the findings of this meta-analysis and their applicability to different agricultural systems. The following additional variables from the articles were incorporated if provided: country, regional location, geographic coordinates (longitude and latitude), mean annual precipitation, temperature of the study site, climate zone, soil texture, and initial soil properties (including soil organic carbon, pH, total nitrogen, available phosphorus, and available potassium).\u003c/p\u003e \u003cp\u003eThe mean (M), standard deviation (SD), and sample size/replication (N) of the selected response variables were collected as the values required for the meta-analysis. The results presented in figures or charts were extracted using the GetData Graph Digitizer Software version 2.25 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://getdata-graph-digitizer.com/\u003c/span\u003e\u003cspan address=\"http://getdata-graph-digitizer.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Some of the articles did not report standard deviations but reported other related metrics such as standard error (SE) and coefficient of variation (CV) or did not report anything at all. Therefore, if the CV was given, the SD was calculated using Eq.\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eSD = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\text{C}\\text{V}}{100}\\:\\text{X}\\:\\text{M}\\text{e}\\text{a}\\text{n}\\)\u003c/span\u003e\u003c/span\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;. Eq.\u0026nbsp;1\u003c/p\u003e \u003cp\u003eIf SE was given, the SD was calculated using Eq.\u0026nbsp;2.:\u003c/p\u003e \u003cp\u003eSD\u0026thinsp;=\u0026thinsp;SE X \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sqrt{N}\\)\u003c/span\u003e\u003c/span\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;. Eq.\u0026nbsp;2\u003c/p\u003e \u003cp\u003eFor studies that did not report SD, SE, or CV, we assumed that the SD was 10% of the mean, and the mean was multiplied by 0,1 to get the SD [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Although efforts were made to obtain additional information for a specific article, no response was received from any of the corresponding authors contacted.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe metanalysis was done using the \u0026ldquo;metafor package\u0026rdquo; of the R Studio Software (version 4.0.3) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org/\u003c/span\u003e\u003cspan address=\"https://www.r-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The natural log (ln R) of the response ratio (R) was calculated as the effect size based on the relationship of the mean values of treatment \u003cem\u003e(Mt)\u003c/em\u003e and control response variables \u003cem\u003e(Mc)\u003c/em\u003e as in Eq.\u0026nbsp;3.\u003c/p\u003e \u003cp\u003eln RR = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{Mt}{Mc}\\)\u003c/span\u003e\u003c/span\u003e = ln \u003cem\u003eMt\u003c/em\u003e - ln \u003cem\u003eMc\u003c/em\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;Equation 3\u003c/p\u003e \u003cp\u003eWhere Mt and Mc are the mean values of the treatment and control response variables, respectively. A 95% confidence interval (CI) was used to determine if there were any significant differences. Thus, if the CI did not overlap with zero, a significant difference was observed between the treatment and control groups. Conversely, if the CI overlapped by zero, it implied that there was no significant difference between the control and treatment groups [32; 11; 30].\u003c/p\u003e \u003cp\u003eThe random-effects model using residual maximum likelihood (REML) was used to assess group differences using the \u0026ldquo;rma\u0026rdquo; function of the metafor package. Cochran\u0026rsquo;s Q and Higgins\u0026rsquo; I\u003csup\u003e2\u003c/sup\u003e were used to determine the heterogeneity of the effect size. I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;75%, 25\u0026ndash;75%, and I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;25% indicated high, medium, and low heterogeneity, respectively[28; 30]. The results were presented as forest plots using the \u0026ldquo;forest rma\u0026rdquo; function.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Overview of the study\u003c/h2\u003e \u003cp\u003eThe meta-analysis ultimately included 97 articles with 788 observations that satisfied the criteria \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e The research encompassed 25 countries from four continents, namely Africa, Asia, Europe, and North America. A significant number of studies were conducted in Asia and America, and the countries where most studies were carried out were the USA (21), India (17), Mexico (10), and China (6).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe mean annual temperature and precipitation ranged between 1.1\u0026ndash;34.5\u0026deg;C and 19.1\u0026ndash;4907 mm, respectively, while the major climatic zones where data were collected were mostly humid and semi-arid. The soil consisted of a range of textures, including clay, loam, clay loam, sand, sandy clay, sandy clay loam, sandy loam, and silt loam. Data was extracted from 25 vegetable crops; tomato was the most extensively studied crop and accounted for the largest dataset in the fruit crop category. Lastly, the study identified 10 PM, which were black, blue, green, grey, yellow, transparent, white, silver, brown, and red. Black PM was the most studied among the different PMs and was examined in almost every article.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Study heterogeneity and the overall effect\u003c/h2\u003e \u003cp\u003eThe Higgins and Thompson I\u003csup\u003e2\u003c/sup\u003e heterogeneity test indicated varied results with respect to the response variables assessed in this study \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Heterogeneity was highly significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in yield, biomass, height, stem diameter, WUE, stem diameter, weed biomass, moisture content, temperature, pH, AP, and K. Weed biomass showed the highest heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;93.03) while temperature, SOC, pH, and TN had the least heterogeneity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistics for heterogeneity report of effect sizes of all studied variables in the metanalysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eI\u003csup\u003e2\u003c/sup\u003e level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI\u003csup\u003e2\u003c/sup\u003e p value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYield\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1762.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiomass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e295.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e479.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emoderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStem diameter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWUE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e217.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emoderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeed biomass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1029.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e618.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoisture content\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e738.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoi organic carbon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e190.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Nitrogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAvailable Phosphorus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e291.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e205.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emoderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDF: degree of freedom, Q: test for heterogeneity, I\u003csup\u003e2\u003c/sup\u003e: total heterogeneity and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eThe results indicated high significant difference (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in the general effect of PM on most crop productivity parameters while pH (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and SOC (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) where the only soil properties showing significant differences \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOverall effects of the study of effect sizes of all studied variables in the metanalysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eci.lb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eci.ub\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ek\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYield\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiomass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStem diameter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeed biomass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-3.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWUE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoisture content\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSE: standard error, ci.lb and ci.ub: confidence interval (upper and lower levels) n: number of observations, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Effects of plastic mulch color on vegetable crop productivity\u003c/h2\u003e \u003cp\u003eThe use of colored PM significantly increased the yield of all vegetables compared to the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The green PM showed highest yield increase (ES\u0026thinsp;=\u0026thinsp;5.73, CI\u0026thinsp;=\u0026thinsp;3.92\u0026ndash;7.93) and it significantly differed from that of black PM (ES\u0026thinsp;=\u0026thinsp;2.53, CI\u0026thinsp;=\u0026thinsp;2.14\u0026ndash;2.92), white PM (ES\u0026thinsp;=\u0026thinsp;2.33, CI\u0026thinsp;=\u0026thinsp;1.47\u0026ndash;3.19), and transparent PM (ES\u0026thinsp;=\u0026thinsp;2.03, CI\u0026thinsp;=\u0026thinsp;1.63\u0026ndash;2.45). Yellow and brown PM did not have biomass data for evaluation. Similar to the yield, the assessed PM significantly increased the biomass of all vegetables compared to the control \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb\u003cb\u003e)\u003c/b\u003e. The highest increase in biomass was observed on the transparent PM. The biomass increases were significantly higher on transparent PM (ES\u0026thinsp;=\u0026thinsp;6.52, CI\u0026thinsp;=\u0026thinsp;5.17\u0026ndash;7.87) than on the black PM (ES\u0026thinsp;=\u0026thinsp;3.53, CI\u0026thinsp;=\u0026thinsp;2.39\u0026ndash;4.67). The lowest increase in biomass, were observed from silver PM (ES\u0026thinsp;=\u0026thinsp;6.52, CI\u0026thinsp;=\u0026thinsp;0.98\u0026ndash;3.54), white PM (ES\u0026thinsp;=\u0026thinsp;2.65, CI\u0026thinsp;=\u0026thinsp;1.80\u0026ndash;3.50) and blue PM (ES\u0026thinsp;=\u0026thinsp;2.73, CI\u0026thinsp;=\u0026thinsp;0.28\u0026ndash;5.17).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNo plant height data was available with respect to grey PM. Plant height of all crops was significantly increased by all PM colors compared to the control except for brown and yellow PM \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e. The highest increase in height of all plants was observed on the black PM (ES\u0026thinsp;=\u0026thinsp;1.95, CI\u0026thinsp;=\u0026thinsp;1.49\u0026ndash;2.42) which was significantly higher than the transparent PM (ES\u0026thinsp;=\u0026thinsp;0.9, CI\u0026thinsp;=\u0026thinsp;0.62\u0026ndash;1.19) white PM (ES\u0026thinsp;=\u0026thinsp;0.93, CI\u0026thinsp;=\u0026thinsp;0.35\u0026ndash;1.5) and yellow PM (ES\u0026thinsp;=\u0026thinsp;0.9, CI = -0.71\u0026ndash;2.67). Only the black PM significantly increased stem diameter of vegetable crops compared to the control \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb\u003cb\u003e)\u003c/b\u003e. The black PM demonstrated the greatest increase (ES\u0026thinsp;=\u0026thinsp;6.60, CI = -6.60\u0026ndash;19.24), while the lowest increase was found on the red PM (ES\u0026thinsp;=\u0026thinsp;0.46, CI = -1.17\u0026ndash;2.08).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe weed biomass did not have all the plastic mulch colors included in the study. Among the included plastic mulch colors, the results revealed that all the PM colors decreased the weed biomass compared to the control, although the biomass on the brown and green PM did not significantly differ from that on the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The largest decrease in weed biomass was observed on the red PM (ES = -9.04, CI =-13.33 \u0026ndash; (-4.76)) and did not significantly differ with all other PM colors. The brown (ES = -3.88, CI = -9.12 \u0026ndash; (-1.35)) and white (ES = -3.79, CI = -6.78 \u0026ndash; (-0.79)) PM had the least decrease in weed biomass. In addition, other P colors such as transparent, red and blue also had larger decrease in weed biomass after the red PM color.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Effects of plastic mulch color on soil properties\u003c/h2\u003e \u003cp\u003eThe assessment of all ten PMs in this study showed that only the yellow PM had absent data pertaining to soil temperature \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The black, blue, green, red, silver, transparent, and white PMs showed significant variations compared to the control, while brown, and grey PM did not show significant differences from the control. Among the PM, the black (ES\u0026thinsp;=\u0026thinsp;0.82, CI\u0026thinsp;=\u0026thinsp;0.69\u0026ndash;0.94) and brown (ES\u0026thinsp;=\u0026thinsp;0.85, CI = -0.02\u0026ndash;1.71) plastic mulching demonstrated the highest increase in soil temperature, although they were not significantly different from other PM. On the other hand, grey (ES\u0026thinsp;=\u0026thinsp;0.28, CI = -2.5\u0026ndash;0.80), and white (ES\u0026thinsp;=\u0026thinsp;0.38, CI\u0026thinsp;=\u0026thinsp;0.12\u0026ndash;0.63) plastic mulching had a lower increase in soil temperature compared to other PM.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe study included four PM colors (black, silver, transparent, and white) on water use efficiency of vegetables. The results revealed that all four PMs exhibited a significant improvement in water use efficiency compared to the control \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Among these PMs, the black PM demonstrated the most significant increase in water use efficiency, with an effect size (ES) of 1.95 (confidence interval [CI]\u0026thinsp;=\u0026thinsp;1.49\u0026ndash;2.42). Moreover, the black P significantly differed from the transparent PM (ES\u0026thinsp;=\u0026thinsp;0.90, CI\u0026thinsp;=\u0026thinsp;0.62\u0026ndash;1.19) and the white PM (ES\u0026thinsp;=\u0026thinsp;0.93, CI\u0026thinsp;=\u0026thinsp;0.35\u0026ndash;1.50).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRegarding soil moisture, only the colored PM, such as black, blue, green, red, silver, transparent, and white had data collected \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The black PM (ES\u0026thinsp;=\u0026thinsp;0.40, CI\u0026thinsp;=\u0026thinsp;0.03\u0026ndash;0.77) was found to have a significant increase in moisture content compared to the control. However, the other PM colors such as green (ES\u0026thinsp;=\u0026thinsp;0.28, CI = -0.25\u0026ndash;0.80), and silver (ES\u0026thinsp;=\u0026thinsp;0.68, CI = -3.16\u0026ndash;4.53) also increased soil moisture content. In contrast, the blue PM (ES = -0.48, CI = -3.93\u0026ndash;2.96), red PM (ES = -2.71, CI = -6.70\u0026ndash;1.28), transparent PM (ES = -0.29, CI = -2.01\u0026ndash;1.44), and white PM (ES = -0.08, CI = -0.85\u0026ndash;0.69) were found to decrease moisture content, with the greatest decrease observed in the red PM.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSoil chemical properties indicated significant changes when plastic mulches were applied \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e For instance, the soil organic carbon was significantly higher in the black PM than the control, with an ES of 0.19 (CI\u0026thinsp;=\u0026thinsp;0.03\u0026ndash;0.35). However, the black PM had a significant negative effect on soil pH compared to the control, with an ES of -0.31 (CI = -0.48 \u0026ndash; (-0.14)). On the other hand, the blue, silver, and white PMs significantly increased soil pH, with ES values of 2.62 (CI\u0026thinsp;=\u0026thinsp;0.44\u0026ndash;4.80), 3.21 (CI\u0026thinsp;=\u0026thinsp;0.79\u0026ndash;5.63), and 2.62 (CI\u0026thinsp;=\u0026thinsp;0.44\u0026ndash;4.80), respectively. On the available phosphorus, the grey (ES\u0026thinsp;=\u0026thinsp;2.03, CI\u0026thinsp;=\u0026thinsp;0.06\u0026ndash;4) and silver (ES\u0026thinsp;=\u0026thinsp;2.04, CI\u0026thinsp;=\u0026thinsp;0.64\u0026ndash;3.43) PM demonstrated the greatest increase, which also significantly differed from the control. Conversely, the black, blue, and white PMs showed the lowest increase in soil phosphorus content and did not significantly differ from the control. Regarding the available potassium, only the grey PM was found to significantly increase the available potassium, with an ES value of 2.03 (CI\u0026thinsp;=\u0026thinsp;0.06\u0026ndash;4.00). This increase was higher than that observed for the other PM. However, no increase was observed for the blue PM, with an ES of 0 (CI = -0.65\u0026ndash;2.77). Additionally, the black, silver, and white PMs had a similar increase, with an ES of 1.06 (CI = -0.65\u0026ndash;2.77).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffects of different PMs under vegetable production on soil chemical properties.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoil Properties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMulch Color\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEffect Size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOC (n\u0026thinsp;=\u0026thinsp;3, k\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack (n\u0026thinsp;=\u0026thinsp;3, k\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03\u0026ndash;0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH (n\u0026thinsp;=\u0026thinsp;4, k\u0026thinsp;=\u0026thinsp;84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack (n\u0026thinsp;=\u0026thinsp;4, k\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.48 \u0026ndash; (-0.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlue (n\u0026thinsp;=\u0026thinsp;1, k\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.44\u0026ndash;4.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSilver (n\u0026thinsp;=\u0026thinsp;1, k\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u0026ndash;5.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite (n\u0026thinsp;=\u0026thinsp;1, k\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.44\u0026ndash;4.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Nitrogen (n\u0026thinsp;=\u0026thinsp;4, k\u0026thinsp;=\u0026thinsp;84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack (n\u0026thinsp;=\u0026thinsp;1, k\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.65\u0026ndash;2.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlue (n\u0026thinsp;=\u0026thinsp;1, k\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.60\u0026ndash;1.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSilver (n\u0026thinsp;=\u0026thinsp;1, k\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.65\u0026ndash;2.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite (n\u0026thinsp;=\u0026thinsp;1, k\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.65\u0026ndash;2.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAvailable Phosphorus (n\u0026thinsp;=\u0026thinsp;4, k\u0026thinsp;=\u0026thinsp;86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack (n\u0026thinsp;=\u0026thinsp;15, k\u0026thinsp;=\u0026thinsp;131)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.16\u0026ndash;0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlue (n\u0026thinsp;=\u0026thinsp;3, k\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.66\u0026ndash;2.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrey (n\u0026thinsp;=\u0026thinsp;1, k\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06\u0026ndash;4.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSilver (n\u0026thinsp;=\u0026thinsp;4, k\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.64\u0026ndash;3.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite (n\u0026thinsp;=\u0026thinsp;3, k\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.63\u0026ndash;2.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAvailable Potassium (n\u0026thinsp;=\u0026thinsp;5, k\u0026thinsp;=\u0026thinsp;88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack (n\u0026thinsp;=\u0026thinsp;5, k\u0026thinsp;=\u0026thinsp;83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.65\u0026ndash;2.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlue (n\u0026thinsp;=\u0026thinsp;1, k\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.60\u0026ndash;1.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrey (n\u0026thinsp;=\u0026thinsp;1, k\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06\u0026ndash;4.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSilver (n\u0026thinsp;=\u0026thinsp;2, k\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.65\u0026ndash;2.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite (n\u0026thinsp;=\u0026thinsp;1, k\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.65\u0026ndash;2.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe letter \u0026ldquo;n\u0026rdquo; and \u0026ldquo;k\u0026rdquo; indicate the number of studies and observations respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe current metanalysis study was aimed at assessing the effects of different PMs on crop and soil productivity under vegetable production based on several studies conducted across the world that met our study criteria. The choice to focus on vegetables only was because that is the crop category in which PMs are mainly used and has immensely contributed to the yield increases. The current study consolidated several published articles \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e, providing a sufficient basis for conducting a meta-analysis. However, it is important to note that many of these studies originate from a limited number of countries, with a significant concentration in the USA, India, Mexico, and China. Although we observed 10 different PM colors, the black and transparent PMs were the most studied [19; 1]. This is because the black PM is the most popular choice as it is the most cost-effective option [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe application of PM, regardless of its color, resulted in significant improvements in all crop productivity parameters, including yield, biomass, height, stem diameter, while significantly reduced weed biomass \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e This is corresponding with several other studies in the literature that PMs enhance growth and development of numerous crops [20; 21; 22]. Plastic mulches regulate the microclimate and rhizosphere temperature of plants which significantly improves physiological and morphological activities such as cell expansion and enlargement [12; 7; 15]. Plastic mulches absorb substantial quantities of solar radiations, while preserving soil moisture content by reducing evaporation [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In addition, the meta-analysis showed that yield \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e, biomass \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb\u003cb\u003e)\u003c/b\u003e and water use efficiency \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e irrespective of the PM color was significantly different from the control which depicts the superiority of any PM color in improving these crop parameters.\u003c/p\u003e \u003cp\u003eThe impact of different PM colors on crop productivity is expected to vary. This is because colors absorb, transmit, radiate and reradiate, and reflect solar radiation differently, which heavily influences soil temperature dynamics and, ultimately, differences in crop growth, development and yield [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. However, although differences are expected and were observed in this study, the \u003cem\u003emodus operandi\u003c/em\u003e is that anything that strongly influence crop growth and development (for instance stem diameter and height in this study) will also strongly influence biomass and yield. But in this study, that was not the case. For instance, yield, biomass, height, and stem diameter increased the most, compared to the control, on green, transparent, black, and silver PMs, respectively. It was not observed that any specific color had a trend in dominating crop growth parameters, which in turn affected yield and biomass production. The reason for these inconsistencies could be the limited number of datasets collected for the several colors (blue, brown, green, red, silver, white and yellow) included in the study Wei et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]; Zhang et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], where the meta-analysis results were based on a few studies rather than in the case of black PM, where datasets were based on several studies. Another possible reason could be the disparities in edaphic and climatic factors encountered in the various study locations, such as soil texture, initial soil properties (including nutrient content, pH, and organic matter), climate (including rainfall and temperature), topography and the type of crops grown. In addition, weed biomass decreased as a result of PM, even though the brown and green mulch color did not differ significantly with the control. It is well known that PM acts as a barrier to weeds which reduce their germination and suppress their growth. This is one of the significant uses of PMs in vegetable production as weeds are problematic. PM has long been recognized as an effective means of controlling weed growth in vegetable production. Its capacity to impede weed germination and suppress their development is a key advantage in this context [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTemperature had the highest effect (n\u0026thinsp;=\u0026thinsp;40), followed by moisture content. The significant impact of soil temperature under PMs, as noted by Shiukhy et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], is primarily due to the direct influence of PMs on soil temperature. Plastic mulches alter soil temperature because they affect how solar radiation interacts with the soil [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This interaction depends on specific thermal properties of the plastic material used, such as reflectivity, absorptivity, and transmittance. These properties collectively determine the net effect of the PM on soil temperature. Changes in soil temperature can subsequently influence other soil properties and processes, such as moisture content, microbial activity, and nutrient availability, thus impacting overall crop growth and productivity [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. This study observed a general increase in soil temperature, although brown, green, and grey PM did not differ significantly from that of the control. Among the mulch colors, black and transparent PM colors showed the highest increase in soil temperature compared to other colors. The reason for the increase with black PM is its ability to improve the efficiency of increasing minimum, mean, and maximum soil temperatures [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This occurs through black PM\u0026rsquo;s ability to absorbs energy, which it will pass through the soil by conduction [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe efficiency of PM in enhancing water use efficiency is attributed to its capacity to reduce evaporation, thereby increasing the availability of water for plant growth. Furthermore, PM plays a crucial role in reducing the evapotranspiration of crops which also improves water use efficiency [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Practices that promote water use efficiency in agriculture have been applauded for their crucial role in boosting crop productivity with less water, particularly in arid and semi-arid regions where conserving water is essential [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Among the various PM colors, black mulch demonstrated the greatest increase, indicating its strong impact in enhancing water use efficiency. However, our meta-analysis observed an unexpected trend on the moisture content compared to what is typically reported in literature. It was found that PM colors such as blue, red, and transparent were associated with a decrease in moisture content, whereas the green and silver PM colors did not significantly differ from the control. Upon tracing the articles, we noted that the articles reporting this trend attributed it to the high rainfall and vegetation cover in the non-mulched plots [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This explanation is particularly relevant, especially regarding the timing of sampling, as it is expected that there would be higher moisture content in bare soil than in covered soil following a rainfall event, as the plastic mulch acts as a barrier preventing water from penetrating into the soil.\u003c/p\u003e \u003cp\u003eThe soil\u0026rsquo;s chemical properties comprised of few PM colors because of a few articles and datasets. This implies that there are still limited studies that have investigated the influence of PM color on soil chemical properties. Thus, further studies are needed to fill this gap, as soil chemical properties are central to crop production and yield. Soil organic carbon had only one color (black), soil pH and total nitrogen had four colors (black, blue, silver, and white), while available phosphorus and available potassium had five colors (black, grey, blue, silver, and white). Nevertheless, the few studies observed in this study generally showed that almost all PM colors improved soil properties compared to the control. However, the PM colors did not differ significantly from the control, except in few cases in pH, available phosphorus, and available potassium. The increase in SOC and pH is because PM increases the decomposition of organic matter due to an increase in soil temperature and moisture content. However, other authors MingFu et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] argued that PMs facilitate root and microbial respiration, which intensifies organic matter decomposition and significantly increases the CO\u003csub\u003e2\u003c/sub\u003e concentration. This, in turn, reduces the soil pH, which could be the reason why black PM decreased the pH. Regarding soil nutrients, it has been argued that PM increases soil nutrients in the soil, but the reduction in nutrients is due to plant uptake at the end of the season [41; 42]. This is also because PMs reduce nutrient loss by both leaching and surface runoff erosion, as the ground will be covered.\u003c/p\u003e \u003cp\u003eBlack plastic mulch is particularly effective due to its ability to efficiently absorb ultraviolet (UV), visible, and infrared wavelengths of solar radiation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This absorption significantly increases soil temperature by capturing high levels of radiation, thereby raising the minimum, maximum, and mean soil temperatures. The warmer soil, in turn, enhances weed suppression by inhibiting weed growth, particularly in weed-infested areas [43; 44]. This contributes to improved plant performance compared to other mulch colors. Furthermore, black plastic mulch enhances water use efficiency by reducing evapotranspiration from the soil surface [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. This results in less moisture loss, making it a key factor in protected agriculture by decreasing the need for frequent irrigation [46; 47]. In comparison to other mulch colors, such as white or transparent, black mulch has been shown to provide better thermal regulation and weed control, which are crucial for crop yield optimization. Additionally, the dark color creates an ideal environment for maintaining optimal soil temperatures, which contributes to healthier plant growth and higher productivity. Overall, the combination of heat retention, moisture conservation, and superior weed suppression makes black plastic mulch the preferred choice in many agricultural systems.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe study aimed at conducting a comprehensive meta-analysis to consolidate information on the effects of different colored PM on selected soil properties, weeds biomass and vegetable productivity. The results of the meta-analysis demonstrated that the application of PM with respect to crop parameters resulted on increased yield, biomass, plant height, and stem diameter compared to non-mulched. While on the other hand, the weed biomass was considerably reduced, which indicates a reduction in competition for available soil nutrients between the main crops and weeds, resulting in improved crop productivity. The chemical properties of soil have not been thoroughly studied which translates to a limited number of studies included in the dataset. Even though soil chemical properties, such as soil organic carbon, soil pH, total nitrogen, available phosphorus, and available potassium, have been under studied, the available reports indicated improved soil properties compared to non-mulched. In the context of these results, plastic mulching is anticipated to be a successful strategy for improving food security, mitigating the negative effects of soil degradation, climate change, and water resource scarcity in arid and semi-arid regions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAsanda Sokombela: Conceptualisation, Writing - Initial Draft, Writing - Revisions, Methodology, Data Curation, Investigation, Visualisation. Ashwell R. Ndhlala: Conceptualisation, Writing - Review and Editing, Supervision, Resources, Project Administration and Funding Acquisition. Bahlebi K. Eiasu: Conceptualisation, Writing - Review and Editing, Supervision and Resources. Moshibudi P. Bopape-Mabapa: Conceptualisation, Writing - Review and Editing, Supervision and Resources Patrick Nyambo: Writing - Review and Editing, Methodology, Supervision, Validation. \u0026nbsp; Semakaleng Mpai: Writing - Review and Editing, Methodology, Supervision, Validation. \u0026nbsp; All authors have read and agreed to the submitted version of the manuscript.\u0026nbsp;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Department of Science and Innovation (DSI), South African Government (Grant number DSCI/CONC2235/2021)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data will be available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNyochembeng LM, Mankolo RN (2021) Colored plastic mulch effects on plant performance and disease suppression in organically grown bell pepper (Capsicum annuum). \u003cem\u003eJournal of Agricultural Science (Toronto)\u003c/em\u003e 13: 11\u0026ndash;17. https://doi.org/10.5539/jas.v13n6p11\u003c/li\u003e\n\u003cli\u003eAly M, Ahmed N, El-Zawawy HAH, Ali B (2023) Effect of Nostoc clacicola as bio-fertilizer with plastic mulch on the growth and economic value of sweet pepper. \u003cem\u003eEgyptian Journal of Agricultural Research\u003c/em\u003e 101: 119\u0026ndash;130. DOI:10.21608/ejar.2023.165324.1286\u003c/li\u003e\n\u003cli\u003eHofmann T, Ghoshal S, Tufenkji N, Adamowski JF, Bayen S, Chen Q, Demokritou P, Flury M, H\u0026uuml;ffer T, Ivleva NP, Ji R, Leask RL, Maric M, Mitrano DM, Sander M, Pahl S, Rillig MC, Walker TR, White JC, Wilkinson KJ (2023) Plastics can be used more sustainably in agriculture. \u003cem\u003eCommunications Earth and Environment\u003c/em\u003e 4: 1\u0026ndash;11. https://doi.org/10.1038/s43247-023-00982-4\u003c/li\u003e\n\u003cli\u003eKaraer M, G\u0026uuml;ltaş HT, Kuş\u0026ccedil;u H (2023). The Effects of Plastic Mulched Drip Irrigation on Yield, Fruit Quality and Water Productivity of Table Tomatoes. \u003cem\u003eGesunde Pflanzen\u003c/em\u003e 75: 1591\u0026ndash;1599. https://doi.org/10.1007/s10343-023-00848-x\u003c/li\u003e\n\u003cli\u003eSaini J, Mirza AA (2022). Impact of colored plastic mulches on soil characteristics and strawberry crop productivity : A review. \u003cem\u003eThe Pharma Innovation Journal 2022;\u003c/em\u003e 11: 1117\u0026ndash;1123. https://doi.org/10.21273/hortsci.40.5.1371\u003c/li\u003e\n\u003cli\u003eIbarra-Jim\u0026eacute;nez L, Lira-Saldivar RH, Valdez-Aguilar LA, R\u0026iacute;o JL-D (2011). Colored plastic mulches affect soil temperature and tuber production of potato. \u003cem\u003eActa Agriculturae Scandinavica Section B: Soil and Plant Science\u003c/em\u003e 61: 365\u0026ndash;371. https://doi.org/10.1080/09064710.2010.495724\u003c/li\u003e\n\u003cli\u003eAmare G, Desta B (2021) Colored plastic mulches: impact on soil properties and crop productivity. \u003cem\u003eChemical and Biological Technologies in Agriculture\u003c/em\u003e 8. DOI:10.1186/s40538-020-00201-8\u003c/li\u003e\n\u003cli\u003eHam JM, Kluitenberg GJ, Lamont WJ (2019) Optical Properties of Plastic Mulches Affect the Field Temperature Regime. \u003cem\u003eJournal of the American Society for Horticultural Science\u003c/em\u003e 118: 188\u0026ndash;193. https://doi.org/10.21273/jashs.118.2.188 \u003c/li\u003e\n\u003cli\u003eShah F, Wu W (2020) \u003cem\u003eUse of plastic mulch in agriculture and strategies to mitigate the associated environmental concerns\u003c/em\u003e. (1st ed.). Vol. 164. Elsevier Inc. https://doi.org/10.1016/bs.agron.2020.06.005\u003c/li\u003e\n\u003cli\u003eIqbal R, Raza MAS, Valipour M, Saleem MF, Zaheer MS, Ahmad S, Toleikiene M, Haider I, Aslam MU, Nazar MA (2020). Potential agricultural and environmental benefits of mulches\u0026mdash;a review. \u003cem\u003eBulletin of the National Research Centre\u003c/em\u003e 44. https://doi.org/10.1186/s42269-020-00290-3\u003c/li\u003e\n\u003cli\u003eWang L, Coulter JA, Li L, Luo Z, Chen Y, Deng X, Xie J (2020). Plastic mulching reduces nitrogen footprint of food crops in China: A meta-analysis. \u003cem\u003eScience of the Total Environment\u003c/em\u003e 748: 141479. https://doi.org/10.1016/j.scitotenv.2020.141479\u003c/li\u003e\n\u003cli\u003eKader MA, Nakamura K, Senge M, Mojid MA, Kawashima S (2020). Effects of colored plastic mulch on soil hydrothermal characteristics, growth and water productivity of rainfed soybean. \u003cem\u003eIrrigation and Drainage\u003c/em\u003e 69: 483\u0026ndash;494. https://doi.org/10.1002/ird.2431\u003c/li\u003e\n\u003cli\u003eShiukhy S, Raeini-Sarjaz M, Chalavi V (2015) Colored plastic mulch microclimates affect strawberry fruit yield and quality. \u003cem\u003eInternational Journal of Biometeorology\u003c/em\u003e 59: 1061\u0026ndash;1066. https://doi.org/10.1007/s00484-014-0919-0\u003c/li\u003e\n\u003cli\u003eNgosong C, Okolle JN, Tening AS (2019) Mulching: A sustainable option to improve soil health. Soil fertility management for sustainable development, pp.231-249. https://doi.org/10.1007/978-981-13-5904-0_11\u003c/li\u003e\n\u003cli\u003eSpaldon S, Namgyal D, Hussain A, Tundup P, Angmo D, Kendra KV (2023) Effect of different mulch colors on the yield of cabbage in the cold arid region of Ladakh ( UT ), India. \u003cem\u003eEco. Env. \u0026amp; Cons\u003c/em\u003e 71\u0026ndash;75. https://doi.org/10.5958/2454-552x.2021.00161.4\u003c/li\u003e\n\u003cli\u003eKasirajan, S. and Ngouajio M. 2012. Polyethylene and biodegradable mulches for agricultural applications: a review Agronomy for Sustainable Development. 32: pp. 501-529\u003c/li\u003e\n\u003cli\u003eLalitha, M., Thilagam, V. K., Balakrishnan, N. \u0026amp; Mansour, M. (2010). Effect of plastic mulch on soil properties and Crop growth - a review. Agricultural Review, 31 (2): 145 \u0026ndash; 149.\u003c/li\u003e\n\u003cli\u003eCanul-Tun CE, Ibarra-Jim\u0026eacute;nez L, Valdez-Aguilar LA, Lozano-del R\u0026iacute;o AJ, C\u0026aacute;rdenas-Flores A, Zerme\u0026ntilde;o-Gonz\u0026aacute;lez A, Lozano-Cavazos CJ, Valenzuela-Soto JH, Torres-Olivar V (2017) Influence of colored plastic mulch on soil temperature, growth, nutrimental status, and yield of bell pepper under shade house conditions. \u003cem\u003eJournal of Plant Nutrition\u003c/em\u003e 40: 1083\u0026ndash;1090. DOI:10.1080/01904167.2016.1263331\u003c/li\u003e\n\u003cli\u003eMostafa H, Khater ES, Hamouda R (2020) Changes of root zone temperature, growth and productivity of broccoli cultivated with colored plastic mulches. \u003cem\u003eResearch in Agricultural Engineering\u003c/em\u003e 66: 112\u0026ndash;121. https://doi.org/10.17221/84/2019-rae\u003c/li\u003e\n\u003cli\u003eChang DC, Cho JH, Jin YI, Im JS, Cheon CG, Kim SJ, Yu HS (2016) Mulch and planting depth influence potato canopy development, underground morphology, and tuber yield. \u003cem\u003eField Crops Research\u003c/em\u003e 197: 117\u0026ndash;124. https://doi.org/10.1016/j.fcr.2016.05.003\u003c/li\u003e\n\u003cli\u003eAgyare RY, Abdulai MS, Buah SS, Ayipio E, Bonsu SK, Kamga RT (2017) Growth and Fruit Yield of Okro as Influenced by Genotypes and Mulch in the Guinea Savannah Conditions of Ghana. \u003cem\u003eInternational Journal of Agronomy\u003c/em\u003e 2017. DOI:10.1155/2017/9840130\u003c/li\u003e\n\u003cli\u003eLiang ZY, FengXin W, Shock CC, KaiJing Y, ShaoZhong K, JingTao Q, SiEn L, Zhang Y-L, Wang F-X, Shock CC, Yang K-J, Kang S-Z, Qin J-T, Li S-E (2017) Effects of plastic mulch on the radiative and thermal conditions and potato growth under drip irrigation in arid Northwest China. \u003cem\u003eSoil and Tillage Research\u003c/em\u003e 172: 1\u0026ndash;11. https://doi.org/10.1016/j.still.2017.04.010\u003c/li\u003e\n\u003cli\u003eAnzalone AA, Cirujeda A, Aibar J, Pardo G, Zaragoza C (2016) Effect of Biodegradable Mulch Materials on Weed Control in Processing Tomatoes Published by : Weed Science Society of America and Allen Press Linked references are available on JSTOR for this article : Weed Management - Techniques \u0026iuml; ^^ \u0026iuml; ^ a ^ i ^^ \u0026iuml; . ^^. \u003cem\u003eWeed Technology\u003c/em\u003e 24: 369\u0026ndash;377. DOI:10.1614/WT-09-020.1\u003c/li\u003e\n\u003cli\u003eMendon\u0026ccedil;a SR, \u0026Aacute;vila MCR, Vital RG, Evangelista ZR, de Carvalho Pontes N, dos Reis Nascimento A (2021) The effect of different mulching on tomato development and yield. Scientia Horticulturae, 275, p.109657. https://doi.org/10.1016/j.scienta.2020.109657\u003c/li\u003e\n\u003cli\u003eAl-Zohiri S (2013) Influence of Colored Plastic Mulches on Germination, Growth and Marketable Yield of Potato. \u003cem\u003eJournal of Productivity and Development\u003c/em\u003e 18: 405\u0026ndash;420. DOI:10.21608/jpd.2013.42585\u003c/li\u003e\n\u003cli\u003eAzad B, Hassandokht MR, Parvizi K (2015) Effect of mulch on some characteristics of potato in Asadabad, Hamedan. International Journal of Agronomy and Agricultural Research (IJAAR), 6(3), pp.139-147. https://doi.org/10.1007/s40093-017-0189-z\u003c/li\u003e\n\u003cli\u003eMak-Mensah E, Obour PB, Essel E, Wang Q, Ahiakpa JK (2021) Influence of plastic film mulch with biochar application on crop yield, evapotranspiration, and water use efficiency in northern China: A meta-analysis. \u003cem\u003ePeerJ\u003c/em\u003e 9. https://doi.org/10.7717/peerj.10967\u003c/li\u003e\n\u003cli\u003eQin Y, Chai Y, Li R, Li Y, Ma J, Cheng H, Chang L, Chai S (2022) Evaluation of straw and plastic film mulching on wheat production: A meta-analysis in Loess Plateau of China. \u003cem\u003eField Crops Research\u003c/em\u003e 275: 108333. https://doi.org/10.1016/j.fcr.2021.108333\u003c/li\u003e\n\u003cli\u003eWei H, Zhang F, Zhang K, Qin R, Zhang W, Sun G, Huang J (2022). Effects of soil mulching on staple crop yield and greenhouse gas emissions in China: A meta-analysis. \u003cem\u003eField Crops Research\u003c/em\u003e 284: 108566. https://doi.org/10.1016/j.fcr.2022.108566\u003c/li\u003e\n\u003cli\u003eZhang D, Mak-Mensah E, Zhou X, Wang Q, Obour PB (2023). Impact of Plastic Film with Wheat Straw Mulching on Maize Water Use Efficiency, Evapotranspiration, and Grain Yield in Northern China: a Meta-analysis. \u003cem\u003eJournal of Soil Science and Plant Nutrition\u003c/em\u003e 23: 867\u0026ndash;880. https://doi.org/10.1007/s42729-022-01089-z\u003c/li\u003e\n\u003cli\u003eAcutis M, Tadiello T, Perego A, Di Guardo A, Schillaci C, Valkama E (2022) EX-TRACT: An excel tool for the estimation of standard deviations from published articles. \u003cem\u003eEnvironmental Modelling and Software\u003c/em\u003e 147: 105236. https://doi.org/10.1016/j.envsoft.2021.105236 \u003c/li\u003e\n\u003cli\u003eGao H, Yan C, Liu Q, Ding W, Chen B, Li Z (2019) Effects of plastic mulching and plastic residue on agricultural production: A meta-analysis. \u003cem\u003eScience of the Total Environment\u003c/em\u003e 651: 484\u0026ndash;492. https://doi.org/10.1016/j.scitotenv.2018.09.105\u003c/li\u003e\n\u003cli\u003eMing ZZ, Yuan L, JianFei L, JingWei W, ZhenXing Z, Na X (2022) Changes of soil water and heat transport and yield of tomato (Solanum lycopersicum) in greenhouses with micro-sprinkler irrigation under plastic film. \u003cem\u003eAgronomy\u003c/em\u003e 12. https://doi.org/10.3390/agronomy12030664\u003c/li\u003e\n\u003cli\u003eTofanelli MBD, Wortman SE (2020). Benchmarking the agronomic performance of biodegradable mulches against polyethylene mulch film: A meta-analysis. \u003cem\u003eAgronomy\u003c/em\u003e 10. https://doi.org/10.3390/agronomy10101618\u003c/li\u003e\n\u003cli\u003eRajablarijani HR, Mirshekari B, AghaAlikhani M, Rashidi V, Farahvash F (2014). Sweet corn weed control and yields in response to sowing date and cropping systems. \u003cem\u003eHortScience\u003c/em\u003e 49: 289\u0026ndash;293.\u003c/li\u003e\n\u003cli\u003ePramanik P, Bandyopadhyay KK, Bhaduri D, Bhattacharyya R, Aggarwal P (2015) Effect of mulch on soil thermal regimes-a review. \u003cem\u003eInternational Journal of Agriculture, Environment and Biotechnology\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(3), pp.645-658. https://doi.org/10.5958/2230-732x.2015.00072.8\u003c/li\u003e\n\u003cli\u003eIbarra-Jim\u0026eacute;nez L, Zerme\u0026ntilde;o-Gonz\u0026aacute;lez A, Mungu\u0026iacute;a-Lopez J, Rosario Quezada-Mart\u0026iacute;n MA, De La Rosa-Ibarra M (2008). Photosynthesis, soil temperature and yield of cucumber as affected by colored plastic mulch. \u003cem\u003eActa Agriculturae Scandinavica Section B: Soil and Plant Science\u003c/em\u003e 58: 372\u0026ndash;378. https://doi.org/10.1080/09064710801920297\u003c/li\u003e\n\u003cli\u003eSingh A, Kaushal A, Garg S, Chawla N (2017) Effect of different colored plastic mulches on growth, yield and quality of drip fertigated bell pepper (Capsicum annum var. grossum). \u003cem\u003eIndian Journal of Horticulture\u003c/em\u003e 74: 292\u0026ndash;294. https://doi.org/10.5958/0974-0112.2017.00059.7\u003c/li\u003e\n\u003cli\u003eKhan MN, Ayub G, Ilyas M, Haq FU, Ali J, Alam A (2016) Effect of different mulching materials on weeds and yield of Chili cultivars. \u003cem\u003ePure Appl. Biol\u003c/em\u003e 5: 1160\u0026ndash;1170. https://doi.org/10.19045/bspab.2016.50139\u003c/li\u003e\n\u003cli\u003eMingFu S, YiChen K, WeiNa Z, XinYu Y, YanLing F, HuiFang Y, RuYan Z, AiXia G, ShuHao Q (in press). Plastic film mulching with ridge planting alters soil chemical and biological properties to increase potato yields in semi-arid Northwest China. \u003cem\u003eChemical and Biological Technologies in Agriculture\u003c/em\u003e 9: (21 January 2022). https://doi.org/10.1186/s40538-022-00284-5\u003c/li\u003e\n\u003cli\u003eD\u0026iacute;az-P\u0026eacute;rez JC, Phatak SC, Giddings D, Bertrand D, Mills HA (2005) Root zone temperature, plant growth, and fruit yield of tomatillo as affected by plastic film mulch. \u003cem\u003eHortScience\u003c/em\u003e 40: 1312\u0026ndash;1319. DOI:10.21273/HORTSCI.40.5.1312\u003c/li\u003e\n\u003cli\u003eSintim HY, Bandopadhyay S, English ME, Bary AI, DeBruyn JM, Schaeffer SM, Miles CA, Reganold JP, Flury M (2019) Impacts of biodegradable plastic mulches on soil health. \u003cem\u003eAgriculture, Ecosystems and Environment\u003c/em\u003e 273: 36\u0026ndash;49. https://doi.org/10.1016/j.agee.2018.12.002\u003c/li\u003e\n\u003cli\u003eGetachew, A. and Bizuayehu, D., 2021. Coloured plastic mulches: impact on soil properties and crop productivity. \u003cem\u003eChemical and Biological Technologies in Agriculture\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(1).\u003c/li\u003e\n\u003cli\u003eNwagwu, F.A., Obok, E.E., Umunnakwe, O.C. and Akpan, J.F., 2023. Influence of polyethylene film colour and soil solarisation duration on weed dynamics and performance of hybrid maize (Zea mays L.).\u003c/li\u003e\n\u003cli\u003eYang, D., Li, S., Kang, S., Du, T., Guo, P., Mao, X., Tong, L., Hao, X., Ding, R. and Niu, J., 2020. Effect of drip irrigation on wheat evapotranspiration, soil evaporation and transpiration in Northwest China. Agricultural Water Management, 232, p.106001.\u003c/li\u003e\n\u003cli\u003ePrem, M., Ranjan, P., Seth, N. and Patle, G.T., 2020. Mulching techniques to conserve the soil water and advance the crop production\u0026mdash;A Review. \u003cem\u003eCurr. World Environ\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e, pp.10-30.\u003c/li\u003e\n\u003cli\u003eDemo, A.H. and Asefa Bogale, G., 2024. Enhancing crop yield and conserving soil moisture through mulching practices in dryland agriculture. \u003cem\u003eFrontiers in Agronomy\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e, p.1361697. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Plastic mulch, crop productivity, climate mitigation, soil-nutrition","lastPublishedDoi":"10.21203/rs.3.rs-5951398/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5951398/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSoil degradation, climate change, and water scarcity worsen the declining crop productivity. Plastic mulches provide a sustainable solution, yet comprehensive evaluations of their effects, particularly in vegetable production, remain limited. This meta-analysis synthesizes 97 studies and 789 observations across 25 vegetable species to assess the influence of plastic mulch colour on crop yields and soil properties. Ten plastic mulch colors were analyzed: black, blue, green, gray, yellow, transparent, white, silver, brown, and red. Results show that all mulch colors improved crop productivity and soil parameters compared to non-mulched soil. Green (ES\u0026thinsp;=\u0026thinsp;5.73, CI\u0026thinsp;=\u0026thinsp;3.92\u0026ndash;7.93), transparent (ES\u0026thinsp;=\u0026thinsp;6.52, CI\u0026thinsp;=\u0026thinsp;5.17\u0026ndash;7.87), and black (ES\u0026thinsp;=\u0026thinsp;1.95, CI\u0026thinsp;=\u0026thinsp;1.49\u0026ndash;2.42) mulches produced the highest significant increase in yield, plant height, and stem diameter, respectively. The highest reduction in weed biomass occurred with red mulch (ES = -9.04, CI = -13.33\u0026ndash;-4.76). Increases in soil temperature and water use efficiency were noted from black (ES\u0026thinsp;=\u0026thinsp;0.82, CI\u0026thinsp;=\u0026thinsp;0.69\u0026ndash;0.94) and silver (ES\u0026thinsp;=\u0026thinsp;0.68, CI = -3.16\u0026ndash;4.53), while the black (ES\u0026thinsp;=\u0026thinsp;0.19, CI\u0026thinsp;=\u0026thinsp;0.03\u0026ndash;0.35), blue (ES\u0026thinsp;=\u0026thinsp;2.62, CI\u0026thinsp;=\u0026thinsp;0.44\u0026ndash;4.80), and gray (ES\u0026thinsp;=\u0026thinsp;2.03, CI\u0026thinsp;=\u0026thinsp;0.06\u0026ndash;4) mulches exhibited improved soil organic carbon, pH, total nitrogen, available phosphorus, and potassium, respectively. Besides black, the impacts of other colors are still under-explored, which limits the understanding of their effects on soil properties. Further studies are essential, as soil chemical characteristics are essential in agricultural productivity.\u003c/p\u003e","manuscriptTitle":"Colored plastic mulch impacts on soil properties, weed density and crop productivity: A Metanalysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-17 12:17:21","doi":"10.21203/rs.3.rs-5951398/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-03T05:20:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-22T05:14:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"178812471231281945437635873121153416497","date":"2025-04-17T03:18:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-16T10:22:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-29T10:17:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-20T10:49:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c3c18726-1c1b-439e-b61f-66796025e873","owner":[],"postedDate":"April 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47247645,"name":"Earth and environmental sciences/Environmental social sciences/Climate change adaptation"},{"id":47247646,"name":"Earth and environmental sciences/Environmental social sciences/Sustainability"},{"id":47247647,"name":"Biological sciences/Plant sciences/Light responses"},{"id":47247648,"name":"Biological sciences/Plant sciences/Plant development"},{"id":47247649,"name":"Biological sciences/Plant sciences/Plant domestication"}],"tags":[],"updatedAt":"2025-09-01T16:09:49+00:00","versionOfRecord":{"articleIdentity":"rs-5951398","link":"https://doi.org/10.1038/s41598-025-17237-1","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-08-29 15:58:09","publishedOnDateReadable":"August 29th, 2025"},"versionCreatedAt":"2025-04-17 12:17:21","video":"","vorDoi":"10.1038/s41598-025-17237-1","vorDoiUrl":"https://doi.org/10.1038/s41598-025-17237-1","workflowStages":[]},"version":"v1","identity":"rs-5951398","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5951398","identity":"rs-5951398","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}