Colored plastic mulch impacts on soil properties, weed density and vegetable crop productivity: A meta-analysis

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 (effect size (ES) = 5.73, confidence interval (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.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-17237-1.

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^1-4. In response, sustainable and innovative agricultural initiatives are being implemented to overcome these challenges and meet the projected 10 billion global population by 2050³. One such practice is plastic mulching (PM), an effective approach in managing soil and crop micro-environments, to increase agricultural productivity. This technique was first employed in the 1950s for commercial vegetable production⁵. Currently, it is applied on approximately 30 million hectares worldwide, of which China accounts for with 60% of this area. Spain, France and Italy contribute about 120,000, 100,000, and 85,000 hectares, respectively^5,6.

According to Ham et al.⁷ and Shah and Wu⁸, PM can potentially enhance agricultural productivity by changing temperature and moisture regimes within the soil. By reducing evaporation, PM improves water use efficiency and reduces the need for irrigation⁴. This is particularly important in arid regions with scarce water resources and low precipitation^9,10. Additionally, PM lowers competition for nutrients and water by effectively controlling weed populations, thus improving crop productivity¹¹. It reduces the incidence of soil-borne diseases Shiukhy et al.¹² and limits the growth of weeds that attract diseases¹³. The increased soil temperature significantly accelerates germination rate and plant growth⁸. However, PM has its disadvantages which include 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 properly³. Despite these challenges, the overall potential benefits on crop productivity have made PM a valuable tool in sustainable agriculture³. Nevertheless, continuous research is crucial to optimize its use, benefits and mitigate the potential drawbacks⁸.

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^11,14. Different plastic colors create distinct microclimates around the soil and crops, consequently impacting productivity^11,14. The most common black PM exhibits a high capacity for absorption across the ultraviolet and infrared wavelengths of solar radiation Amare and Desta¹⁵ 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^16,17,1. 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^18,19,20. 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.

Plastic mulching in agriculture has mainly been used in horticultural crop production, focusing on vegetable and fruit cultivation⁶. Different coloured plastic mulches are utilized and have been reported to have potential to improve yields and quality of crops¹⁵. Researchers have extensively examined 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 control²¹. 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 tomatoes²². Al-Zohiri²³ 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 potatoes²⁴.

Methodology

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 were used:

• i.The study should have been conducted on a vegetable crop and compared at least one treatment of PM color with a control (bare soil).
• ii.The study should have been conducted only under field conditions.
• iii.The study should have data on at least one of the selected response variables (yield, weeds, soil properties).
• iv.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.

Data collection and grouping and publication bias

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 as the base unit; WUE in kg/ha/mm; plant height and stem diameter in cm; soil organic carbon and total nitrogen in %, and available phosphorus and potassium in g/kg. 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.

1

If SE was given, the SD was calculated using Eq. 2.

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 SD²⁵. Although efforts were made to obtain additional information for a specific article, no response was received from any of the corresponding authors contacted.

Funnel plots are commonly used to evaluate publication bias, but they require a variance measure like SE or SD, which most studies in this analysis did not provide. An alternative way to visualize publication bias is by plotting effect size distributions with density plots^26,27. A distribution of effect sizes that is approximately normal and centered around zero suggests the absence of publication bias, as it includes studies with positive, neutral, and negative effects. All evaluated parameters (crop yield, biomass, plant height, stem diameter, weed biomass, temperature, WUE, moisture content, SOC, pH, available phosphorus, and available potassium) except for total nitrogen were entirely close to zero. This suggests that publication bias was minimal in the articles utilized for this meta-analysis (Fig. S1). The sole exception was total nitrogen, which was represented by only one study (n = 1).

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.

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^10,28,29.

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’ I² were used to determine the heterogeneity of the effect size (ES). I² > 75%, 25–75%, and I² < 25% indicated high, medium, and low heterogeneity, respectively^30,28. The results were presented as forest plots using the “forest rma” function.

Results

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) (Fig. 2).

Fig. 1.

Flowchart of literature identification and screening. Adapted from PRISMA²⁸.

Fig. 2.

Diagram showing countries where studies included in the metanalysis.

The mean annual temperature and precipitation ranged between 1.1 and 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.

Study heterogeneity and the overall effect

The Higgins and Thompson I² 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 (I² = 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	I2	I2 level	I2 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, I² 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 < 0.01) and SOC (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.

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. 3a). 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. 3b). 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).

Fig. 3.

Effects 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.

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. 4a). 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. 4b). 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).

Fig. 4.

Effects of PM color on vegetable (a) height and (b) stem diameter. The dotted vertical line is 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.

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. 5). 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.

Fig. 5.

Effects 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.

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. 6). 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.

Fig. 6.

Effects 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.

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. 7). 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).

Fig. 7.

Effects 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.

Regarding soil moisture, only the colored PM, such as black, blue, green, red, silver, transparent, and white had data collected (Fig. 8). 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.

Fig. 8.

Effects 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.

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 available phosphorus, the 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. The black and silver PMs with an ES of 1.06 (CI = -0.65–2.77) had no significant increase in the available potassium.

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 = 81)	Black (n = 4, k = 81)	-0.31	-0.48 – (-0.14)
Total nitrogen (n = 4, k = 84)	Black (n = 1, k = 1)	1.06	-0.65–2.77
Available phosphorus (n = 4, k = 85)	Black (n = 15, k = 66)	0.02	-0.16–0.20
	Blue (n = 3, k = 4)	1.03	-0.66–2.74
	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
	Silver (n = 2, k = 2)	1.06	-0.65–2.77

The letter “n” and “k” indicate the number of studies and observations respectively.

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^1,17. This is because black PM is the most popular choice as it is the most cost-effective option¹⁵.

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^18,19,20. Plastic mulches regulate the microclimate and rhizosphere temperature of plants which significantly improve physiological and morphological activities such as cell expansion and enlargement^15,11,14. Plastic mulches absorb substantial quantities of solar radiation, while preserving soil moisture content by reducing evaporation³¹. In addition, the meta-analysis showed that yield (Fig. 3a), biomass (Fig. 3b) and water use efficiency (Fig. 7) 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 yield³². However, although differences are expected and were observed in this study, the modus operandi is that anything that strongly influences 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.³³; Zhang et al.²⁸, 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 context³⁴.

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.¹², 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 soil³⁵. 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 productivity³⁶. 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 temperatures⁵. This occurs through black PM’s ability to absorb energy, which it will pass through the soil by conduction³⁷.

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 efficiency³⁷. 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 essential³⁸. 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 in 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 plots¹. 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 a 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.³⁹ argued that PMs facilitate root and microbial respiration, which intensifies organic matter decomposition and significantly increases the CO₂ 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^40,41. 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 radiation¹⁵. 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^42,43. 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 surface⁴⁴. This results in less moisture loss, making it a key factor in protected agriculture by decreasing the need for frequent irrigation^45,46. 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.

The were fewer studies conducted which met the selection criteria of the meta-analysis, which limited the potential of the study to evaluate other variables like climate. In addition, subgroup analyses based on geographic regions or climatic conditions were not conducted, which can influence mulch performance. Variations in soil characteristics, crop management practices, and study designs were not accounted for, which may have contributed to the observed heterogeneity. Additionally, the lack of detailed reporting in primary studies limited our ability to perform deeper analyses. Another limitation of this study is the absence of funnel plot analysis to assess publication bias. While funnel plots are commonly used for detecting asymmetrical effects or selective publication, their interpretation requires a sufficient number of studies and consistent reporting of standard errors, which was not met in our dataset. Instead, we used density plots to explore the distribution of effect sizes across the included studies. Density plots, while not diagnostic for publication bias, allowed us to visualize the overall shape, skewness, and potential multimodality in the data. This approach helped identify patterns in the distribution of outcomes but does not replace formal bias detection methods.

Future research should focus on exploring the interaction between colored plastic mulch and region-specific environmental factors, such as climate, soil type, and farming practices, to better tailor mulch applications for different agro-ecological zones. Additionally, incorporating advanced meta-analytic techniques such as meta-regression and subgroup analyses will help clarify the role of moderating variables. There is also a need for more standardized and comprehensive reporting in primary studies to improve the quality of evidence synthesis. Expanding this research to include biodegradable and environmentally friendly mulch alternatives could also provide sustainable solutions for improving soil health, weed control, and vegetable crop productivity under changing climate conditions.

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 in 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.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

AS: Conceptualisation, Writing - Initial Draft, Writing - Revisions, Methodology, Data Curation, Investigation, Visualisation. AR: Conceptualisation, Writing - Review and Editing, Supervision, Resources, Project Administration and Funding Acquisition. BE: Conceptualisation, Writing - Review and Editing, Supervision and Resources. MP: Conceptualisation, Writing - Review and Editing, Supervision and Resources PN: Writing - Review and Editing, Methodology, Supervision, Validation. SM: Writing - Review and Editing, Methodology, Supervision, Validation. All authors have read and agreed to the submitted version of the manuscript.

Funding

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.

Declarations

Competing interests

The authors declare no competing interests.