Effect of different colors of plastic-film mulching on the fresh weight of P. palustre
In this study, four colors (black, white, red, and green) of plastic-film mulching treatments were adopted (Fig. 1A), and we randomly selected 34, 35, 36, and 36 individual plants from the black film, white film, red film, and green film treatments, respectively. Then the fresh weight of each individual plant was weighed. The results showed that there were no significant differences in the fresh weight of single plant between four treatments (n≥34) (Fig. 1B). However, when n=top 28, the fresh weight of single plant of the green film treatment was significantly higher than that of the white film treatment (Fig. 1C). Compared with the white film treatment, the fresh weight of the green film treatment increased by 14.15%. In addition, the white film treatment showed the lowest fresh weight of single plant, although it was not significantly different from the other two treatments (black and red films).
Effect of different colors of plastic-film mulching on the soil temperature
The soil temperature of different treatments was also determined. As shown in Fig. 2, on May 18, 2022, the soil temperatures in the black and red film treatments were significantly higher than those in the other two treatments. At the second measurement, the highest soil temperature was observed in the red film treatment. The third measurement showed that the highest soil temperatures were found in the red and green film treatments. Based on the results of three temperature measurements, the soil temperature was almost the highest in the red film treatment and lowest in the white film treatment.
Metabolites of different treatments based on LC-MS
In this study, we extracted and analyzed the metabolites from the whole plant of P. palustre with six replicates of each treatment. The base peak chromatogram (BPC) indicted that the obtained data could be used for subsequent analysis (Fig. 3). In total, 1588 and 1604 metabolites were identified under the positive and negative ion scanning modes, respectively (Supplementary Fig. 1). Further analysis of correlation, PCA, Venn, and PLS-DA showed that the data were reliable (Supplementary Fig. 2). KEGG compound classification revealed that these metabolites included several categories: antibiotics, carbohydrates, hormones and transmitters, lipids, nucleic acids, organic acids, peptides, vitamins and cofactors, and so on containing 177 metabolites (Supplementary Fig. 3A; Supplementary Table 1). KEGG pathway exhibited that these metabolites were involved in biosynthesis of other secondary metabolites, amino acid metabolism, lipid metabolism, carbohydrate metabolism and so on (Supplementary Fig. 3B).
Differential metabolites analysis
The different groups could be better distinguished by OPLS-DA analysis (Fig. 4). The model was considered valid when Q2>50% and R2Y-Q2<0.3 26, and this criterion was satisfied in both positive and negative ion modes, so the OPLS-DA model fitted well in this study. To ensure the reliability of the results, the OPLS-DA model was also analyzed by permutation testing. As shown in Fig. 5, the Q2 intercept of all comparison groups was < 0.05 in both positive and negative ion modes. This indicated that the OPLS-DA model was feasible and the metabolites differed significantly between treatments.
Further, according to the VIP>1 and p<0.05, all the identified metabolites were used for screening the differential metabolites, and the results of the different comparison groups were analyzed. The results showed that a total of 1775 differential metabolites were identified in this study. Of these, there were 867, 821, 775, 743, 810, and 872 differential metabolites were identified in Green_vs_Black, Red_vs_Black, Red_vs_White, Red_vs_Green, Green_vs_White, and White_vs_Black, respectively (Supplementary Fig. 4). Based on these differential metabolites, KEGG compounds classification showed that a total of 103 differential metabolites were identified in this study (Fig. 6). These differential metabolites were classified into different categories, including phospholipids, monosaccharides, oligosaccharides, carboxylic acids, amino acids and so on (Supplementary Table S2). Among these, there were 42, 47, 42, 46, 57, and 39 differential metabolites in Green_vs_Black, Red_vs_Black, Red_vs_White, Red_vs_Green, Green_vs_White, and White_vs_Black, respectively (Supplementary Fig. 5). Further KEGG enrichment analysis revealed that the differential metabolites of different comparison groups were significantly enriched in different metabolic pathways (Supplementary Table 3). For example, in Green_vs_White, a total of 61 differential metabolites were involved in 7 metabolic pathways, which were the highest number of differential metabolites and metabolic pathways significantly enriched. This indicated the greatest difference between the two treatments. Conversely, the differential metabolites in Red_vs_Green were not significantly enriched in any metabolic pathway.
Monosaccharides
Polysaccharides are one of the most important quality indicators of P. palustre. Zhang, et al. 27 found that P. palustre polysaccharides consisted of eight monosaccharides including galacturonic acid, glucose, galactose, xylose, mannose, rhamnose, ribose, and glucuronic acid. In this study, five monosaccharides (gluconic acid, rhamnose, 2-deoxy-D-ribose, deoxyribose, and N-Acetylmannosamine) related to the quality of P. palustre were detected. As shown in Fig. 7, the gluconic acid, deoxyribose, and N-Acetylmannosamine in the red film treatment presented the highest abundance compared with the other treatments, meanwhile, the abundances of the five monosaccharides in the red film treatment were significantly higher than those of the green film treatment. It was inferred that the red film treatment could significantly increase the monosaccharide content and might be beneficial to the improvement of the quality of P. palustre.
Oligosaccharides
Oligosaccharide refers to any carbohydrate of from 3-6 units of simple sugars (monosaccharides). Here, we identified three oligosaccharides including sucrose, trehalose, and D-(+)-trehalose. The abundances of these three oligosaccharides in the black film treatment were significantly lower than those of the other treatments. On the contrary, these three oligosaccharides in the green film treatment exhibited the highest abundance (Fig. 8). Therefore, it was indicated that the green film treatment could promote the content of oligosaccharides of P. palustre. Meanwhile, the black film treatment was not conducive to the increase of oligosaccharide content in P. palustre in comparison with the other treatments.
Amino acids
In this study, we detected eight differential amino acids containing L-alanine, L-glutamine, L-phenylalanine, L-asparagine, L-(+)-arginine, L-tyrosine, Aspartic acid, and L-glutamic acid. As could be seen from Fig. 9, the abundances of eight different amino acids in red film treatment were almost the lowest, while those in black film treatment were almost the highest. Alanine, Serine, and Glycine are sweet amino acids in P. palustre, and Aspartic acid and Glutamic acid are delicious amino acids 28. This suggested that the black film treatment was beneficial to the improvement of the nutrition and flavor levels of P. palustre.
Correlation analysis of various indicators
In this study, the correlation analysis on the 18 indicators (except soil temperature) analyzed above were further performed. As shown in Table 1, Rhamnose was positively correlated with 2-Deoxy-D-ribose and negatively correlated with Trehalose and Sucrose (p<0.05). Gluconic Acid was positively correlated with N-Acetylmannosamine and Aspartic Acid but negatively correlated with L-Glutamine (p<0.05). 2-Deoxy-D-ribose was negatively correlated with Trehalose, D-(+)-Trehalose, and Sucrose while positively correlated with L-Glutamic Acid (p<0.05). Deoxyribose and L-Phenylalanine were positively correlated with N-Acetylmannosamine and Aspartic Acid and L-Tyrosine, respectively, while Sucrose and L-Alanine were negatively correlated with L-Glutamic Acid and Aspartic Acid. L-Glutamic Acid and L-Alanine had a significantly negative correlation with Trehalose and D-(+)-Trehalose and N-Acetylmannosamine, respectively, while there was a significant positive correlation between Sucrose, Trehalose, and D-(+)-Trehalose. In addition, there was a significantly positive correlation between N-Acetylmannosamine and Aspartic Acid, with a correlation coefficient of 100%.
Analysis of the membership function values of various indicators
We calculated the D values of the indicators for each treatment using membership functions. The higher the D value, the better the treatment. It could be seen from Table 2, the ranking of different treatments was black>red>white>green, indicating that the black and red film treatments might be more suitable for the cultivation and quality production of P. palustre in comparison with the other two
Table 2
Comprehensive evaluation of different treatments.
Treatment | µ(x) | D value | Ranking |
µ1 | µ2 |
Black | 0.7580 | 1.0000 | 0.8311 | 1 |
Green | 0.0000 | 0.1529 | 0.0462 | 4 |
Red | 1.0000 | 0.0000 | 0.6978 | 2 |
White | 0.2470 | 0.7085 | 0.3864 | 3 |