Researching and Raising Awareness of Dynamic Accumulator Plants in the Northeast

The results and discussion will be divided into 4 sections: crop yields, plant tissue analysis, liquid nutrient analysis, and soil analysis.

1. Crop yields

Based on the USDA analysis discussed above, 6 trial crops were selected for on-farm trials. These crops were started indoors, transplanted into dedicated rows, and allowed to establish over the course of the first year of this study. All trial crops were then harvested during the second year, following established recommendations for when to harvest, where available. Multiple cuts were taken throughout the growing season whenever possible. Information such as harvest date ranges, average heights of trial crops at time of harvest, and yields were recorded and compared to available data on these crops (see Tables 2 and 3). All yields mentioned throughout this study refer to the weight of fresh material.

Some of the plants included in this study are not commonly cultivated, and there was a lack of relevant information available on them. For example, redroot amaranth is commonly regarded as a noxious weed, and studies of this plant to-date seem to be confined to its harmful effects on livestock and the yields of cash crops, its status as an invasive weed currently spreading across the globe, and how to effectively exterminate it. Others, specifically red clover and Russian comfrey, and, to a lesser extent, stinging nettle, are enjoying increasing interest due to their perceived potential economic benefits as cash crops and, in the case of red clover, also as a nitrogen-fixing cover crop.

Each of the six trial crops being studied was grown in a dedicated “extraction” trial row, measuring 3 ft wide and 25 ft long. These rows were allowed to establish during the first growing season and were repeatedly harvested over the second growing season, with the intent to extract as much nutrient-rich plant material as possible from the rows. Table 3 shows the yields from the “extraction” trial rows.

It is worth noting that the findings of this study are just as much an examination of the cultivation methods used and their suitability to the crops being trialed as they are an examination of the crops themselves. As this study set out to examine these 6 crops’ potential as dynamic accumulators, integrated into nutrient management plans of Northeast farms, an element of the study’s design is to assess the feasibility of establishing permanent rows of these crops, with minimal effort on the part of the farmer, relying on the plants to fend for themselves against weed pressure, moisture or nutrient deficiencies, and the challenges of maintaining a thick stand in the row year after year, either by renewing and spreading by rhizome (as in the case of Russian comfrey), by self-seeding (lambsquarters and redroot amaranth), or a combination of both (stinging nettle and red clover). For this reason, all trial crops were planted into unamended soil and given minimal attention, apart from 1 month of irrigation at the start of the first year and occasional hand weeding during the two years of the field trials. Another notable feature of the method of cultivation used in this study is that all rows were given 2 inches of wood chip mulch at the time of planting, consistent with Unadilla Community Farm’s method of establishing perennial rows in the food forest, where these field trials took place.

A. retroflexus: As shown in Table 3, harvest dates for redroot amaranth were 1 month later than expected, possibly due to the relatively cold, Northern location of the field trials, where frosts regularly extend into June. As a tender annual, redroot amaranth was slow to emerge in the spring, waiting for all danger of frost to pass before seedling emergence. While there doesn’t seem to be any data available on yields for this crop, based on observations made during field trials it seems this plant would be better suited to be grown as a single-cut annual, as is the norm for other commercially grown Amaranthus species. Second-year growth failed to meet the volume and vigor of first-year growth. It is possible that the use of wood chip mulch prevented adequate seed-to-soil contact. Uneven germination could also be an inherent feature of this species, suggesting seedlings could emerge year after year, interfering with subsequent crops but failing to maintain a thick stand over multiple years through self-seeding alone.

C. album: The harvest dates for lambsquarters fell within the established range, with a later start date and a shorter harvest window most likely due to the relatively cold climate and short seasons of the Northeast. However, despite exhibiting promising growth during its first year, it failed to adequately reseed to produce a thick stand during the second year, as evidenced by the low yields reported in Table 3. This was a commonality between both lambsquarters and redroot amaranth, the two annuals being trialed in this study that relied exclusively on self-seeding to maintain a thick stand across two seasons. As mentioned earlier, the use of wood chip mulch could have impeded the plants’ efforts to reseed; low germination rates could also be an inherent feature of both of these uncultivated species.

S. peregrinum: Russian comfrey made a strong performance in the on-farm trials. The harvest window for this crop exceeded established norms by about 2 weeks, and both the number of cuts (5) and the overall yield (60.1 tons/acre) were at the high end of the expected range. This could be owed in part to the use of wood chip mulch, which has the potential to both conserve soil moisture and reduce soil temperatures in the summer months, both of which have been shown to have a positive impact on comfrey yields (Hills, 1976; Teynor, Putnam, Doll, Kelling, Oelke, Undersander, and Oplinger, 1997). As a long-lived perennial and sterile hybrid that spreads exclusively via rhizome, its ability to thrive and spread were not negatively impacted by the mulch as some of the self-seeding trial crops were.

T. officinale: Dandelion’s harvest date range proved later than expected. However, by the second year of trials the dandelion was well established and producing relatively high yields (3 tons/acre), compared to established data (0.8-1 ton/acre). Dandelion’s strong performance could be due in part to the moisture-conserving and soil-cooling effects of wood chip mulch.

T. pratense: Red clover failed to establish a thick ground cover during on-farm trials. The first summer was hot and dry, and combined with a strategy of minimal irrigation and no intercropping, this resulted in dry soil and full sun exposure, factors that are known to result in poor red clover performance (Clark, 2007). These seasonal factors could have been mitigated with increased irrigation and/or interplanting with a grain or other early-harvest annual crop during the first season to provide shelter from extreme summer conditions (Hall, 2008). However, intercropping would have complicated efforts to isolate the effects of red clover on soil nutrient levels.

U. dioica: Stinging nettle thrived in the field trials, transplanting easily and spreading via rhizome to quickly fill in its test rows. As a moisture-loving plant, it is possible that the use of moisture-conserving wood chip mulch in this study helped fuel stinging nettle’s rapid growth and spread. It proved to be an excellent ground cover, outcompeting and suppressing weeds. During the second year, 4 cuts were taken, exceeding the normative range of 2-3. Total yields for the season (17.8 tons/acre) far surpassed the established range (8-8.7 tons/acre).

2. Plant tissue analysis

During the second year of field trials, plant tissue samples were collected from each of the six trial crops and dried on-site in a shade house converted into a drying shed. Plant tissue analysis was carried out by Cornell University’s nutrient analysis laboratory. Nutrient concentrations were then compared to data derived from the USDA database analysis discussed above. In the case of Russian comfrey, where no data is available in the USDA databases, nutrient concentrations were compared with data from the University of Minnesota agricultural experiment station (Robinson, 1983).

Table 4 lists nutrient concentrations, in ppm, for the 6 trial crops, as reported by the USDA databases and University of Minnesota agricultural experiment station, with nutrient concentrations that exceed dynamic accumulator thresholds displayed in bold. Table 5 expresses the same data, in the form of “percent of average.”

Table 6 lists nutrient concentrations for plant tissue samples collected during on-farm trials, with nutrient concentrations that exceed dynamic accumulator thresholds displayed in bold. Nutrient values overall are relatively lower, and there are fewer nutrient values that exceed dynamic accumulator thresholds, when compared to previous findings. This underscores the potential variability of plant tissue nutrient concentrations – while capable of impressive nutrient concentrations when grown in the right conditions, results can vary considerably from site to site. This suggests that dynamic accumulators may be better suited for tying up excessive nutrients in rich soil, rather than extracting desirable nutrients from poorer soil.

However, Table 6 does show 2 trial crops that demonstrate nutrient concentrations that exceed dynamic accumulator thresholds: lambsquarters (with a K concentration of 40,715 ppm) and Russian comfrey (with a K concentration of 52,959 ppm and an Si concentration of 513 ppm). While relatively high K concentrations for these two crops are consistent with available data, the sources referenced in Table 4 do not provide data for Si concentrations of Russian comfrey. Our findings indicate that in addition to K, Russian comfrey may be a dynamic accumulator of Si as well.

Comparing plant tissue samples (Table 6) with soil samples collected during the same year (Appendix 2) allows for the calculation of bioaccumulation factors (BAFs) for the trial crops. This is calculated by dividing plant tissue nutrient concentrations (in ppm) by “background” nutrient concentrations in the soil (also in ppm), and provides some insight into a plant’s ability to accumulate nutrients while taking into account the soil quality it was grown in. Table 7 displays BAFs for all trial crops, calculated using soil nutrient concentrations from 3 soil horizons (0-6”,6-12”, 12-24”). Table 8 displays BAF averages for all 6 trial crops. Bioaccumulation factors vary from site to site, but these values can be useful for making comparisons between trial crops within this study. It is also important to note that the soil analyses conducted in this study measured total nutrient concentrations, rather than available concentrations. This will skew the BAF values for nutrients that are mostly present in the soil in unavailable forms. For this reason, BAF values that fall below 1 (which normally indicates a plant is excluding a nutrient) will be included and compared in this discussion.

A. retroflexus: While redroot amaranth foliage failed to exhibit nutrient concentrations above dynamic accumulator thresholds, it did contain the highest concentrations of Al (17.7 ppm), Mn (87.4 ppm), S (2,431 ppm), and Zn (37.9 ppm) compared to all other trial crops. It also possessed the largest average BAF for all 4 of these nutrients, as well as for Mg. Most notably, redroot amaranth possessed a BAF for S of 7.4, indicating that it actively accumulated this nutrient at concentrations over 7 times greater than the surrounding soil. According to USDA data, redroot amaranth has been shown in previous studies to meet dynamic accumulator thresholds for Mg and Zn, among other nutrients, but there is no information available on its nutrient concentrations for Al, Mn, or S. Future research should investigate redroot amaranth’s Al, Mn, and S content when grown in a variety of soils, to assess its potential as a dynamic accumulator of these nutrients.

C. album: Plant tissue analysis revealed that lambsquarters accumulated a very high concentration of K (40,715 ppm), surpassing the concentration threshold for dynamic accumulators. It demonstrated a BAF of 47.8 for K, accumulating K concentrations over 47 times greater than the surrounding soil. Lambsquarters also accumulated the highest concentration of Mg (3,267 ppm) of all the trial crops, although its BAF for Mg was 1.3, indicating that lambsquarters’ Mg content was not terribly high relative to soil concentrations. Other relatively high bioaccumulation factors reported for lambsquarters include P (3.7), Ca (4.0), and S (6.0). The USDA databases confirm that lambsquarters has been shown to meet dynamic accumulator thresholds for P, K, and Ca, but there is no available USDA data on lambsquarters’ S concentrations, revealing an opportunity for further research.

S. peregrinum: Russian comfrey was shown to possess the highest concentrations of K (52,959 ppm), B (30.3 ppm), and Si (513 ppm) of all trial crops, with concentrations of K and Si surpassing dynamic accumulator thresholds. Russian comfrey also demonstrated the highest BAF of all trial crops for K (68.1) and B (0.13), with no data available for Russian comfrey’s BAF of Si. These findings are in alignment with data from Robinson (1983) showing Russian comfrey surpassing the dynamic accumulator threshold for K, although Robinson did not provide data on Si concentrations. Additional peer-reviewed research is needed on Russian comfrey’s plant tissue nutrient concentrations and bioaccumulation factors, especially for K and Si, when grown in a variety of soils.

T. officinale: The foliage of dandelion possessed the highest nutrient concentrations and bioaccumulation factors for P (3,495 ppm, BAF = 5.0), Cu (12.6 ppm, BAF = 1.2), and Na (169.5 ppm, BAF = 8.6) of all trial crops. Dandelion also possessed impressive BAFs for K (36.1), Ca (2.7), Mo (2.0) and S (7.2). According to USDA data, dandelion has been previously shown to accumulate above-average concentrations of P and K, and to surpass dynamic accumulator thresholds for Ca, Cu, and Na, among other nutrients. There is no peer-reviewed data available through USDA on dandelion tissue concentrations of Mo and S, revealing an opportunity for further research.

T. pratense: Plant tissue analysis for red clover shows the highest concentration and bioaccumulation factor for Fe (57.3 ppm, BAF = 0.0026) of all trial crops. This is in alignment with data from USDA, which shows red clover surpassing dynamic accumulator thresholds for Fe, among other nutrients. It should be noted that Fe soil concentrations reported in this study refer to total Fe, rather than available Fe, suggesting that red clover’s bioaccumulation factor for Fe is being underreported. Further research is needed to calculate BAFs for red clover, using available soil nutrient concentrations across a range of growing media, to further explore red clover’s potential as a dynamic accumulator of Fe.

U. dioica: Stinging nettle foliage demonstrated both the highest concentration and bioaccumulation factor for Ca (17,440 ppm, BAF = 8.1) of all trial crops. This is in alignment with data from USDA, which shows stinging nettle surpassing dynamic accumulator thresholds for Ca, among other nutrients.

3. Liquid nutrient analysis

During the second year of on-farm trials, plant material harvested from trial rows was steeped in rainwater, without agitation, to produce non-aerated liquid plant extracts, following the guidelines put forward by Brinton (2011). Rainwater catchment was used because of its affordability and widespread availability for Northeast farmers, and also to minimize the presence of dissolved solids in the water. Liquid temperature and pH was measured daily for all batches, using a digital pH meter with an accuracy rating of ±0.1 pH. This data is reported in Table 9.

The batches of liquid plant extracts were left to steep outdoors in a shaded location, to monitor the effects of temperature fluctuations on pH. Table 9 shows a range of recorded temperatures from 55.6°F to 84.9°F across all trials, with a mean temperature of 70.25°F. Temperature swings did not appear to significantly affect pH levels, and the mean temperature is quite close to Brinton’s recommendation of 72°F. This suggests that the naturally occurring temperature range on Northeast farms from June to September is conducive to producing non-aerated liquid plant extracts outdoors or in unheated buildings, reducing potential production costs for farmers.

The temperature and pH of the rainwater used for each batch was measured prior to adding plant material; these data points are expressed in Table 9 as entries with a steep time of 0 days. The pH of pure rainwater fluctuated from 5.3 to 5.9 across all batches. According to the United States Geological Survey (USGS, 2019), rainfall normally has a pH just under 6, while acid rain pH can range from 4.0 to 5.5. Our findings confirm USGS reports that the Northeast experiences acid rain as a result of air pollution. This complicates the formulation of non-aerated liquid plant extracts using rainwater on Northeast farms, as the ideal pH range for most vegetable crops is 5.5 to 7.0 (Liu and Hanlon, 2012). A recommendation to address this issue in future trials would be to correct rainwater pH prior to steeping plant material. The effects of pH and pH correction methods on nutrient solubility could be explored in future studies.

For all on-site measurements, pH steadily decreased once plant material was introduced, due to the almost immediate onset of fermentation during the steeping process. Table 9 shows the daily pH measurements taken on-site. After 3 and 5 days of steeping, liquid samples were mailed to the nutrient analysis laboratory. Table 10 shows pH measurements taken at the laboratory. There are some irregularities present in these pH measurements that are not present in the measurements taken on-site, including a higher frequency of rising pH levels, and an unlikely pH of 8.15 for a liquid sample of stinging nettle extract that had steeped for 3 days. This suggests that the laboratory’s measuring device was poorly calibrated at times, and brings into question the accuracy of the laboratory’s pH data. In future research, conducting all liquid nutrient analyses on-site would allow researchers to ensure testing is done in a timely manner and with properly calibrated equipment. That said, a steady decrease of pH over time would confirm the findings of Brinton (2011), and would indicate that regarding pH, a shorter steep time of 3 days would be preferable, to minimise the need for pH adjustment.

However, Table 10 also shows that nutrient concentrations generally increased from 3 to 5 days of steeping. Concentrations of B, Fe, Mg, and Mn always increased over this time period; Ca, K, Na, S, and Zn were twice as likely to increase; and concentrations of P increased from 3 to 5 days of steeping in all batches apart from one (the dandelion extract). Changes in the concentrations of Al and Cu did not follow a clear trend. These findings suggest that a steep time of 5 days would result in higher concentrations of desirable nutrients, when compared to a steep time of 3 days. However, it is unlikely that Northeast farmers relying on acid rain would be able to achieve acceptable pH levels over that time period without initially adjusting the rainwater’s pH.

Nutrient carryover from plant tissue to liquid plant extract was explored by comparing the results of the dried plant tissue analysis with the liquid nutrient analysis. Table 11 lists liquid extract nutrient concentrations, expressed as the percentage of dried plant tissue nutrient concentrations. The highest percentage of nutrient carryover for each nutrient, after both 3 days of steeping and 5 days of steeping, has been bolded.

The analysis of nutrient carryover provides a useful method of comparison between these 6 plants. However, since plant tissue nutrient concentrations for dried samples were used, this method of measuring nutrient carryover is skewed by differences in water content of fresh tissue. Therefore the results presented here are probably biased in favor of plants that possess less water content in their foliage. This bias could be addressed in future studies by either measuring nutrient concentrations in fresh plant tissue instead of dried, or by measuring the ratio of fresh weight to dry weight for plant tissue samples and factoring that into the calculation of nutrient carryover.

Another shortcoming of this liquid nutrient analysis is that it is limited to a single batch of liquid extract per plant. Due to the complex relationship between pH and nutrient solubility, further research is needed to study the production of non-aerated liquid plant extracts across multiple batches, using rainwater at different initial pH values. This would allow researchers to study the effect of pH on nutrient solubility. Different methods of pH adjustment and their effect on nutrient solubility should also be explored.

Finally, future studies should produce multiple batches of liquid extract for each set of variables, to allow for a larger sample size. This would allow for nutrient concentration ranges and averages to be drawn across multiple samples, minimizing the effect of data outliers or inaccuracies in measurement.

A. retroflexus: Redroot amaranth extract demonstrated the highest concentration and rate of nutrient carryover for Fe, when compared at both 3 days (1.13 ppm, 3.05% carryover) and 5 days (1.29 ppm, 3.51% carryover) of steeping. It also demonstrated the highest concentration and rate of nutrient carryover for S after 3 days (105.22 ppm, 4.33% carryover), although the fact that the concentration of this nutrient decreases by day 5 suggests these measurements could be inaccurate.

C. album: Liquid extract derived from lambsquarters foliage possessed the highest concentrations of all the trial crops for Al (0.49 ppm), Cu (0.10 ppm), Mg (48.35 ppm), and Zn (0.42 ppm) after a 3 day steep, and the highest concentrations of K (903.54 ppm), Al (0.53 ppm), Mg (56.43 ppm), and Zn (0.55 ppm) after a 5 day steep. Lambsquarters also demonstrated the highest rate of nutrient carryover for Al after 3 days (6.39%), and for Al (6.91%), Na (12.50%), and Zn (1.46%) after 5 days.

S. peregrinum: Russian comfrey extract possessed the highest K concentration of all the trial crops after 3 days of steeping (889.65 ppm), and the highest S concentration after 5 days (131.63 ppm). It produced the highest rate of nutrient carryover for S when compared to other batches at 5 days of steeping (8.87%).

T. officinale: Dandelion extract possessed the highest P concentration of all the trial crops after 3 days of steeping (62.05 ppm), and the highest Na concentration after both 3 days (1.57 ppm) and 5 days (2.22 ppm) of steeping. It did not demonstrate high rates of nutrient carryover for any nutrients, neither after 3 days nor 5 days of steeping.

T. pratense: Red clover extract was not measured as having high concentrations or rates of carryover for any nutrients.

U. dioica: Stinging nettle extract demonstrated the highest rates of nutrient carryover, both when compared at a 3 day steep time and at a 5 day steep time, for P (2.18%, 3.35%), K (2.65%, 3.21%), B (1.81%, 2.78%), Ca (1.76%, 2.04%), Cu (6.72%, 1.62%), Mg (1.83%, 2.07%) and Mn (2.21%, 2.98%). Stinging nettle also demonstrated the highest rate of nutrient carryover after a 3 day steep for Na (9.32%) and Zn (3.13%).

4. Soil analysis

Three rounds of soil samples were collected from all trial rows, at 3 soil horizons: 0-6”, 6-12”, and 12-24”. Soil samples were sent to Cornell nutrient analysis laboratory and underwent total elemental analysis. The first round of soil samples was collected during spring of the first year, before planting (see Appendix 1). A second round of soil samples was collected during spring of the second year, after all trial crops had been established in their rows over the course of the first growing season (see Appendix 2). A third and final round of soil samples was collected during autumn of the second year, after all rows had undergone heavy harvesting throughout the second growing season (see Appendix 3).

Appendix 4 illustrates the change in soil nutrient concentrations after the first year of growth, expressed as a percentage of initial soil concentrations. Stinging nettle rows saw the greatest overall reduction in soil nutrients when compared to other rows at 0-6” and 6-12” horizons, and specifically the greatest reduction in P and K levels in the top 0-6” of soil. Redroot amaranth rows also saw a relatively large decrease in Na levels, at all soil horizons. Conversely, rows planted with dandelion showed an overall increase in soil nutrients over the first year of growth. An unrealistic jump in boron concentrations is evident in Appendix 4, across all trial rows and all soil horizons. This suggests that there may have been an error made in the measuring or recording of boron levels. In light of this, all data on soil concentrations of boron will be ignored in this discussion.

During the second year of growth, all trial rows were heavily harvested, taking multiple cuts across the season whenever possible. One “extraction” row of each trial crop had its harvested plant material removed from the row. Table 12 shows the percent of change in soil nutrient concentrations across all extraction rows, calculated using data from the second round of soil samples (collected in the spring prior to harvesting) and the third round of soil samples (collected in the autumn following harvesting). Contrary to expectations, none of the extraction rows demonstrated a significant reduction in soil nutrient concentrations. On the contrary, the data shows a slight trend towards increasing concentrations for all nutrients apart from Na, which consistently decreased. In fact, the stinging nettle extraction row shows Mn concentrations more than doubling across all soil horizons. Similarly, the redroot amaranth extraction row shows large increases in Ca concentrations in the 0-6” horizon (347% increase) and the 6-12” horizon (208% increase). These unexpected results could be due to microbial activity and decomposing organic matter enriching the soil and more than compensating for the trial crops’ extraction of nutrients from the soil. The use of wood chip mulch in the trial rows and across the larger food forest where these trials took place could be contributing to this. Also, the decision not to harvest during the first year of this study, and instead to leave the trial crops to establish, resulted in all trial rows heavily mulching themselves over the winter, as above-ground plant material died back and covered the surface of the rows. This plant debris may have been decomposing and returning nutrients to the soil over the course of the second year.

During the second year of growth, one “chop and drop” row of each trial crop was mulched with the plant material that had been harvested from that row. Table 13 shows the percent of change in soil nutrient concentrations across all chop and drop rows, calculated using data from the second round of soil samples (collected in the spring prior to harvesting) and the third round of soil samples (collected in the autumn following the “chopping and dropping” of harvested material). This data shows a slight trend towards increasing concentrations for all nutrients apart from Na. The chop and drop rows tended to demonstrate larger nutrient increases than the extraction rows, apart from Na concentrations which consistently decreased.

A. retroflexus: As shown in Table 13, one year of chopping and dropping with redroot amaranth coincided with large increases in nutrient concentrations in the top 0-6” of soil for 10 nutrients: P (213%), K (197%), Ca (420%), Co (229%), Cu (246%), Mg (312%), Mn (232%), Ni (294%), S (252%), and Zn (225%). Interestingly, plant tissue analysis conducted as a part of this study shows redroot amaranth possessing the highest nutrient concentrations for Mn, S, and Zn, among others, and the largest bioaccumulation factors of any trial crop for Mg, Mn, S, and Zn, among others (see Tables 7 an 8). Data from the USDA phytochemical and ethnobotanical databases (see Tables 4 and 5) also shows redroot amaranth possessing high concentrations for several of these nutrients, meeting dynamic accumulator thresholds for 5 of them (P, K, Ca, Mg, and Zn), and failing to meet the threshold for only 1 of them (Cu). There is no data available in the USDA databases for 4 of these nutrients (Co, Mn, Ni, and S).

C. album: Soil nutrient concentrations of the lambsquarters “chop and drop” row did not differ greatly from the “extraction” row. This is most likely due to poor growth during the second year of trials (see the Crop Yields section of this discussion).

S. peregrinum: Despite producing yields much higher than any other trial crop (see Table 3), there was little difference in soil nutrient concentrations between Russian comfrey’s extraction row and chop and drop row (Table 12, Table 13). In fact, despite producing more than triple the mass of any other trial crop, there was little difference in soil nutrient concentrations after chopping and dropping with Russian comfrey (Table 13). The one notable change in soil nutrient concentrations in the Russian comfrey chop and drop row is a 293% increase in Cu concentrations in the top 0-6” of soil, which does not correlate with plant tissue Cu concentrations. This lack of change in soil nutrient concentrations could be explained by the relatively low nutrient concentrations of Russian comfrey’s foliage, reported both in this study (Table 6) and by Robinson (1983) (Table 4, Table 5). Unfortunately, the soil analyses conducted for this study do not include data on N or Si concentrations, Si being one of the two nutrients Russian comfrey has been shown to accumulate in high amounts. It is also possible that the widely reported benefits of mulching with Russian comfrey are not so much caused by its high nutrient content, but by other benefits resulting from mulching with plant tissue: increased organic matter, conservation of soil moisture, reduction in soil temperature, etc.

T. officinale: Soil nutrient concentrations did not noticeably increase in the dandelion chop and drop row. This could be due to dandelion’s relatively low yields, both projected and actual, when compared to the other trial crops (Table 2, Table 3).

T. pratense: Soil nutrient concentrations of the red clover “chop and drop” row did not differ greatly from the “extraction” row (Table 12, Table 13). This could be due to poor growth during the second year of trials (Table 3), combined with lower than expected nutrient concentrations in its foliage (Table 6).

U. dioica: Table 13 shows that one year of chopping and dropping with stinging nettle coincided with a doubling or more of soil nutrient concentrations for P, Ca, Co, Cu, Mg, Mn, Ni, and Zn over at least one soil horizon. Most notably, Ca levels more than doubled in both the 0-6” soil horizon (263%) and the 6-12” soil horizon (227%), while Ca levels dropped in the 12-24” soil horizon (63%). These findings are consistent with the hypothesis that dynamic accumulators enrich the topsoil by extracting nutrients from the subsoil. Plant tissue analysis conducted as part of this study (Table 6) showed stinging nettle foliage possessed the highest Ca concentrations of any of the trial crops (17,440 ppm), suggesting that chopping and dropping with calcium-rich stinging nettle foliage may have helped to enrich the topsoil with that nutrient. This hypothesis is further strengthened by a review of the USDA phytochemical and ethnobotanical databases (displayed in Tables 4 and 5), which found stinging nettle to possess Ca concentrations more than triple the average (307%).

Citations

Brinton, W. (2011). Making your own liquid fertilizer [PDF file]. Retrieved from https://opimedia.azureedge.net/-/media/Files/MEN/Editorial/Articles/Magazine-Articles/2011/02-01/Free-Homemade-Liquid-Fertilizers/Liquid-Fertilizers---Full-Report---Woods-End-Laboratories-pdf.pdf

Clark, A. (2007). Managing cover crops profitably (3rd ed.). Sustainable Agriculture Research and Education.

Hall, M. H. (2008). Agronomy facts 21: red clover [Fact sheet]. Penn State College of Agricultural Sciences. Retrieved from https://extension.psu.edu/downloadable/download/sample/sample_id/293/

Hills, L. D. (1976). Comfrey: past, present and future. London: Faber and Faber.

Liu, G. and Hanlon, E. (2012, September). Soil pH range for optimum commercial vegetable production. University of Florida Institute of Food and Agricultural Sciences. Retrieved from https://edis.ifas.ufl.edu/pdf%5CHS%5CHS120700.pdf

Robinson, R. (1983). Comfrey – a controversial crop. University of Minnesota Agricultural Experiment Station, AD-MR-2210.

Teynor, T. M., Putnam, D. H., Doll, J. D., Kelling, K. A., Oelke, E. A., Undersander, D. J., and Oplinger, E. S. (1997, November 17). Comfrey. Alternative Field Crops Manual. Retrieved from https://www.hort.purdue.edu/newcrop/afcm/comfrey.html

United States Geological Survey (2019, August 2). Acid rain and water. Retrieved from https://www.usgs.gov/special-topics/water-science-school/science/acid-rain-and-water