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S1
—Appendix. Supplementary Information—
In situ Degradation of Biodegradable Plastic Mulch
Films in Compost and Agricultural Soils
Henry Y. Sintima,b, Andy I. Barya,b, Douglas G. Hayesc, Larry C. Wadsworthc, Marife
B. Anunciadoc, Marie E. Englishc, Sreejata Bandopadhyayc, Sean M. Schaefferc,
Jennifer M. DeBruync, Carol A. Milesd, John P. Reganoldb, and Markus Flurya,b,∗
aDepartment of Crop & Soil Sciences, Washington State University, Puyallup, WA 98371
bDepartment of Crop & Soil Sciences, Washington State University, Pullman, WA 99164
cDepartment of Biosystems Engineering and Soil Science, University of Tennessee,
Knoxville, TN, 37996
dDepartment of Horticulture, Washington State University, WSU Mount Vernon,
Northwestern Washington Research & Extension Center, Mount Vernon, WA 98273
Supplementary information includes details on ASTM D5988 test, mulch and soil character-
ization, meshbag study.
S2
S1 ASTM D5988 Biodegradation Test
Field-weathered BioAgri and PLA/PHA were retrieved from Knoxville field plots after the
pumpkin cropping season in 2017 (see below). Unused cellulosic paper mulch was used as
control. The mulch films were cut into 1 cm × 1 cm pieces (0.21 to 0.25 g) and added to
the soil (50 g) with a C:N ratio of 10:1 (g/g). The mixture was then placed into sample
jars and incubated at 27 oC following the ASTM D5988 standardized test protocol (ASTM
International, 2012). The soil, a Shady-Whitwell complex soil, was sieved (2 mm) and plant
debris were removed. Air samples were taken from the headspace of the jars, and CO2 evolu-
tion was measured using a CO2 infrared gas analyzer (LICOR 820,Lincoln, NE). The percent
biodegradation was calculated based on ASTM D-5988. Moles of CO2 were determined and
converted to microgram of carbon. Biodegradation was determined by the ratio of cumulative
carbon produced over the amount of original carbon from mulches added to the sample jar
(Figure S1).
S2 Physicochemical Characterization of Mulches
Analyses were performed on the initial mulches (as received from manufacturers) and after
deployment in the field. Paper mulch underwent complete macroscopic disintegration after
field deployment at Knoxville, and so no samples were remaining for analyses. The field-
weathered mulches were cleaned by gentle dry brushing to remove adhering soil and water
before the analyses. Details of the cleaning procedure and analyses used to characterize the
physicochemical compositions are reported elsewhere (Hayes et al., 2017). Below, we provide
a brief description of the methods.
S3
S21. Physical Analyses
Weight was determined gravimetrically on the mulch samples, with dimensions of 17.78 cm in
the machine direction and 15.24 cm in the cross-machine direction, and the same specimens
were used for thickness measurements with a TMI 49-70 Series Micrometer (Testing Machines
Inc., Amityville, NY). Percent elongation at maximum tensile stress in the machine direction
was determined according to ASTM D5035 (Model 5567, Instron, Norwood, MA) and a 10 kN
load cell. An initial gauge length between the clamps of the tensile tester was 2.54 cm instead
of the recommended 7.72 cm, because most of the field-weathered mulches were smaller
than the recommended specimen length of 15.24 cm. Water contact angle was measured
by the sessile drop method using a manual goniometer (model 147 50-00-115, Rame-Hart
Instrument Co., Netcong, NJ) at 20oC. Glass transition temperature (Tg) and melting point
temperature (Tm) were determined via differential scanning calorimetry; 3 to 7 mg samples
were analyzed using a model Q 2000 calorimeter from TA Instruments (New Castle, DE),
except the polyethylene mulch where the Tg was not measured, but values were taken from
the literature. Heating-cooling cycle for the differential scanning calorimetry was as follows:
heating at 10oC min−1 from 40oC to 200oC, and the temperature held constant at 200oC for
5 min, followed by cooling at 10oC min−1 until reaching −50oC, and the temperature held
constant at −50oC for 5 min. A second heating-cooling cycle was performed using the same
heating rate as the first cycle, except for polyethylene where a single heating-cooling cycle
was used.
S4
S22. Chemical and Molecular Analyses
Total carbon content (%C) and δ13C in the mulch samples were determined using a cavity
ring-down spectrometer (CRDS, Picarro G2121-i, Picarro Inc., Santa Clara, CA) coupled to
a combustion module (CM-CRDS, Costech Analytical Tech Inc., Valencia, CA). Internal lab-
oratory standards were used for all isotopic analyses, which were calibrated against certified
standards (USGS 41 and USGS 40, L-glutamic acid). Gel permeation chromatography was
used to determine the weight-averaged molecular weight of chloroform-soluble components
from the mulches. Only BioAgri, Organix, and PLA/PHA samples were analyzed.
S3 Effect of Meshbags on Mulch Degradation
Meshbags will likely affect mulch degradation because they hinder mass and energy transfer
between the mulches and the soil outside of the bags. The larger the meshbag opening, the
less is the effect on mulch degradation; however, large openings also allow non-degraded mulch
pieces to fall out, making quantifications difficult. In order to determine which meshbag size
would be suitable, we setup a pilot study in October 2014. We composted a biodegradable
plastic mulch (Bio360, manufactured by Dubois Agrinovation, Quebec, Canada), a PLA
fabric, and a paper mulch enclosed in 250-µm and 1-mm nylon meshbags. Mulch was placed
into meshbags (no compost was added to the meshbags so that we could retrieve the mulch
pieces without disturbance), and the meshbags were then placed into compost. The compost
was an aerated static pile containing broiler litter (28% vol.), dairy manure solids (28%), fish
carcasses (2%), bedding (14%), and yard wastes (28%). After 18 weeks of composting, we
could not visually detect mulch samples in either meshbag, except for black staining (more
conspicuous on 250-µm nylon meshbag) that was observed on the meshbags that contained the
S5
Bio360 (Figure S2). Thus, we concluded that the 250-µm opening was large enough to allow
access of bacteria and fungi to degrade the mulches during our composting study. Nonetheless,
the meshbags likely will have slowed down the degradation of the mulches in compost and soil;
however, without the use of meshbags it would be impossible to quantitatively recover buried
mulch samples. While the kinetics of the degradation may be affected by the meshbags,
the overall relative differences in the degradation among the mulches should not drastically
change. In addition, the use of paper mulch as a positive control treatment in this study will
enable us to determine the extent to which meshbags affect mulch degradation.
S4 Measurement of Soil Properties
Soil water content and temperature were monitored with sensors installed at 10-cm depth
(5TM sensor logged with EM50G data logger, Decagon Devices Inc., Pullman, WA). Other
soil properties were measured in September 2015, prior to mulch burial in soil. Soils were
sampled in the top 0 to 12 cm depth (composite of 15 random samples) with a soil core
sampler, air dried in the laboratory, and sieved through a 2-mm sieve. The soil samples
were then analyzed for soil pH, organic matter, nitrate-N, and available phosphorus by a
commercial laboratory (American Agricultural Laboratory, McCook, NE) following standard
soil testing procedures (NCERA, 2015). The composite soil samples were also analyzed for
soil respiration using the soil CO2-C burst Solvita test method (Woods End Laboratories,
2016).
Four enzymes were assayed: β-glucosidase, β-D-cellubosidase , β-xylosidase, and N-
acetyl-β-glucosaminidase, using 4-MUB-β-D-glucopyranoside, 4-MUB-β-D-cellobioside, 4-MUB-
β-D-xylopyranoside, and 4-MUB-N-acetyl-β-D-glucosaminide substrates, respectively. For
S6
enzyme analyses, soil was mixed with a sodium acetate trihydrate buffer, adjusting the pH
closely with respective soil pH values measured at the two sites. An aliquot of the soil slurry
(800 µL) was pipetted into 96-DeepWell plates, and 200 µL of appropriate standards and
substrates were added to the soil slurries. Separate plates were prepared using standard
curves of 4-methylumbelliferone and 7-amino-4-methylcoumarin synthetic fluorescent indi-
cators. The plates were sealed, inverted to mix the contents, and then incubated at room
temperature for 3 hours. The substrates and standard plates were centrifuged at 1500 rpm,
and the supernatants pipetted into black 96 well plates. Fluorescence microplate enzyme
assay was then performed using a BioTekTM plate reader (Winooski, Vermont) at excitation
wavelength of 365 nm and emission wavelength of 450 nm.
DNA from soil samples (0.25 g) was extracted with the MoBioTM PowerLyzerTM Power-
Soil DNA isolation kit with inhibitor removal technology. Extracted DNA was quantified with
the Quant-ItTM PicoGreenTM dsDNA Quantification Kit (ThermoFisher Scientific). Bacte-
rial and fungal abundances (16S rRNA and ITS gene copies, respectively) were quantified
from soil DNA samples using established protocols (FemtoTM Bacterial DNA quantification
kit and FemtoTM Fungal DNA quantification kit, Zymo Research). qPCR was done with a
CFX Connect Real-Time PCR Detection System (BioRad). All samples were analyzed in
triplicate.
DNA samples were shipped frozen to the Genomic Services Laboratory (GSL) at Hud-
son Alpha (Huntsville, AL) for 16S rRNA amplicon sequencing. The V4 region of the 16S
rRNA gene was amplified using primers 515F (GTGCCAAGCAGCCGCGGTAA) and 806R
(GGACTACHVGGGTWTCTAAT), and the first PCR was run with V4 amplicon primers,
Kapa HiFi master mix, and 20 cycles of PCR. PCR products were purified and stored at
S7
−20oC. The PCR indexing was later completed for the 16S (V4) amplicon batch. Products
were indexed using GSL3.7/PE1 primers, Kapa HiFi master mix, and 12 cycles of PCR. Final
libraries were quantified using Pico Green.
Raw sequence data was used to trim off primers, make contigs, remove sequences with
ambiguous bases and long homopolymers using mothur v.1.39.5 following the MiSeq SOP.
Before aligning to the reference database (SILVA release 102), unique sequences were identi-
fied. After alignment to SILVA database, sequences were filtered to remove overhangs at both
ends, and sequences de-noised by pre-clustering sequences with up to 2 nucleotide differences.
Chimeras were removed using the VSEARCH algorithm. All sequences including 18S rRNA
gene fragments and 16S rRNA from Archaea, chloroplasts, and mitochondria were classified
using the Bayesian classifier against the mothur-formatted version of the RDP PDS training
set (v.9) with a bootstrap value of >80% cut off and the general approach to using 80%
confidence in bootstrap values for phylogenetics. Following this step, untargeted (i.e., non-
bacterial) sequences classified as Eukaryota and Arachaeota were removed, and sequences
were binned into phylotypes according to their taxonomic classification at the genus level.
Beta diversity was computed using Bray-Curtis distances of microbial community com-
position (vegan package v 2.4-3 in R). Significant differences between bacterial community
composition at the two locations for Fall 2015 were analyzed by permutational multivariate
analysis of variance (ADONIS function in R) based on the Bray-Curtis dissimilarity matrix.
All libraries were scaled to even depth (minimum sample read count, i.e., smallest library
size of 34,328) before analysis was performed. Alpha diversity was computed by subsam-
pling the libraries to the minimum number of reads (34,328), with replacement to estimate
species abundance of the real population by normalizing sampling effort. The subsampling
S8
was repeated 100 times and the diversity estimates from each trial were averaged. The R phy-
loseq package (estimate richness function) was used to calculate richness (number of observed
OTUs) and Inverse Simpson index (for diversity).
S5 Estimation of Mulch Degradation in Soil
Upon retrieval from the soil, the meshbags containing the mulches were cleaned gently with a
soft brush and a slightly moistened terry cloth to remove adhering compost or soil, and then
air-dried. The meshbags were then cut open and the mulch pieces transferred onto a white
surface. The mulch fragments were spread uniformly on the white surface and photographed.
ImageJ software was used to digitize the photographs and measure the total area. The
total area was then expressed as percent or fraction of the initial surface area of the buried
mulch samples. The extent of mulch degradation (EoD) in equation (2) was evaluated by
numerically integrating the measured function f(T ) by the trapezoidal rule.
A 2nd-order polynomial model was used to estimate the degradation of BioAgri, Na-
turecycle, Organix, and PLA/PHA after soil incubation in Knoxville and Mount Vernon.
Mulch degradation was modeled as a function of thermal time, with 0oC base temperature,
and calendar time, separately for the two locations. Model performance was assessed by the
mean absolute error (MAE), normalized root mean squared error (NRMSE; normalized to
the range of observed data), coefficient of determination (R2), and index of agreement (d):
MAE =1
n
n∑i=1
|Pi −Mi| (S1)
NRMSE = 100
(1n
∑ni=1(Pi −Mi)
2
Mmax,i −Mmin,i
)(S2)
S9
R2 =
∑ni=1(Mi −Mave)(Pi − Pave)(√∑n
i=1(Mi −Mave)2) (√∑n
i=1(Pi − Pave)2)2
(S3)
d = 1−( ∑n
i=1(Pi −Mi)2∑n
i=1(|Pi −Mave|+ |Mi −Mave|)2
)(S4)
Mi and Pi are the measured and predicted values, respectively; Mave and Pave are the
average of the measured and predicted values, respectively, and n is the number of data;
MAE and NMSE ranges from 0 to +∞, where 0 is a perfect fit. R2 and d ranges from 0 to 1,
where 1 indicates a perfect fit.
References
ASTM International (2012). Standard Test Method for Determining Aerobic Biodegradation
of Plastic Materials in Soil, D5988–12. ASTM International, West Conshohocken.
Hayes, D. G., Wadsworth, L. C., Sintim, H. Y., Flury, M., English, M., Schaeffer, S. and
Saxton, A. M. (2017). Effect of diverse weathering conditions on the physicochemical
properties of biodegradable plastic mulches. Polymer Testing 62, 454–467.
Khonakdar, H. A., Jafari, S. H. and Hassler, R. (2007). Glass-transition-temperature depres-
sion in chemically crosslinked low-density polyethylene and high-density polyethylene
and their blends with ethylene vinyl acetate copolymer. J. Appl. Polym. Sci. 104, 1654–
1660.
Laredo, E., Suarez, N., Bello, A. and Marquez, L. (1996). The glass transition in low linear
S10
density polyethylene determined by thermally stimulated depolarization currents. J.
Appl. Polym. 34, 641–648.
NCERA (2015). Recommended chemical soil test procedures for the North Central Region.
North Central Regional Res. Publ. No. 221 ed. North Central Extension and Research
Activity, Madison, WI.
Trautmann, N. M. and Krasny, M. E. (1998). Composting in the classroom: scientific inquiry
for high school students. Chapter 1; The science of composting. Kendall/Hunt Publishing
Company, Dubuque, IA, USA.
Woods End Laboratories (2016). Soil CO2-burst official Solvita instructions. Woods End
Laboratories, Inc., Mt Vernon, ME.
S11
Tab
leS
1.P
hysi
coch
emic
al
pro
per
ties
ofth
ep
last
icm
ulc
hes
bef
ore
and
afte
rd
eplo
ym
ent
inth
efi
eld
du
rin
g20
15.
Val
ues
taken
from
Hay
eset
al.
(2017
),ex
cep
tw
hen
not
edot
her
wis
e.V
alu
esre
pre
sent
the
mea
n±
stan
dar
dd
evia
tion
(n=
4).
Mulc
hes
Wei
ght
Thic
knes
sE
longati
on
Mole
cula
rw
eight
Conta
ctangle
Tota
lca
rbon
δ13C
Tg
Tm
(gm−2)
(µm
)(%
)(k
Da)
(o)†
(%)
(h)
(oC
)(o
C)
Init
ial
Bio
Agri
23.1
±0.6
26.0
±2.0
260±
35
246±
12.8
88±
657.6
±1.8
−26.2
±0.2
−30.7
±0.5
93.5
±2.0
Natu
recy
cle
22.7
±1.6
48.0
±2.0
213±
45
na
69±
554.8
±0.6
−31.5
±0.2
−31.2
±0.4
105±
0.2
Org
anix
19.2
±0.7
20.0
±2.0
273±
29
251±
30.7
86±
451.4
±0.1
−29.8
±0.3
−30.1
±1.5
120±
0.6
PL
A/P
HA
26.2
±0.6
33.0
±2.0
247±
17
267±
7.3
68±
347.5
±0.2
−13.0
±0.0
49.2
±1.2
154±
0.0
Pap
er109±
1.2
479±
18
6.4
±0.6
na
<10
46.0
±1.8
−25.8
±0.2
na
na
Poly
ethyle
ne
22.5
±0.5
47.0
±2.0
578±
32
na
79±
282.9
±1.2
−30.0
±0.1
−120‡
110±
0.0
Knox
ville
(fiel
d-w
eath
ered
)
Bio
Agri
25.4
±1.9
78.0
±6.0
14.2
±7.1
185±
6.1
41±
346.0
±9.5
−25.8
±0.2
−28.9
±1.0
108.0
±1.7
Natu
recy
cle
38.9
±2.8
132±
2.0
6.1
±0.6
na
37±
751.6
±0.8
−31.3
±0.1
na
na
Org
anix
20.7
±0.4
74.0
±8.0
11.3
±1.1
211±
3.9
47±
248.2
±1.5
−29.1
±0.1
−29.4
±0.2
110±
2.5
PL
A/P
HA
28.9
±0.7
58.0
±4.0
5.3
±0.4
226±
4.5
52±
643.5
±1.2
−12.5
±0.1
49.7
±2.6
155±
0.1
Pap
erna
na
na
na
na
na
na
na
na
Poly
ethyle
ne
24.3
±0.5
59.0
±4.0
411±
35
na
53±
777.2
±0.5
−30.1
±0.1
na
110±
0.1
Mount
Ver
non
(fiel
d-w
eath
ered
)
Bio
Agri
23.0
±0.8
38.0
±4.0
28.4
±5.4
297±
6.6
40±
2na
na
−30.0
±1.3
98.7
±5.3
Natu
recy
cle
28.4
±1.2
58.0
±2.0
7.9
±0.9
na
56±
3na
na
na
na
Org
anix
19.5
±0.4
31.0
±2.0
79.5
±20.4
265±
11
35±
4na
na
−29.2
±0.4
110±
1.7
PL
A/P
HA
26.6
±0.3
37.0
±2.0
7.2
±0.3
218±
6.5
59±
2na
na
48.3
±2.8
154±
0.1
Pap
er111±
0.4
522±
20
5.6
±0.4
na
<10
na
na
na
na
Poly
ethyle
ne
26.3
±0.4
50.0
±4.0
378±
35
na
78±
3na
na
na
110±
0.1
Tg:
Gla
sstr
an
siti
on
tem
per
atu
re;
Tm
:M
elti
ng
poin
tte
mp
eratu
re.
† :M
easu
red
at
20oC
.‡
Valu
eta
ken
from
Lare
do
etal.(L
are
do
etal.,
1996)
an
dK
hon
akd
ar
etal.(K
hon
akd
ar
etal.,
2007).
na:
Data
not
availab
le.
Th
eT
gan
dT
mof
PL
A/P
HA
refl
ects
that
of
PL
A,
wh
erea
sth
at
of
Bio
Agri
,N
atu
recy
cle
an
dO
rgan
ixre
flec
tsP
BA
T.
Mole
cula
rw
eight
refl
ects
chlo
rofo
rm-s
olu
ble
com
pon
ents
from
the
mu
lch
es.
S12
Tab
leS
2.B
acte
rial
and
fun
gal
ab
un
dan
cefo
rd
iffer
ent
mu
lch
trea
tmen
tsfo
rF
all
2015
and
Fal
l20
18.
Ab
un
dan
ces
are
inlo
g10
gen
eco
pie
sg−
1d
ryso
il.
Tre
atm
ent
Knox
ville
Mount
Ver
non
Fall
2015
Fall
2018
Fall
2015
Fall
2018
16S
ITS
16S
ITS
16S
ITS
16S
ITS
Bio
Agri
9.3
96±
0.1
60
8.5
85±
0.1
41
9.1
43±
0.3
59
8.3
72±
0.5
38
9.2
91±
0.4
30
8.152±
0.397
9.7
29±
0.2
18
9.777±
0.312
Natu
recy
cle
9.5
07±
0.0
45
8.7
36±
0.0
79
9.1
75±
0.2
61
8.2
05±
0.3
25
9.6
42±
0.2
22
8.481±
0.361
9.8
08±
0.1
07
9.530±
0.094
No
Mulc
h9.5
11±
0.3
01
8.6
94±
0.3
69
9.2
18±
0.2
25
8.3
90±
0.5
29
9.683±
0.128
8.867±
0.201
9.948±
0.159
9.658±
0.103
Org
anix
9.6
86±
0.3
62
8.6
29±
0.3
15
9.3
21±
0.2
44
8.9
09±
0.2
87
9.370±
0.049
8.469±
0.148
9.799±
0.045
9.521±
0.088
PL
A/P
HA
9.3
15±
0.2
54
8.4
83±
0.2
42
9.1
17±
0.5
17
8.6
80±
0.9
46
9.405±
0.171
8.301±
0.190
9.784±
0.157
9.526±
0.111
Poly
ethyle
ne
9.2
51±
0.2
10
8.213±
0.311
9.2
44±
0.0
92
8.841±
0.419
9.274±
0.219
8.280±
0.146
9.812±
0.079
9.625±
0.073
Pap
er9.3
21±
0.2
31
8.4
76±
0.3
42
9.1
71±
0.5
48
8.4
17±
0.8
19
9.565±
0.222
8.453±
0.262
9.677±
0.210
9.329±
0.174
16S:
bact
eria
lm
ark
ergen
e
ITS:
fungal
mark
ergen
e
Num
ber
sin
bold
face
indic
ate
signifi
cant
diff
eren
ces
atP
=0.0
5of
bact
eria
land
fungal
gen
eco
pie
sb
etw
een
Fall
2015
and
Fall
2018
S13
Table S3. Chemical and biological properties of the soil at Knoxville and Mount Vernon,before meshbag burial in Fall 2015.
Soil parameters Units Sites
Knoxville Mount Vernon
Soil pH 5.70 ± 0.39 5.82 ± 0.23
Nitrate-N mg kg−1 10.7 ± 3.9 17.0 ± 15.9
Available P mg kg−1 79.9 ± 28.0 91.4 ± 10.4
Organic matter g kg−1 15.2 ± 1.9 23.4 ± 1.3
CO2-C mg kg−1 8.52 ± 3.30 40.9 ± 15.1
β-glucosidase µmol activity hr−1 g−1 soil 40.0 ± 14.0 47.2 ± 14.7
β-D cellobiosidase µmol activity hr−1 g−1 soil 8.58 ± 5.03 13.2 ± 4.4
β-xylosidase µmol activity hr−1 g−1 soil 1.06 ± 1.53 2.41 ± 1.55
N-acetyl β glucosaminidase µmol activity hr−1 g−1 soil 8.43 ± 5.75 15.2 ± 4.7
Values represent the mean ± standard deviation (n = 24).
S14
Tab
leS
4.B
act
eria
lan
dfu
ngal
abu
nd
an
cean
dd
iver
sity
and
rich
nes
sin
the
soil
atK
nox
vil
lean
dM
ount
Ver
non
inF
all
2015
.A
bu
nd
ance
sare
per
dry
soil
mas
s.
Loca
tion
Bac
teri
alab
un
dan
ceF
un
gal
ab
un
dan
ceD
iver
sity
Ric
hn
ess
log10
(16S
gen
eco
pie
sg−1
soil
)lo
g10
(IT
Sgen
eco
pie
sg−1
soil
)(I
nve
rse
Sim
pso
nin
dex
)(N
rof
ob
serv
edO
TU
s)
Kn
oxvil
le9.
41±
0.16
8.5
2±
0.1
87.95±0.27
271±10
Mou
nt
Ver
non
9.43±
0.15
8.3
6±
0.1
38.71±0.37
259±7
Nu
mb
ers
inb
old
face
ind
icat
esi
gnifi
cant
diff
eren
ces
atP
=0.
05
bet
wee
nth
etw
olo
cati
on
s
OT
U:
Op
erat
ion
alT
axon
omic
Un
it
S15
Table S5. Evaluation of the performance of 2nd-order polynomial models used to estimatedegradation of the different biodegradable plastic mulches.
Thermal Time Calendar TimeMulch MAE NRMSE R2 d MAE NRMSE R2 d
KnoxvilleBioAgri 8.0 13.2 0.79 0.94 8.2 13.3 0.79 0.94Naturecycle 7.5 11.2 0.88 0.97 7.5 11.4 0.88 0.97Organix 5.8 9.1 0.93 0.98 7.0 10.4 0.91 0.98PLA/PHA 4.9 7.6 0.95 0.99 4.8 7.9 0.94 0.98
Mount VernonBioAgri 3.8 11.9 0.79 0.94 3.8 12.2 0.79 0.94Naturecycle 4.5 9.7 0.91 0.98 5.1 10.8 0.88 0.97Organix 2.8 10.9 0.88 0.97 2.7 10.9 0.87 0.97PLA/PHA 2.9 13.4 0.76 0.92 3.2 14.0 0.75 0.91
MAE: mean absolute error (MAE); NRMSE: normalized root mean squared error (normalizedto the range of observed data); R2: coefficient of determination; d: index of agreement
S16
0
25
50
75
100
0 20 40 60 80 100
Bio
degr
adat
ion
(%)
Time (d)
PLA/PHA
BioAgri
Paper (Cellulosic)
Fig. S1. Biodegradation as determined by CO2 release from biodegradable plastic mulches(BioAgri and PLA/PHA) and paper mulch (cellulose) during soil incubation under controlledlaboratory conditions (ASTM D-5988).
S17
250
µm
250
µm
1 m
m1
mm
Bio360 Paper PLA
Uncleaned m
eshbags
after composting
Cleaned meshbags
after composting
Unused
mulches
Unused meshbags
Mes
hbag
sive
size
Fig. S2. Visual observation of BioAg 360, paper, and PLA mulches after composting for 18weeks in 250 µm and 1 mm nylon meshbags in pilot study. Note that the PLA mulch forthis particular experiment was white. Round and rectangular tokens served as identificationtags.
S18
0
25
50
75
100
Tem
pera
ture
(°C
)
0
25
50
75
100
Nov Dec Jan Feb Mar
Tem
pera
ture
(°C
)
Date
(b) 2016
(a) 2015
Atmosphere Compost
Fig. S3. Mean daily atmospheric and compost temperature at 60-cm depth during compostingin (a) 2015 and (b) 2016 at Puyallup, WA. Gray ribbon represents the standard deviationof the mean, with n = 8, except in 2015 where one sensor was removed after each meshbagsampling date. Brown dotted horizontal line at 60oC indicates upper limit for growth of mostthermophilic fungi (Trautmann and Krasny, 1998).
0
25
50
75
100
2016−01 2017−01 2018−01 2019−01
Wat
er a
mou
nt (m
m)
PrecipitationIrrigation
0
25
50
75
100
2016−01 2017−01 2018−01 2019−01
Wat
er a
mou
nt (m
m)
PrecipitationIrrigation
−10
0
10
20
30
40
2016−01 2017−01 2018−01 2019−01Date (yyyy−mm)
Tem
pera
ture
(°C
)
−10
0
10
20
30
40
2016−01 2017−01 2018−01 2019−01Date (yyyy−mm)
Tem
pera
ture
(°C
)
(a) Knoxville
c) Knoxville
(b) Mount Vernon
(d) Mount Vernon
Fig. S4. Daily precipitation (rainfall and irrigation) and daily-averaged air temperature atKnoxville (a,c) and Mount Vernon (b,d) during the 36-month field study.
S19
0.0
0.2
0.4
0.6
0.8
2016−01 2017−01 2018−01 2019−01
Wat
er c
onte
nt (m
3 m−3
)
0.0
0.2
0.4
0.6
0.8
2016−01 2017−01 2018−01 2019−01
Wat
er c
onte
nt (m
3 m−3
)
0
10
20
30
40
2016−01 2017−01 2018−01 2019−01Date (yyyy−mm)
Tem
pera
ture
(°C
)
0
10
20
30
40
2016−01 2017−01 2018−01 2019−01Date (yyyy−mm)
Tem
pera
ture
(°C
)
(a) Knoxville
(c) Knoxville
(b) Mount Vernon
(d) Mount Vernon
PaperBioAgri
NaturecycleOrganix
PLA/PHAPolyethylene
Fig. S5. Daily-averaged soil water content and soil temperature at 10-cm depth at Knoxville(a,c) and Mount Vernon (b,d) during the 36-month field study. Discontinued lines representsperiods when the sensors were temporarily removed for field operations (tillage). Horizontalbars in plot (b) indicate time periods when the soil was flooded.
S20
Fig. S6. Microbial taxa distribution (Class level) at Knoxville and Mount Vernon for thedifferent mulch treatments in Fall 2015. Relative abundances above a cut-off level of 2%are indicated. “Bacteria unclassified” denote taxa with relative abundance above the cut-offlevel of 2%, but that could not be classified.
S21
0 5000 10000 150000
20
40
60
80
100
Mul
ch d
egra
datio
n (%
)
0 10 20 30 400
20
40
60
80
100
Mul
ch d
egra
datio
n (%
)
0 5000 10000 150000
20
40
60
80
100
Mul
ch d
egra
datio
n (%
)
0 10 20 30 400
20
40
60
80
100
Mul
ch d
egra
datio
n (%
)
0 5000 10000 150000
20
40
60
80
100
Mul
ch d
egra
datio
n (%
)
0 10 20 30 400
20
40
60
80
100
Mul
ch d
egra
datio
n (%
)
0 5000 10000 150000
20
40
60
80
100
Thermal time (°C-day)
Mul
ch d
egra
datio
n (%
)
0 10 20 30 400
20
40
60
80
100
Time (months)
Mul
ch d
egra
datio
n (%
)
Knoxville Mount Vernon
Knoxville:
Mount Vernon:
⇥ x ⇥ x
⇥ x ⇥ x
Knoxville:
Mount Vernon:
⇥ x ⇥ x
⇥ x
Knoxville:
Mount Vernon:
⇥ x ⇥ x
⇥ x
Knoxville:
Mount Vernon:
⇥ x ⇥ x
⇥ x ⇥ x
Knoxville:
Mount Vernon:
⇥ x ⇥ x
⇥ x ⇥ x
Knoxville:
Mount Vernon:
⇥ x ⇥ x
⇥ x
Knoxville:
Mount Vernon:
⇥ x ⇥ x
⇥ x
Knoxville:
Mount Vernon:
⇥ x ⇥ x
⇥ x
BioAgri
Naturecycle
Organix
PLA/PHA
BioAgri
Organix
PLA/PHA
Naturecycle
Fig. S7. Measured and simulated degradation of biodegradable plastic mulches in soil as afunction of thermal (left column) and calendar time (right column). Lines represent fitted2nd-order polynomial model and symbols represent measured mulch degradation data. Errorbars are standard deviations of the mean (n = 4).
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