40 0 estimating mineralizable nitrogen from organic ...ย ยท 1. net nmin mg kg โ 1 l = ๐๐...
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1.
Net N
min
m
g kg
โ1so
il=
๐ผ๐๐
๐๐๐
๐๐๐ ๐
โ๐ผ๐
๐๐๐
๐๐
๐๐ ๐๐ก=
0
Estimating Mineralizable Nitrogen from Organic Materials
The u
se of n
ear in
frared
reflectance sp
ectrosco
py
allow
ed fo
r rapid
estimates
of th
e in
itial organ
ic N o
f the
material (r2
=0.9
7) an
d rate
con
stant o
f min
eralization
(r2
=0.9
2) w
hen
net N
m
ineralizatio
n w
as fit to first
ord
er kin
etics.
Introduction
Objectives
Conclusions
1. Determine mineralizable N and rate of mineralization from 42 different organic-certified materials (24 commercially available organic fertilizers, 8 composts, and 10 poultry litters).
ACKNOWLEDGEMENTS
PMN INCUBATION 1. Organic materials were characterized for initial water content (drying at 65oC for 48 h),
inorganic N (KCl), total C and N (dry combustion) and total elements (acid digestion). 2. Materials were applied at a rate to supply an estimated 75 mg N kg-1 of PAN to Cecil Sandy
Loam soil at 50% water holding capacity and incubated at 30oC for 99 days. PAN was estimated to be 10%, 40% and 50% of the total N for composts, poultry litters, and fertilizers respectively.
3. Subsamples were taken on d 1, 3, 7, 14, 35, 56, 78, 99 to determine inorganic N (1M KCl, 1:5) 4. Net N mineralization (Net Nmin) was determined for each d by subtracting the d.1 initial
inorganic N and fitting the data to a first order exponential model. N mineralization measured in the soil control was then subtracted from the model.
5. Net Nmin (g kg-1 material) was fit to first-order kinetics using SAS PROC NLIN:
Fig.4. Simplified model structure.
Kate Cassity-Duffey, M. Cabrera, D. Franklin, J. Gaskin, D.E. Kissel, and U. Saha Department of Crop & Soil Sciences - University of Georgia, Athens, GA;katecass@uga.edu
2. Evaluate NIRS for predicting initial characteristics and rate constants of mineralization of organic-certified materials.
Results: Net N Mineralized
Fig. 2. Stella ยฎ Model Software Input Parameters
Fig.5.Model in Stellaยฎ Modeling Software
Fig.6. Litter WC sub-model driven by air water potential.
Results: NIRS
Materials and Methods
NIRS ANALYSIS 1. Samples were oven dried (65oC), ground, and packed in quartz ring cups. 2. Samples were then scanned using FOSS NIRSystem 6500; 400-2500 nm at 2-nm intervals 3. WinSCAN v 1.50 software (FOSS North America, Eden Prairie, Minnesota) reported
reflectance (R) as log (1/R) and was used for statistical analysis. 4. Software used principle component regression for analysis of the spectra to develop
calibration and cross validation with initial characteristics, and the rate constant of mineralization.
In the southeastern United States, compost, poultry litter, and commercial organic fertilizers (made from plant and animal byproducts) are commonly used in vegetable production to supply plant-available nitrogen (PAN). However, due to the high variability in the nitrogen (N) content and composition of these materials, predicting the amount of PAN and the rate of N mineralization from these products is difficult. The ability to accurately predict N mineralization through the use of near infrared spectroscopy (NIRS) would allow for rapid estimations of PAN immediately prior to application, leading to increased precision of application of these products and reduced farmer costs.
Fig.
1. T
he
mat
eria
ls u
sed
fo
r P
MN
an
d N
IRS
anal
ysis
Net Nmin = ๐OrgN 1 โ eโkt where iOrgN is the initial organic N (g kg material), k is the rate constant of mineralization, and t is time (d)
PL2
PL3
PL5
PL8
PL9
PL10
PL11
PL12
PL13
PL14
CO
MP
1C
OM
P2
Blo
od M
Feath
er M
Sym
phony
Fis
h M
Cra
b S
hell
Harm
ony
Bio
Fis
h M
Must
ard
MP
G V
eg M
ixS
oyb
ean M
Veggie
Mix
Fis
h B
one M
Bone M
Cotton M
Vegan m
ixN
S 7
-12-0
NS
5-6
-6N
S 1
0-2
-8P
MP
M P
lus
MG
3-3
-3
Ne
t N
Min
era
lize
d %
O
rga
nic
Nitro
ge
n A
pp
lied
0
20
40
60
80
100
Ra
te c
on
sta
nt
(k x
10
2 d
-1)
-1
0
1
2
3
4
5
6
Net N Min
Rate Constant
PL2
PL3
PL5
PL8
PL9
PL10
PL11
PL12
PL13
PL14
CO
MP
1C
OM
P2
Blo
od M
Feath
er M
Sym
phony
Fis
h M
Cra
b S
hell
Harm
ony
Bio
Fis
h M
Must
ard
MP
G V
eg M
ixS
oyb
ean M
Veggie
Mix
Fis
h B
one M
Bone M
Cotton M
Vegan m
ixN
S 7
-12-0
NS
5-6
-6N
S 1
0-2
-8P
MP
M P
lus
MG
3-3
-3
Ne
t N
Min
era
lize
d %
O
rga
nic
Nitro
ge
n A
pp
lie
d
0
20
40
60
80
100
Ra
te c
on
sta
nt
(k x
10
2 d
-1)
-1
0
1
2
3
4
5
6
Net N Min
Rate Constant Fig. 2. Net N min from materials (PL=poultry litter, COMP=compost, M=meal) that mineralized and respective rate constants of mineralization determined through first-order kinetics.
Characteristic Mean SD RSQ SECV 1-VR
Water Content g g-1 0.33 0.35 0.86 0.17 0.76 Total C g 100 g-1 35.82 9.67 0.74 7.13 0.49 Total N g 100g-1 4.64 2.50 0.79 1.37 0.70 Organic N g kg-1 40.38 22.66 0.97 10.17 0.79 k x 102 d-1 0.51 0.48 0.92 0.42 0.30
The use of near NIRS allowed for rapid estimates of the initial organic N of the materials (r2=0.97) and the rate constant of mineralization (r2=0.92) when net N mineralization was fit to first-order kinetics for a range of organic materials.
Acknowledgement This work was supported by USDA-SARE Grant LS16-269
โข NIRS accurately estimated initial material water content, total N and C, organic N as well as the rate constant of mineralization allowing for prediction of mineralizable N using first-order kinetics.
โข Net N min calculated using NIRS predicted variables led to a r2 =0.92 with measured values
โข Blood and feather meal values were not estimated well using NIRS and were removed
PL2
PL3
PL5
PL8
PL9
PL10
PL11
PL12
PL13
PL14
CO
MP
1C
OM
P2
Blo
od M
Feath
er M
Sym
phony
Fis
h M
Cra
b S
hell
Harm
ony
Bio
Fis
h M
Must
ard
MP
G V
eg M
ixS
oyb
ean M
Veggie
Mix
Fis
h B
one M
Bone M
Cotton M
Vegan m
ixN
S 7
-12-0
NS
5-6
-6N
S 1
0-2
-8P
MP
M P
lus
MG
3-3
-3
Ne
t N
Min
era
lize
d %
O
rga
nic
Nitro
ge
n A
pp
lied
0
20
40
60
80
100
Rate
con
sta
nt
(k x
10
2 d
-1)
-1
0
1
2
3
4
5
6
Rate Constant
Poultry LItter
Compost
Fertilizer
โข Avg Net Nmin % of Total N applied: โข Composts: -3.5% โข Poultry litter: 17.0% โข Fertilizers: 30.8%
โข Rate constants (k) varied among materials.
โข Very high โkโ in blood and feather meal may be due to the high solubility of these products.
NIRS Predicted Net Nmin 100 d (g kg-1 material)
0 20 40 60 80
Mea
sure
d N
et N
min
100
d (
g k
g-1
mate
ria
l)
0
20
40
60
80
Poultry Litter
Compost
Fertilizer
Measured=0.81*Predicted+ 0
r2=0.92
Fig. 3. Predicted Nmin using organic N values and k constants determined through NIRS versus measured Nmin at 99 d
Table. 1. NIRS determined mean, standard deviation (SD), r-square (RSQ), standard error of cross validation (SECV), and 1- validation ratio (VR) of selected material characteristics.
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