Field Spectroscopy to Determine Nutritive Value Parameters of Individual Ryegrass Plants
Abstract
:1. Introduction
2. Materials and Methods
2.1. Sample Population and Study Area
2.2. Spectral Collection
2.3. Laboratory Analysis
2.4. Model Building
3. Results
3.1. PLS Models Descriptive Statistic
Statistic | ADF | ASH | CP | DM | IVVDMD | IVVOMD | NDF | WSC |
---|---|---|---|---|---|---|---|---|
Scatter correction | none | weighted MSC | derivative scale & offset | SNV | derivative scale & offset | remove, scale & offset | SNV | MSC |
Derivative, gap, smooth 1, smooth 2 | 1,8,1,1 | 1,8,1,1 | 1,8,1,1 | 1,8,1,1 | 1,8,1,1 | 1,8,1,1 | 1,8,1,1 | 1,8,1,1 |
Samples (N) | 103 | 102 | 105 | 103 | 104 | 104 | 104 | 105 |
Mean | 24.42 | 9.82 | 11.59 | 24.63 | 76.77 | 72.89 | 46.17 | 24.25 |
SD | 1.59 | 1.96 | 3.38 | 2.94 | 2.73 | 2.13 | 3.54 | 2.87 |
Est. Min | 19.65 | 3.94 | 1.44 | 15.81 | 68.58 | 66.48 | 35.56 | 15.63 |
Est. Max | 29.20 | 15.71 | 21.74 | 33.46 | 84.96 | 79.29 | 56.78 | 32.87 |
SEC | 0.73 | 0.46 | 0.66 | 1.18 | 0.78 | 0.74 | 1.47 | 0.44 |
R2 | 0.79 | 0.95 | 0.96 | 0.84 | 0.92 | 0.88 | 0.83 | 0.98 |
SEPC | 1.37 | 0.98 | 1.38 | 2.11 | 1.69 | 1.56 | 2.87 | 2.46 |
λN | 887 | 887 | 887 | 887 | 887 | 887 | 887 | 887 |
Statistic | ADF | ash | CP | DM | IVVDMD | IVVOMD | NDF | WSC |
---|---|---|---|---|---|---|---|---|
N | 50 | 50 | 50 | 50 | 50 | 50 | 50 | 50 |
Slope | 0.75 | 0.72 | 0.84 | 0.54 | 0.95 | 0.87 | 0.68 | 0.50 |
Y-intercept | 6.01 | 3.00 | 2.10 | 10.80 | 4.50 | 9.42 | 14.28 | 12.18 |
Bias | −0.07 | 0.31 | 0.26 | −0.44 | 0.33 | 0.07 | −0.66 | 0.18 |
SEC | 1.28 | 1.40 | 1.84 | 2.85 | 1.52 | 1.39 | 2.85 | 2.86 |
SEP | 1.27 | 1.51 | 1.91 | 2.95 | 1.53 | 1.38 | 3.03 | 3.03 |
SEPC | 1.28 | 1.49 | 1.92 | 2.95 | 1.51 | 1.39 | 2.99 | 3.06 |
R2 | 0.22 | 0.51 | 0.74 | 0.11 | 0.69 | 0.52 | 0.35 | 0.64 |
Predicted ave | 24.34 | 9.73 | 11.59 | 24.32 | 76.52 | 72.94 | 46.59 | 23.98 |
Actual ave | 24.27 | 10.03 | 11.86 | 23.88 | 76.85 | 73.01 | 45.94 | 24.16 |
Predicted SD | 0.88 | 1.95 | 3.69 | 1.81 | 2.39 | 1.63 | 3.04 | 2.30 |
Actual SD | 1.43 | 1.98 | 3.60 | 2.99 | 2.72 | 1.98 | 3.50 | 3.06 |
3.2. Robustness of the Predictive Model
3.3. Predictive Ability of Field Model
3.4. Prediction of NV Parameters in Plants Using the Field Model
4. Discussion
4.1. Predictive Model Performance
4.2. Interaction Between Parameters
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Date | Breeding Line | Spectra Collected | NV Lab Results |
---|---|---|---|
23/08/2018 | A | 316 | 0 |
24/08/2018 | D | 27 | 27 |
24/08/2018 | E | 18 | 18 |
24/08/2018 | F | 31 | 31 |
27/09/2018 | A | 288 | 0 |
12/10/2018 | B | 454 | 84 |
11/10/2018 | C | 474 | 0 |
30/11/2018 | B | 94 | 30 |
total | 1704 | 190 |
Statistic | ADF | ash | CP | DM | IVVDMD | IVVOMD | NDF | WSC |
---|---|---|---|---|---|---|---|---|
Samples (N) | 30 | 30 | 30 | 30 | 30 | 30 | 30 | 30 |
Slope | 0.61 | 0.47 | 0.68 | 0.69 | 0.70 | 0.64 | 1.08 | 0.78 |
Intercept | 9.33 | 3.69 | 3.02 | 13.85 | 21.58 | 23.81 | −2.30 | 5.23 |
Bias | 0.19 | −0.80 | −0.15 | 6.03 | −1.30 | −2.32 | 1.22 | −0.91 |
SEC | 1.59 | 0.79 | 1.11 | 1.60 | 2.25 | 2.14 | 3.41 | 2.48 |
SEP | 1.58 | 1.16 | 1.13 | 6.24 | 2.55 | 3.13 | 3.51 | 2.59 |
SEPC | 1.59 | 0.86 | 1.14 | 1.63 | 2.23 | 2.14 | 3.35 | 2.47 |
R2 | 0.10 | 0.14 | 0.29 | 0.26 | 0.07 | 0.09 | 0.15 | 0.24 |
Predicted Ave | 23.51 | 8.45 | 10.02 | 25.44 | 75.33 | 72.62 | 45.11 | 27.38 |
Actual Ave | 23.70 | 7.65 | 9.88 | 31.47 | 74.03 | 70.30 | 46.33 | 26.48 |
Predicted SD | 0.85 | 0.67 | 1.02 | 1.34 | 0.90 | 1.04 | 1.33 | 1.76 |
Actual SD | 1.64 | 0.84 | 1.30 | 1.83 | 2.30 | 2.21 | 3.64 | 2.79 |
ADF | Ash | CP | DM | IVVDMD | NDF | IVVOMD | WSC | |
---|---|---|---|---|---|---|---|---|
average | 24.24 | 9.86 | 11.24 | 24.71 | 76.37 | 45.37 | 72.94 | 23.81 |
minimum | 20.35 | 5.50 | 4.03 | 19.11 | 68.44 | 29.83 | 63.42 | 12.92 |
maximum | 29.45 | 15.71 | 23.42 | 33.37 | 90.65 | 55.61 | 82.83 | 31.79 |
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Smith, C.; Cogan, N.; Badenhorst, P.; Spangenberg, G.; Smith, K. Field Spectroscopy to Determine Nutritive Value Parameters of Individual Ryegrass Plants. Agronomy 2019, 9, 293. https://doi.org/10.3390/agronomy9060293
Smith C, Cogan N, Badenhorst P, Spangenberg G, Smith K. Field Spectroscopy to Determine Nutritive Value Parameters of Individual Ryegrass Plants. Agronomy. 2019; 9(6):293. https://doi.org/10.3390/agronomy9060293
Chicago/Turabian StyleSmith, Chaya, Noel Cogan, Pieter Badenhorst, German Spangenberg, and Kevin Smith. 2019. "Field Spectroscopy to Determine Nutritive Value Parameters of Individual Ryegrass Plants" Agronomy 9, no. 6: 293. https://doi.org/10.3390/agronomy9060293
APA StyleSmith, C., Cogan, N., Badenhorst, P., Spangenberg, G., & Smith, K. (2019). Field Spectroscopy to Determine Nutritive Value Parameters of Individual Ryegrass Plants. Agronomy, 9(6), 293. https://doi.org/10.3390/agronomy9060293