A Dataset on Corn Silage in China Used to Establish a Prediction Model Showing Variation in Nutrient Composition
It is important to assess the nutritional concentrations of forage before it can be used for tremendous improvements in the dairy industry. This improvement requires a rapid, accurate, and portable method for detecting nutrient values, instead of traditional laboratory analysis. Fourier-transform in...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Journal of Spectroscopy |
| Online Access: | http://dx.doi.org/10.1155/2023/7860822 |
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| author | Shu Zhang Jian Hao Donghai Wang Chenglong Luo Na Lu Xiaocen Guo Yanfang Liu Zixiao Zhang Shengli Li |
| author_facet | Shu Zhang Jian Hao Donghai Wang Chenglong Luo Na Lu Xiaocen Guo Yanfang Liu Zixiao Zhang Shengli Li |
| author_sort | Shu Zhang |
| collection | DOAJ |
| description | It is important to assess the nutritional concentrations of forage before it can be used for tremendous improvements in the dairy industry. This improvement requires a rapid, accurate, and portable method for detecting nutrient values, instead of traditional laboratory analysis. Fourier-transform infrared (ATR-FTIR) spectroscopy technology was applied, and partial least squares regression (PLSR) and backpropagation artificial neural network (BP-ANN) algorithms were used in the current study. The objective of this study was to estimate the discrepancy in nutritional content and rumen degradation in WPCS grown in various regions and to propose a novel analytical method for predicting the nutrient content of whole plant corn silage (WPCS). The Zhengdan 958 cultivar of WPCS was selected from eight different sites to compare the discrepancies in nutrients and rumen degradation. A total of 974 WPCS samples from 235 dairy farms scattered across five Chinese regions were collected, and nutritional indicators were modeled. As a result, substantial discrepancies in nutritional concentrations and rumen degradation of WPCS were found when they were cultivated in different growing regions. The WPCS in Wuxi showed 1.14% higher dry matter (DM) content than that in Jinan. Lanzhou had 11.57% and 8.25% lower neutral detergent fiber (NDF) and acid detergent fiber (ADF) concentrations than Jinan, respectively. The DM degradability of WPCS planted in Bayannur was considerably higher than that in Jinan (6 h degradability: Bayannur vs. Jinan = 49.85% vs. 33.96%), and the starch of WPCS from Bayannur (71.79%) was also the highest after 6 h in the rumen. The results indicated that the contents of NDF, ADF, and starch were estimated precisely based on ATR-FTIR combined with PLSR or the BP-ANN algorithm (R2 ≥ 0.91). This was followed by crude protein (CP), DM (0.82 ≤ R2 ≤ 0.90), ether extract (EE), and ash (0.66 ≤ R2 ≤ 0.81). The BP-ANN algorithm had a higher prediction performance than PLSR (R2PLSR ≤ R2BP-ANN; RMSEPLSR ≥ RMSEBP-ANN). The same WPCS cultivar grown in different regions had various nutrient concentrations and rumen degradation. ATR-FTIR technology combined with the BP-ANN algorithm could effectively evaluate the CP, NDF, ADF, and starch contents of WPCS. |
| format | Article |
| id | doaj-art-32c0d7b52a4d48dd8b3323f6ff5f21ba |
| institution | DOAJ |
| issn | 2314-4939 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Spectroscopy |
| spelling | doaj-art-32c0d7b52a4d48dd8b3323f6ff5f21ba2025-08-20T03:18:44ZengWileyJournal of Spectroscopy2314-49392023-01-01202310.1155/2023/7860822A Dataset on Corn Silage in China Used to Establish a Prediction Model Showing Variation in Nutrient CompositionShu Zhang0Jian Hao1Donghai Wang2Chenglong Luo3Na Lu4Xiaocen Guo5Yanfang Liu6Zixiao Zhang7Shengli Li8College of Animal ScienceInner Mongolia Yili Industrial Group Co.,Ltd.College of Animal ScienceState Key Laboratory of Animal NutritionBeijing Jingwa Agricultural Science & Technology Innovation CenterBeijing Jingwa Agricultural Science & Technology Innovation CenterBeijing Sino Agricultural Aiko Testing Technology Co.,Ltd.Beijing Jingwa Agricultural Science & Technology Innovation CenterState Key Laboratory of Animal NutritionIt is important to assess the nutritional concentrations of forage before it can be used for tremendous improvements in the dairy industry. This improvement requires a rapid, accurate, and portable method for detecting nutrient values, instead of traditional laboratory analysis. Fourier-transform infrared (ATR-FTIR) spectroscopy technology was applied, and partial least squares regression (PLSR) and backpropagation artificial neural network (BP-ANN) algorithms were used in the current study. The objective of this study was to estimate the discrepancy in nutritional content and rumen degradation in WPCS grown in various regions and to propose a novel analytical method for predicting the nutrient content of whole plant corn silage (WPCS). The Zhengdan 958 cultivar of WPCS was selected from eight different sites to compare the discrepancies in nutrients and rumen degradation. A total of 974 WPCS samples from 235 dairy farms scattered across five Chinese regions were collected, and nutritional indicators were modeled. As a result, substantial discrepancies in nutritional concentrations and rumen degradation of WPCS were found when they were cultivated in different growing regions. The WPCS in Wuxi showed 1.14% higher dry matter (DM) content than that in Jinan. Lanzhou had 11.57% and 8.25% lower neutral detergent fiber (NDF) and acid detergent fiber (ADF) concentrations than Jinan, respectively. The DM degradability of WPCS planted in Bayannur was considerably higher than that in Jinan (6 h degradability: Bayannur vs. Jinan = 49.85% vs. 33.96%), and the starch of WPCS from Bayannur (71.79%) was also the highest after 6 h in the rumen. The results indicated that the contents of NDF, ADF, and starch were estimated precisely based on ATR-FTIR combined with PLSR or the BP-ANN algorithm (R2 ≥ 0.91). This was followed by crude protein (CP), DM (0.82 ≤ R2 ≤ 0.90), ether extract (EE), and ash (0.66 ≤ R2 ≤ 0.81). The BP-ANN algorithm had a higher prediction performance than PLSR (R2PLSR ≤ R2BP-ANN; RMSEPLSR ≥ RMSEBP-ANN). The same WPCS cultivar grown in different regions had various nutrient concentrations and rumen degradation. ATR-FTIR technology combined with the BP-ANN algorithm could effectively evaluate the CP, NDF, ADF, and starch contents of WPCS.http://dx.doi.org/10.1155/2023/7860822 |
| spellingShingle | Shu Zhang Jian Hao Donghai Wang Chenglong Luo Na Lu Xiaocen Guo Yanfang Liu Zixiao Zhang Shengli Li A Dataset on Corn Silage in China Used to Establish a Prediction Model Showing Variation in Nutrient Composition Journal of Spectroscopy |
| title | A Dataset on Corn Silage in China Used to Establish a Prediction Model Showing Variation in Nutrient Composition |
| title_full | A Dataset on Corn Silage in China Used to Establish a Prediction Model Showing Variation in Nutrient Composition |
| title_fullStr | A Dataset on Corn Silage in China Used to Establish a Prediction Model Showing Variation in Nutrient Composition |
| title_full_unstemmed | A Dataset on Corn Silage in China Used to Establish a Prediction Model Showing Variation in Nutrient Composition |
| title_short | A Dataset on Corn Silage in China Used to Establish a Prediction Model Showing Variation in Nutrient Composition |
| title_sort | dataset on corn silage in china used to establish a prediction model showing variation in nutrient composition |
| url | http://dx.doi.org/10.1155/2023/7860822 |
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