scholarly journals Prediction of crude protein and classification of the growth stage of wheat plant samples from NIR spectra

2004 ◽  
Vol 142 (5) ◽  
pp. 517-524 ◽  
Author(s):  
F. GATIUS ◽  
J. LLOVERAS ◽  
J. FERRAN ◽  
J. PUY
Keyword(s):  
Protein Content ◽  
Crude Protein ◽  
Growth Stage ◽  
Near Infrared ◽  
Wheat Plant ◽  
Global Model ◽  
Growth Stages ◽  
Crude Protein Content ◽  
Validation Set

Near-infrared spectroscopy (NIRS) was used to analyse the crude protein content of dried and milled samples of wheat and to discriminate samples according to their stage of growth. A calibration set of 72 samples from three growth stages of wheat (tillering, heading and harvest) and a validation set of 28 samples was collected for this purpose. Principal components analysis (PCA) of the calibration set discriminated groups of samples according to the growth stage of the wheat. Based on these differences, a classification procedure (SIMCA) showed a very accurate classification of the validation set samples: all of them were successfully classified in each group using this procedure when both the residual and the leverage were used in the classification criteria. Looking only at the residuals all the samples were also correctly classified except one of tillering stage that was assigned to both tillering and heading stages. Finally, the determination of the crude protein content of these samples was considered in two ways: building up a global model for all the growth stages, and building up local models for each stage, separately. The best prediction results for crude protein were obtained using a global model for samples in the two first growth stages (tillering and heading), and using a local model for the harvest stage samples.

Sampling requirements for predicting cattle diet quality using faecal near-infrared reflectance spectroscopy (F.NIRS) in heterogeneous tropical rangeland pastures

2010 ◽  
Vol 32 (4) ◽  
pp. 435 ◽  
Author(s):  
I. A. White ◽  
L. P. Hunt ◽  
D. P. Poppi ◽  
S. R. Petty
Keyword(s):  
Sample Size ◽  
Protein Content ◽  
Crude Protein ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Crude Protein Content ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Collection Method

Faecal near-infrared reflectance spectroscopy (F.NIRS) provides predictive information on cattle diets and nutritional levels, useful for livestock management or for research purposes. Potential errors exist throughout the entire F.NIRS process, including the collection method. The accepted collection method involves aggregating equal amounts of faecal material from 5 to 15 animals, mixing and removing a single sample for analysis. The adequacy of this method was tested by collecting and analysing up to 70 samples from individual cattle in different paddocks. Two methods were used to determine sample size based on observed variability in dietary attributes. Variability of dietary non-grass material and crude protein content increased with paddock size, so required sample size also increased. For dietary F.NIRS predictions to be used for research, our results suggest from 20 to 51 samples are needed in small to large paddocks to accurately predict the proportion of dietary non-grass material, from 12 to 50 samples for crude protein content and from 6 to 34 samples for dry matter digestibility. Composite samples from 15 cattle provided representative means in less than 50% of the situations investigated using biologically significant precision levels, but would be adequate for management of animal nutrition. Analysis of individual samples provided additional measures of range and variability which were also informative.

Effect of growth stage at cutting on yield and quality of lucerne cultivars from different dormancy groups in northern Victoria

1987 ◽  
Vol 27 (1) ◽  
pp. 55 ◽  
Author(s):  
RH Slarke ◽  
WK Mason
Keyword(s):  
Protein Content ◽  
Crude Protein ◽  
Dry Matter ◽  
Growth Stage ◽  
In Vitro Digestibility ◽  
Growth Stages ◽  
Flower Bud ◽  
Yield And Quality

At Kyabram, Victoria, the effects of growth stage at cutting on dry matter (DM) yield and quality of lucerne was determined during the warm season haymaking period for cultivars with contrasting winter dormancy characteristics. Growth stages at cutting were pre-flower bud, flower-bud, 10% bloom and full bloom. Cultivars were winter non-dormant CUF 101 and Pioneer Brand 572, semi-winter dormant Pioneer Brand 581 and winter dormant Pioneer Brand 545. Cultivar responses or interactions between cultivar and growth stage at cutting were not significant (P>0.05) for dry matter yield, crude protein or in vitro digestibility. Cutting of the pre-flower bud stage, compared with cutting at the 10% bloom stage, reduced DM yield by 18% (16.4 v. 13.5 t/ha), but increased crude protein content of the lucerne from 19.3 to 24%. The total protein yield per hectare was not affected by cutting stages from pre-flower bud stage to 10% bloom. Cutting lucerne at the flower bud stage rather than at 10% bloom gave increased protein content and digestibility with only a moderate yield decline. However, more frequent cutting was unsatisfactory as it decreased the density of the stand and increased the proportion of weeds and so could not be recommended.

Effects of growth-stage-based alfalfa harvest on weed encroachment and resultant quality

1999 ◽  
Vol 79 (2) ◽  
pp. 243-247 ◽  
Author(s):  
J. R. Moyer ◽  
J. Fraser ◽  
L. M. Rode ◽  
A. K. Topinka
Keyword(s):  
Protein Content ◽  
Key Words ◽  
Crude Protein ◽  
Growth Stage ◽  
Vegetative Stage ◽  
Crude Protein Content ◽  
Neutral Detergent Fibre ◽  
Yield And Quality ◽  
Acid Detergent Fibre ◽  
Cutting Management

Growth-stage-based alfalfa harvest treatments were imposed on a 2-yr-old Beaver alfalfa stand in 1992 to determine the effect of harvest treatments on yield and quality. By 1993, alfalfa cut at the vegetative stage or prebud stage contained 25% dandelions by weight. At these stages weeds lowered crude protein content in the total forage relative to pure alfalfa. Weed contents were similar and less than 1% by weight in forage cut at prebloom and later stages. Crude protein and fibre contents were similar in total forage and pure alfalfa at prebloom and later stages. Key words: Acid detergent fibre, crude protein, cutting management, dandelion, growth stage, neutral detergent fibre

Prediction of Dry Matter and Crude Protein Content in Fresh Grass Silage by Near Infrared Spectroscopy

2005 ◽  
Vol 1 (1) ◽  
pp. 57-75 ◽  
Author(s):  
Marina Vranić ◽  
Mladen Knežević ◽  
Zsolt Seregély ◽  
Krešimir Bošnjak ◽  
Josip Leto ◽  
...  
Keyword(s):  
Protein Content ◽  
Crude Protein ◽  
Dry Matter ◽  
Near Infrared ◽  
Chemical Constituents ◽  
Nir Spectroscopy ◽  
Meat Production ◽  
Crude Protein Content ◽  
Near Infrared Reflectance ◽  
Grass Silage

Intensive livestock feeding requires constant monitoring of diet composition to ensure a consistent level of milk or meat production. A rapid analysis of fresh grass silage samples for dry matter (DM) and crude protein (CP) content would provide basic, rapid information what would permit decision to be made regarding the need to supplement the diet. The aim of the present study was to determine dry matter (DM) and crude protein (CP) content in fresh grass silage samples by NIR spectroscopy. Crude protein content can be expressed as g per kg dry matter (g kg-1 DM) or as per cent of fresh weight (% FW). Near-infrared reflectance spectra were recorded for 103 fresh grass silage samples. Laboratory analysis of DM and CP were determined for these samples. MLR, PCR and PLS techniques were used for data modelling to determine the optimum models for predicting each of the chemical constituents. It was concluded that the PLS method was superior to the PCR and MLR methods for DM and CP prediction in fresh grass silage samples, while MLR showed a promising possibility to determine the CP content using only two spectral values measured at two “characteristic”wavelengths.

scholarly journals Growth Stages Classification of Potato Crop Based on Analysis of Spectral Response and Variables Optimization

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3995 ◽  
Author(s):  
Ning Liu ◽  
Ruomei Zhao ◽  
Lang Qiao ◽  
Yao Zhang ◽  
Minzan Li ◽  
...  
Keyword(s):  
Growth Stage ◽  
Spectral Response ◽  
Classification Model ◽  
Growth Stages ◽  
Potato Field ◽  
Spectral Bands ◽  
Svm Model ◽  
Selection Algorithms ◽  
Potato Crops

Potato is the world’s fourth-largest food crop, following rice, wheat, and maize. Unlike other crops, it is a typical root crop with a special growth cycle pattern and underground tubers, which makes it harder to track the progress of potatoes and to provide automated crop management. The classification of growth stages has great significance for right time management in the potato field. This paper aims to study how to classify the growth stage of potato crops accurately on the basis of spectroscopy technology. To develop a classification model that monitors the growth stage of potato crops, the field experiments were conducted at the tillering stage (S1), tuber formation stage (S2), tuber bulking stage (S3), and tuber maturation stage (S4), respectively. After spectral data pre-processing, the dynamic changes in chlorophyll content and spectral response during growth were analyzed. A classification model was then established using the support vector machine (SVM) algorithm based on spectral bands and the wavelet coefficients obtained from the continuous wavelet transform (CWT) of reflectance spectra. The spectral variables, which include sensitive spectral bands and feature wavelet coefficients, were optimized using three selection algorithms to improve the classification performance of the model. The selection algorithms include correlation analysis (CA), the successive projection algorithm (SPA), and the random frog (RF) algorithm. The model results were used to compare the performance of various methods. The CWT-SPA-SVM model exhibited excellent performance. The classification accuracies on the training set (Atrain) and the test set (Atest) were respectively 100% and 97.37%, demonstrating the good classification capability of the model. The difference between the Atrain and accuracy of cross-validation (Acv) was 1%, which showed that the model has good stability. Therefore, the CWT-SPA-SVM model can be used to classify the growth stages of potato crops accurately. This study provides an important support method for the classification of growth stages in the potato field.

Early productivity and crude protein content of establishing forage swards composed of combinations of native grass and legume species in mixed-grassland ecoregions

2013 ◽  
Vol 93 (3) ◽  
pp. 445-454 ◽  
Author(s):  
Jenalee M. Mischkolz ◽  
Michael P. Schellenberg ◽  
Eric G. Lamb
Keyword(s):  
Protein Content ◽  
Crude Protein ◽  
Plant Density ◽  
Warm Season ◽  
Forage Yield ◽  
Schizachyrium Scoparium ◽  
Legume Species ◽  
Crude Protein Content ◽  
Native Grass ◽  
Western Wheatgrass

Mischkolz, J. M., Schellenberg, M. P. and Lamb, E. G. 2013. Early productivity and crude protein content of establishing forage swards composed of combinations of native grass and legume species in mixed-grassland ecoregions. Can. J. Plant Sci. 93: 445–454. We evaluated the early establishment productivity of forage swards of native, perennial, cool and warm season grasses, and legumes as they have the potential to provide non-invasive, productive, and drought resistant rangelands. Seven species with agronomic potential and a broad native geographic distribution were selected for testing including: nodding brome [Bromus anomalus (Coult.)], blue bunch wheatgrass [Pseudoregneria spicata (Pursh)], western wheatgrass [Pascopyrum smithii (Rydb.)], side oats grama [Bouteloua curtipendula (Michx.)], little blue stem [Schizachyrium scoparium (Michx.)], purple prairie clover [Dalea purpurea (Vent.)], and white prairie clover [Dalea candida (Willd.)]. Forage swards, including all seven monocultures, 21 two-species mixtures and a mixture with all species, were planted in two sites, Saskatoon and Swift Current, Saskatchewan. Western wheatgrass (WWG) had the highest overall plant density and the strongest effect on the forage yield of the forage swards; however, productivity and crude protein content were not reduced when other species were also included in the forage sward. Dalea spp. did not establish as well as the other species, but had the highest crude protein concentrations. This work provides insight into forage sward development at the establishment stage; additional work is required to determine long-term species impacts for well established forage swards.

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