Assessment of seasonal dry‐matter yield and quality of grass swards with imaging spectroscopy

Schut, A.G.T.; Ketelaars, J.J.M.H.

doi:10.1111/j.1365-2494.2003.00391.x

Cited by 14 publications

(7 citation statements)

References 13 publications

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“…, 2002). In addition to species productivity, the measurements made of nutritive value have a determinant role in the efficiency of pasture utilization, supplying herbivores with the necessary nutrients for maintenance and production (Schut and Ketelaars, 2003). According to their yields of digestible DM and CP values (Figure 3), grasses may be classified into: high (e.g.…”

Section: Discussionmentioning

confidence: 99%

Seasonal productivity and nutritive value of temperate grasses found in semi‐natural pastures in Europe: responses to cutting frequency and N supply

Pontes

Carrère

Andueza

et al. 2007

Grass and Forage Science

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Monocultures of thirteen perennial C 3 grass species that co-occur in temperate semi-natural grassland communities in Europe were compared in a factorial field design of two levels of N supply and two levels of cutting frequency. Above-ground yield of dry matter (DM), crude protein (CP) concentration and pepsincellulase DM digestibility of herbage were measured in two successive years. Species was the largest source of variability in yield of DM and DM digestibility of herbage, while CP concentration of herbage responded more to management factors. The highest mean DM yields and values of DM digestibility of herbage were achieved in spring for Festuca arundinacea and in autumn for Phleum pratense. Poa trivialis and Festuca rubra had the lowest DM yield and DM digestibility values, respectively, regardless of seasons and treatments. For all species CP concentration in herbage increased in response to an increase in cutting frequency and N supply by an average of 46 and 34 g kg )1 DM respectively. Differences between years and seasons indicated the importance of plant phenology on nutritional variables and the influence of environmental factors on species performance. Species ranking was compared according to their annual digestible DM and CP yields. The results show that some grasses have a nutritive value which is comparable to that of forages selected for high yields.

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Section: Discussionmentioning

confidence: 99%

Seasonal productivity and nutritive value of temperate grasses found in semi‐natural pastures in Europe: responses to cutting frequency and N supply

Pontes

Carrère

Andueza

et al. 2007

Grass and Forage Science

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“…Ground cover and reflection intensity measured by the system is indicative of canopy geometry. Schut and Ketelaars (2003a,b,c) showed that, with this system, the mass and growth of herbage, light interception, sward heterogeneity, N deficiency and drought stress can be studied because of the non‐destructive nature of reflection measurements.…”

Section: Introductionmentioning

confidence: 99%

Potential of imaging spectroscopy as tool for pasture management

Schut¹,

Lokhorst²,

Hendriks³

et al. 2005

Grass and Forage Science

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The use of imaging spectroscopy to predict the herbage mass of dry matter (DM), DM content of herbage and crude fibre, ash, total sugars and mineral (N, P, K, S, Ca, Mg, Mn, Zn and Fe) concentrations was evaluated. The experimental system used measured reflectance between 404 and 1650 nm at high spatial (0AE28-1AE45 mm 2 ) and spectral resolution. Data from two experiments with Lolium perenne L. mini-swards were used where the degree of sward damage or N-fertilizer application varied. Regression models were calibrated and validated and the potential reduction in prediction error with multiple observations was estimated. The mean prediction errors for DM mass, DM content and N, total sugars, ash and crude fibre concentrations were 235-268 kg ha )1 , 9AE6-16AE8 g kg )1 , 2AE4-3AE4 g kg DM )1 , 16AE2-27AE7 g kg DM )1 , 5AE8-6AE5 g kg DM )1 and 8AE4-10AE4 g kg DM )1 respectively. The predictions for concentrations of P, K, S and Mg allowed identification of deficiency levels, in contrast to the concentrations of Na, Zn, Mn and Ca which could not be predicted with adequate precision. Prediction errors of DM mass may be maximally reduced to 95-142 kg ha )1 with 25 replicate measurements per field. It is concluded that imaging spectroscopy can provide an accurate means for assessment of DM mass of standing grass herbage. Predictions of macronutrient content and feeding value were satisfactory. The methodology requires further evaluation under field conditions.

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“…Frequent information on the status of legume–grass swards could help to direct fertilizer applications and to predict the N supply of the soil for the subsequent crop. An indirect assessment of the sward biomass (BM) by field spectroscopy (Biewer et al, 2008, 2009) or imaging spectroscopy (Schut and Ketelaars, 2003a, b; Schut et al, 2006) was shown to produce reliable data but could not determine the legume dry matter (DM) contribution. Based on grayscale images a digital image analysis (DIA) procedure was proposed by Himstedt et al (2009) that allows the estimation of legume DM contribution with an acceptable accuracy for swards with more than 300 kg DM ha −1 .…”

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The Benefit of Color Information in Digital Image Analysis for the Estimation of Legume Contribution in Legume–Grass Mixtures

2012

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Efficient detection of spafial legume dry matter (DM) contribution in legume-grass mixtures is of greaf importance for targeted management of legume-based swards. Legume coverage may be an appropriate indicator for fhe confribution of legumes, because it can be assessed by on-the-go systems wifh digital image analysis (DIA). To examine fhie perspectives of DIA a pot experimenf, under confroiled conditions, was conducted across a wide range of legume species (white clover [Trifolium repens L.], red clover [Trifolium pratense L.], and alfalfa [Medicago sativa L.]), legume proportion (0-800 g kg"^), and growth stage (start of tiliering to start of heading). In this study, an advanced procedure for the determination of legume DM contribution by DIA is suggested. The DIA procedure comprises the analysis of color images and applies an advanced function to predict legume DM contribution from legume coverage by considering total sward biomass. This resulted in an accurate prediction of legume contribution (grams per kilogram) with R^ of 0.90, 0.94, and 0.93 for red ciover, white ciover, and aifalfa, respectively. For validation, swards of a field experimenf were used. It showed that legume detection is possible, but for practical fieid application some further adjustments are necessary.

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Assessment of seasonal dry‐matter yield and quality of grass swards with imaging spectroscopy

Cited by 14 publications

References 13 publications

Seasonal productivity and nutritive value of temperate grasses found in semi‐natural pastures in Europe: responses to cutting frequency and N supply

Seasonal productivity and nutritive value of temperate grasses found in semi‐natural pastures in Europe: responses to cutting frequency and N supply

Potential of imaging spectroscopy as tool for pasture management

The Benefit of Color Information in Digital Image Analysis for the Estimation of Legume Contribution in Legume–Grass Mixtures

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