Open-access Evaluating the limitations of clipping at stubble height for nutritive forage assessment in mixed pastures

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ABSTRACT

Accurately assessing the nutritive value of diets in mixed pastures is crucial for selecting optimal supplementation and management strategies, which can enhance animal performance and productivity. This 2-year study evaluated whether clipping forage at stubble height accurately represents diets consisting of marandu palisade grass and forage peanut compared to samples collected by hand-plucking. Forage nutritive value was assessed at three grazing intensities: severe (10 cm stubble height), moderate (15 cm stubble height), and light (20 cm stubble height). Two hypotheses were tested to compare the nutritive value of hand-plucked versus clipped samples: H0: β0 = 0 and H0: β1 = 1. Pearson's correlation analysis was also conducted. The hypothesis H0: β0 = 0 was accepted for crude protein (CP), and protein-free neutral detergent fiber (NDF) concentrations in both marandu palisade grass and forage peanut. However, the hypothesis H0: β1 = 1 was rejected for CP and NDF concentrations in marandu palisade grass, and CP in forage peanut (p < 0.01), though not for NDF concentration in forage peanut (p = 0.240). Pearson's correlation coefficients were not significant for any chemical compound evaluated, regardless of species (p > 0.05). Therefore, clipping mixed pasture at stubble height is not an effective method for evaluating the nutritive value of the consumed diet as it fails to account for grazing selection, and spatial and morphological variability.

Keywords:
Arachis pintoi; Urochloa brizantha; forage nutritive value; forage intake; hand-plucking

Introduction

Ruminants grazing in mixed pastures make decisions on where, when, and how much to graze, thereby influencing their nutritional status, canopy composition, and diet nutritive value through selective defoliation (Soder et al., 2009). The nutritive value of a diet is determined by its chemical composition, digestibility, and the nature of digested products (Allen et al., 2011). Typically, tropical grasses have lower nutritive value than legumes (Oelberg, 1956; Gomes et al., 2018; Lee, 2018; Homem et al., 2021). Combining grasses with legumes can cost-effectively enhance diet quality. However, evaluating this mixture accurately is challenging, as noted by Engels and Malan (1973), due to grazing selection behavior.

Various sampling methodologies have been tested to estimate the nutritive value of tropical monocultures (Euclides et al., 1992) and temperate mixed pastures (Engels and Malan, 1973). Hand-plucking is the standard method in grazing trials, known for being fast, cost-effective, and involving observation of animal grazing behavior before sample collection (De Vries, 1995). In mixed pastures, accurately identifying and quantifying consumed forage species is essential (Papachriston et al., 2005; Jaramillo et al., 2021; Cruz et al., 2024). While hand-plucking is effective in tropical monoculture pastures, it requires calibration between the collector and grazing animal, thereby making it labor-intensive in rotational stocking systems, once the sample has an obligatory composite of occupation days. It also lacks standardization for mixed pastures (Berça et al., 2019; Gomes et al., 2018; Homem et al., 2021). An alternative method is clipping at stubble height, which reduces labor and eliminates the need for trained collectors or behavioral observations (Euclides et al., 1992). This method assumes animals consume all forage above the stubble, but its accuracy in mixed tropical pastures, such as marandu palisade grass and forage peanut, is uncertain. Grazing intensity further influences herbage selection and diet composition (Culley et al., 1933; Hughes et al., 2010), making it important to compare stubble height clipping with hand-plucking to evaluate its reliability in estimating the nutritive value of mixed pastures.

This study aimed to determine whether clipping at stubble height yields similar results to hand-plucking when estimating the nutritive value of diets in mixed pastures, with the hypothesis that clipping at lower stubble heights minimizes animal selectivity.

Materials and Methods

Experimental site

All experimental procedures were approved by the Ethics and Animal Welfare Committee of the Universidade Federal de Lavras (protocol number 026/2019). The study was conducted at the Experimental Farm of the Universidade Federal de Lavras in Brazil (21°14’ S, 45°00’ W, altitude 918 m), which features a subtropical humid mesothermal climate with dry winters (Köppen-Geiger climate classification: Cwa; Sá Júnior et al., 2012). Meteorological data were sourced from a weather station located 1,000 m from the experimental area (Figure 1).

Figure 1

Monthly temperatures (°C) and rainfall (mm) in Lavras, Minas Gerais state, Brazil, during the experimental period (seasons of the year).


The pastures were established in Dec 2006 with a combined seeding of marandu palisade grass [Urochloa brizantha (Hochst. ex A. Rich.) R.D. Webster cv. marandu (syn. Brachiaria brizantha)] and forage peanut (Arachis pintoi Krapov. & W.C. Greg. cv. BRS Mandobi). For a matter of simplification, marandu palisade grass will be referred to as "palisade grass" from this point forward. The seeding rates were 7.6 kg ha–1 of pure live seeds for palisade grass and 7.2 kg ha–1 for forage peanut.

Soil characteristics (0-20 cm depth) included a pH(H–O) of 5.6, exchangeable Al, Ca, and Mg at 0.09, 1.9, and 0.5 cmolc dm–3, respectively; available P (Mehlich-I method) at 2.8 mg dm–3; exchangeable K at 69.4 mg dm–3; and organic matter at 45.8 g kg–1. Thirty days prior to the experiment, agricultural gypsum (1.39 t ha–1) and dolomitic limestone (278 kg ha–1) were applied. Fertilizers in the form of single superphosphate (17.6 kg ha–1 of P) and potassium chloride (44 kg ha–1 of K) were applied at the beginning of each spring. The study was conducted over two years, from Sept 2019 to May 2021, with the experimental phases divided into spring (Sept to Jan) and summer (Jan to Apr) as shown in Figure 1. Due to dry winter conditions, no assessments were made from May to Sept in either year.

Treatments and experimental management

The grazing management strategies included three grazing intensity levels: severe (10 cm), moderate (15 cm), and light (20 cm of stubble height). The treatments were assigned in a completely randomized design with four replicates, making a total of 12 experimental units. The resting period for each treatment was determined accordingly. Paddocks were grazed when the canopy reached a height of 24 to 27 cm (Gomes et al., 2018). At least two Tabapua heifers (265 ± 20 kg) were used to graze the paddocks to the target stubble height for each treatment (Figure 2). Additional put-and-take heifers were introduced as needed to achieve the target canopy height within three days.

Figure 2

The experimental unit was divided into three paddocks (1, 2, and 3) with a 3-day occupation period in each one, making a total of nine days. A reserve mixed pasture of palisade grass and forage peanut was used to keep animals during rest periods. All the evaluations were made as explained in the figure.


Experimental evaluations

Hand-plucking samples were collected for forage nutritive value analysis (De Vries, 1995). In the lab, samples from the mixed pasture were separated into grass and legume before being dried. For each species, samples from the first and last day of occupation were analyzed separately. Clipped samples at stubble height for palisade grass and forage peanut were collected on the first day of occupation only, following the defoliation management plan. Clipping was carried out at heights of 10, 15, and 20 cm, depending on the treatment. Grass and legume samples were separated and analyzed individually. Both hand-plucking and clipping forage samples were collected during each grazing cycle throughout the experimental period.

All the samples from clipping and hand-plucking were oven-dried at 55 °C for 72 h, and ground in a Willey-type knife mill (Solab to pass through a 1-mm screen). Dry matter (DM) of each sample was obtained by oven drying at 105 °C for 16 h (method 934.01: AOAC, 2000). CP concentration was calculated based on the N concentration (CP = total N × 6.25), which was determined by following the Kjeldahl procedure (method 920.87: AOAC, 2000). NDF was determined by the autoclave method at 105 °C for 60 min (Pell and Schofield, 1993). Ash and protein-free NDF were obtained by using sodium sulphite and incineration (Robertson and Van Soest, 1981).

To estimate the nutritive value of the diet, external and internal markers were used. Each animal received 10 g of titanium dioxide daily for nine consecutive days, with six days for adaptation and three for sample collection. Spot fecal samples were collected once a day, with the collection time varying each day (6h00, 12h00, and 18h00), and a composite sample was created for each animal over the 3-day occupation period (Cruz et al., 2024). During the sampling days, heifers were brought from the paddocks to the chute, where fecal samples were collected directly from the rectum. The samples were oven-dried at 55 °C for 72 h to determine DM concentration, air-equilibrated, and ground using a Cyclotec mill (Tecator) to pass through both 1-mm and 2-mm screens. Fecal samples were analyzed for titanium dioxide concentration following the method described by Myers et al. (2004).

Fecal and forage samples from hand-plucking ground to pass through a 2-mm screen were incubated in the rumen for 288 h to determine the indigestible neutral detergent fiber (iNDF; Huhtanen et al., 1994). Two cannulated cows grazing palisade grass and forage peanut mixed pasture were used in the iNDF estimate. The proportion of palisade grass and forage peanut in the iNDF residual fecal samples was quantified using δ13C isotopes by the Eq. (1):

(1) % legume = 100 × ( δ 13 C G − δ 13 C S ) ÷ ( δ 13 C G − δ 13 C L )

where %legume is the proportion of carbon from a legume in the iNDF residual fecal samples and δ13CG, δ13CL, and δ13CS, the values of δ13C abundance of the iNDF residual in hand-plucking samples from grass (−12.97 ‰), legume (−28.34 ‰), and the iNDF residual in fecal samples, respectively. For the analysis of δ13C, samples were ground to a fine powder in a roller mill. Subsamples containing between 300- to 500-μg C were analyzed for total C and 13C abundance using an automated continuous-flow isotope-ratio mass spectrometer consisting of a Finnigan DeltaV mass spectrometer coupled to the output of a Carlo Erba EA 1108 total C and N analyzer (Finnigan MAT). The concentration of CP and NDF in the diet was calculated by multiplying the grass and legume proportions (estimated by 13C isotopes or clipping at stubble height) by the CP and NDF content of each species.

Statistical analysis

The nutritive value of palisade grass and forage peanut by hand-plucking was calculated as the average between the first and last day of occupation. The models consisted of fitting a first-order equation of the type Y=β0+β1X [Equation (2)] with the following hypotheses: H0:β0=0 [Equation (3)] and H0:β0=1 [Equation (4)] where Y represented the nutritive value of samples collected by hand-plucking and X, samples collected by clipping at stubble height. Data were analyzed using the REG procedure by SAS (SAS Institute Inc.). Pearson's correlation analysis was carried out between methodologies for the same variable using PROC CORR, as well as by SAS. Differences were stated at p ≤ 0.05.

Results

The hypothesis Eq. (3) was accepted for CP and NDF concentrations in palisade grass and forage peanut when comparing hand-plucking and clipping at stubble height methods (p > 0.05). However, this hypothesis was rejected for diet CP concentration (p < 0.01). The hypothesis Eq. (4) was rejected for CP and NDF concentrations in palisade grass and CP in forage peanut (p < 0.01). It was not rejected for NDF concentration in forage peanut (p = 0.24). Additionally, the hypothesis was rejected for both diet NDF and CP concentrations (p < 0.01). Rejecting Eq. (4) indicates a bias in the equation, leading to either over- or underestimation of the nutritive value (Table 1).

Table 1
Comparison between the nutritive value of hand-plucking samples and clipping at stubble height for marandu palisade grass and forage peanut.

The hypothesis Eq. (3) was not rejected for CP concentration under intense and moderate defoliation (p > 0.05), but Eq. (4) was rejected (p ≤ 0.02) for marandu palisade grass. For light defoliation, both hypotheses were rejected (p ≤ 0.01). The hypothesis Eq. (3) was not rejected for NDF concentration at all defoliation intensity levels (p > 0.05). However, Eq. (4) could not be rejected under intense defoliation only (p = 0.42), indicating that methodologies did not differ in NDF concentration under intense defoliation only (Figure 3A-B).

Figure 3

A) and B) Comparison between the nutritive value of marandu palisade grass and C) and D) forage peanut for hand plucking and clipping at stubble height samples collected under three defoliation management approaches (intense, moderate, and light). CP = crude protein; NDF = neutral detergent fiber.


The hypothesis Eq. (3) could not be rejected for CP and NDF at any defoliation intensity level (p > 0.05) for forage peanut. For CP concentration, the hypothesis Eq. (4) was rejected across all defoliation intensity levels (p ≤ 0.02), but not for NDF concentration (p > 0.05). Thus, methodologies were similar for NDF concentration only at all intensity levels (Figure 3C-D).

As regards the diet's nutritive value, neither Eq. (3) nor Eq. (4) could be rejected for diet CP under intense defoliation (p > 0.05; Figure 4A). The hypothesis Eq. (3) could not be rejected for diet NDF under intense defoliation (p = 0.42; Figure 4B) but was rejected for moderate and light defoliation intensity levels (p < 0.05). The hypothesis Eq. (4) could not be rejected for diet NDF at all defoliation intensity levels (p > 0.05). Thus, diet NDF and CP concentrations were similar under intense defoliation management only.

Figure 4

Comparison between the (A) CP and (B) NDF of the diet for hand plucking and clipping at stubble height samples collected under three defoliation management (intense, moderate, and light). CP = crude protein; NDF = neutral detergent fiber.


There was no significant correlation between the nutritive value of palisade grass and forage peanut collected by hand-plucking and clipping at stubble height (Table 2; p > 0.05). Diet CP collected by clipping showed a correlation with hand-plucking (p < 0.01), whereas diet NDF did not (p = 0.46).

Table 2
Pearson's correlation coefficients for the nutritive value of marandu palisade grass and forage peanut were evaluated by hand plucking and clipping at stubble height.

Discussion

In lightly grazed pastures, utilization tends to be uneven, with some areas being grazed down to just a few centimeters above the soil while others remain largely untouched. Additionally, in pastures with multiple species, some may be grazed close to the soil surface, while others are only consumed from the top layer (Culley et al., 1933). Therefore, assessing the nutritive value must account for these variations and preferences to reflect the animal's actual diet accurately.

Accurate measurements of the nutritive value of a diet are crucial for estimating daily nutrient intake, digestibility, and animal performance, as well as for making proper adjustments to meet cattle requirements, including adjustments to stocking rate (Smith et al., 2020). Numerous studies have been conducted to compare hand-plucking samples with the actual diet consumed by animals (De Vries, 1995; Edlefsen et al., 1960; Kiesling et al., 1969). Most of these studies compare hand-plucked samples with ruminal or esophageal extrusa, as extrusa reflects the animal's selection ability. Comparing the nutritive value of esophageal extrusa from sheep grazing mixed pastures and pure stands, differences were found in five out of eight chemical compounds evaluated, mainly due to saliva contamination (Edlefsen et al., 1960). Despite these differences, the authors concluded that hand-plucking could still be considered an effective method for estimating the diet consumed. The effectiveness of hand-plucking across different vegetation types was tested, and the authors found no significant bias, as the regression intercepts were no different from zero and the regression coefficients were not significantly different from one (De Vries, 1995). The primary challenge of this method lies in calibrating between animals and operators in a manner that does not disturb natural grazing behavior.

Hand plucking has been widely used as a standard method for evaluating forage nutritive value, as the use of fistulated animals is costly, labor-intensive, time-consuming, and raises concerns about animal welfare. Grazing preferences fluctuate throughout the day in response to internal and external factors, and visiting animals, such as rumen-cannulated ones, may not select the same forage as resident animals. Additionally, hand-plucked samples are free from salivary contamination (Coates et al., 1987; De Vries, 1995). For these reasons, hand plucking is considered the method that most accurately represents the nutritive value of the diet consumed.

The primary difference between clipping and hand plucking lies in how the forage is harvested. Clipping involves uniformly cutting the forage at a specific height, whereas hand plucking mimics how animals graze, pulling and breaking the shoots at varying heights depending on the forage species and the type of livestock (Culley et al., 1933).

We considered the nutritive value from hand-plucking samples as the standard. We tested the hypothesis Eq. (3), aiming to demonstrate that when the nutritive value variables were zero for hand-plucking, they would also be zero for clipping at stubble height (Table 1). The hypothesis was not rejected for CP and NDF measured in palisade grass and forage peanut. To assess bias between the methods, we tested Eq. (4). Excluding the NDF concentration of forage peanut, we were able to reject Eq. (4) for all variables, indicating that biases and errors in the clipping method led to differences between the datasets. These findings are supported by Table 2, which shows no significant correlation between the methodologies for any of the variables evaluated (p > 0.05). However, the methods were found to be similar for NDF concentration in palisade grass under intense defoliation and in forage peanut, regardless the level of defoliation (Figures 3B and 4B).

As regards the nutritive value of the diet, our central hypothesis, Eq. (3), was not rejected for CP and NDF solely under intense defoliation conditions. When the opportunity for selection decreased, clipping at stubble height emerged as a useful method, given that it tends to produce more homogeneous grazing. However, the methodology for determining nutritive value needs to be effective across all botanical and chemical components and at levels of defoliation intensity.

Differences between clipping and extrusa methodologies throughout the year in shortgrass areas revealed that clipping often underestimates the diet's nutritive value as it fails to consider grazing habits and preferences (Jefferies and Rice, 1969). This was also observed in our study, where clipping at stubble height led to underestimated values for NDF and CP compared to hand plucking (Table 1). Similarly, clipping generally resulted in lower CP and higher NDF concentrations than hand plucking and extrusa, regardless of season (Sankhyan et al. 1999).

The chemical composition of mixed pastures of oat (Avena strigosa Schreb.) and ryegrass (Lolium multiflorum Lam.) was compared using clipping at ground level, hand plucking, and rumen evacuation (Prohmann et al., 2012). The authors found no significant differences in nutritive value between clipping and hand plucking. However, their study involved temperate forages harvested every 28 days, and the statistical methods used might have obscured any potential differences.

Two clipping heights (7.5 cm and 15 cm) with hand plucking for assessing the nutritive value were assessed in several annual warm-season forage legumes (Muir et al., 2008). Crude protein concentration was lower for samples collected at both clipping heights compared to hand plucking. Higher nutritive value for rhizoma peanut (Arachis glabrata Benth.) when collected by hand plucking rather than clipping at heights of 5 and 10 cm (Butler et al., 2007). Since leaves generally have higher nutritive value than stems and dead material, hand-plucked samples, which primarily consist of leaves, are expected to be more nutritious than clipped samples that include more stems and dead material (Goes et al., 2003; Muir et al., 2008). Additionally, clipping does not account for animal preferences, particularly in mixed-species pastures (Culley et al., 1933).

Overall, the nutritive value of a pasture is influenced by its botanical and chemical composition, digestibility, canopy structure, and intake, all of which are affected by animal grazing behavior and selectivity. While clipping at stubble height can be a viable method for assessing the nutritive value of diets in intensely defoliated pastures (with a stubble height of 10 cm), hand plucking remains the best approach for accurately estimating the nutritive value of mixed pastures due to its incorporation of animal grazing preferences. Clipping should be reserved for estimating nutritive value in the absence of animals, such as in hay fields.

Declaration of use of AI Technologies

The authors declare that no AI technologies were used in this manuscript.

Acknowledgments

This work was funded by the Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG), the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Instituto Nacional de Ciência e Tecnologia de Ciência Animal (INCT-CA), and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). The authors thank the members of NEFOR (Brazilian Forage Team) for their contributions during the field trial. The seventh author gratefully acknowledges the research fellowships from CNPq and the Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ).

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  • Allen VG, Batello C, Berretta EJ, Hodgson J, Kothmann M, Li X, et al. 2011. An international terminology for grazing lands and grazing animals. Grass and Forage Science 66: 2-28. https://doi.org/10.1111/j.1365-2494.2010.00780.x
    » https://doi.org/10.1111/j.1365-2494.2010.00780.x
  • Association of Official Analytical Chemists [AOAC]. 2000. Official Methods of Analysis of AOAC. 17ed. AOAC, Gaithersburg, MD, USA.
  • Berça AS, Cardoso AS, Longhini VZ, Tedeschi LO, Boddey RM, Berndt A, et al. 2019. Methane production and nitrogen balance of dairy heifers grazing palisade grass cv. Marandu alone or with forage peanut. Journal of Animal Science 97: 4625-4634. https://doi.org/10.1093/jas/skz310
    » https://doi.org/10.1093/jas/skz310
  • Butler TJ, Muir JP, Islam MA, Bow JR. 2007. Rhizoma peanut yield and nutritive value are influenced by harvest technique and timing. Agronomy Journal 99: 1559-1563. https://doi.org/10.2134/agronj2007.0035
    » https://doi.org/10.2134/agronj2007.0035
  • Coates DB, Schachenmann P, Jones RJ. 1987. Reliability of extrusa samples collected from steers fistulated at the oesophagus to estimate the diet of resident animals in grazing experiments. Australian Journal of Experimental Agriculture 27: 739-745. https://doi.org/10.1071/EA9870739
    » https://doi.org/10.1071/EA9870739
  • Cruz PJR, Silva DV, Lima IBG, Alves GC, Homem BGC, Alves BJR, et al. 2024. Marandu palisade grass-forage peanut mixed pastures: forage intake, animal behaviour and canopy structure as affected by grazing intensities. Grass and Forage Science 79: 666-667. https://doi.org/10.1111/gfs.12688
    » https://doi.org/10.1111/gfs.12688
  • Culley MJ, Campbell RS, Canfield RH. 1933. Values and limitations of clipped quadrats. Ecology 14: 35-39. https://doi.org/10.2307/1932574
    » https://doi.org/10.2307/1932574
  • De Vries MFW. 1995. Estimating forage intake and quality in grazing cattle: a reconsideration of the hand-plucking method. Rangeland Ecology & Management 48: 370-375.
  • Edlefsen JL, Cook CW, Blake JT. 1960. Nutrient content of the diet as determined by hand plucked and esophageal fistula samples. Journal of Animal Science 19: 560–567. https://doi.org/10.2527/jas1960.192560x
    » https://doi.org/10.2527/jas1960.192560x
  • Engels EAN, Malan A. 1973. Sampling of pastures in nutritive evaluation studies. Agroanimalia 5: 89-94.
  • Euclides VPB, Macedo MCM, Oliveira MP. 1992. Avaliação de diferentes métodos de amostragem sob pastejo. Revista Brasileira de Zootecnia 21:691-702 (in Portuguese).
  • Goes RHTB, Mancio AB, Lana RP, Valadares Filho SC, Cecon PR, Queiroz AC, et al. 2003. Quality evaluation of the tanner grass (Brachiaria arrecta) pasture, by three different collection methods. Revista Brasileira de Zootecnia 32: 64-69 (in Portuguese, with abstract in English). https://doi.org/10.1590/S1516-35982003000100008
    » https://doi.org/10.1590/S1516-35982003000100008
  • Gomes FK, Oliveira MDBL, Homem BGC, Boddey RM, Bernardes TF, Gionbelli MP, et al. 2018. Effects of grazing management in brachiaria grass-forage peanut pastures on canopy structure and forage intake. Journal of Animal Science 96: 3837-3849. https://doi.org/10.1093/jas/sky236
    » https://doi.org/10.1093/jas/sky236
  • Homem BGC, Lima IBG, Spasiani PP, Borges LPC, Boddey RM, Dubeux Junior JCB, et al. 2021. Palisadegrass pastures with or without nitrogen or mixed with forage peanut grazed to a similar target canopy height. 2. Effects on animal performance, forage intake and digestion, and nitrogen metabolism. Grass and Forage Science 76: 413-426. https://doi.org/10.1111/gfs.12533
    » https://doi.org/10.1111/gfs.12533
  • Hughes AL, Hersom MJ, Vendramini JMB, Thrift TA, Yelich JV. 2010. Comparison of forage sampling method to determine nutritive value of bahiagrass pastures. The Professional Animal Scientist 26: 504-510. https://doi.org/10.15232/S1080-7446(15)30638-0
    » https://doi.org/10.15232/S1080-7446(15)30638-0
  • Huhtanen P, Kaustell K, Jaakkola S. 1994. The use of internal markers to predict total digestibility and duodenal flow of nutrients in cattle given six different diets. Animal Feed Science and Technology 48: 211-227. https://doi.org/10.1016/0377-8401(94)90173-2
    » https://doi.org/10.1016/0377-8401(94)90173-2
  • Jaramillo DM, Dubeux JCB, Sollenberger LE, Vendramini JMB, Mackowiak C, DiLorenzo N, et al. 2021. Water footprint, herbage, and livestock responses for nitrogen-fertilized grass and grass-legume grazing systems. Crop Science 61: 3844-3858. https://doi.org/10.1002/csc2.20568
    » https://doi.org/10.1002/csc2.20568
  • Jefferies NW, Rice RW. 1969. Nutritive value of clipped and grazed range forage samples. Journal of Range Management 22: 192-195. https://doi.org/10.2307/3896340
    » https://doi.org/10.2307/3896340
  • Kiesling HE, Nelson AB, Herbel CH. 1969. Chemical composition of tobosa grass collected by hand-plucking and esophageal-fistulated steers. Journal of Range Management 22: 155-159. https://doi.org/10.2307/3896332
    » https://doi.org/10.2307/3896332
  • Lee MA. 2018. A global comparison of the nutritive values of forage plants grown in contrasting environments. Journal of Plant Research 131: 641-654. https://doi.org/10.1007/s10265-018-1024-y
    » https://doi.org/10.1007/s10265-018-1024-y
  • Muir JP, Butler TJ, Wolfe RM, Bow JR. 2008. Harvest techniques change annual warm-season legume forage yield and nutritive value. Agronomy Journal 100: 765-770. https://doi.org/10.2134/agronj2007.0042
    » https://doi.org/10.2134/agronj2007.0042
  • Myers WD, Ludden PA, Nayigihugu V, Hess BW. 2004. A procedure for the preparation and quantitative analysis of samples for titanium dioxide. Journal of Animal Science 82: 179-183. https://doi.org/10.2527/2004.821179x
    » https://doi.org/10.2527/2004.821179x
  • Oelberg K. 1956. Factors affecting the nutritive value of range forage. Journal of Range Management 9: 220-225. https://doi.org/10.2307/3894056
    » https://doi.org/10.2307/3894056
  • Papachriston TG, Dziba LE, Provenza FD. 2005. Foraging ecology of goats and sheep on wooded rangelands. Small Ruminant Research 59: 141-156. https://doi.org/10.1016/j.smallrumres.2005.05.003
    » https://doi.org/10.1016/j.smallrumres.2005.05.003
  • Pell AN, Schofield P. 1993. Computerized monitoring of gas production to measure forage digestion in vitro. Journal of Dairy Science 76: 1063-1073. https://doi.org/10.3168/jds.S0022-0302(93)77435-4
    » https://doi.org/10.3168/jds.S0022-0302(93)77435-4
  • Prohmann PEF, Branco AF, Paris W, Barreto JC, Magalhães VJA, Goes RHTB, et al. 2012. Method of sampling and chemical characterization of forage intake by cattle in pasture ryegrass intercropping oats. Arquivo Brasileiro de Medicina Veterinária e Zootecnia 64: 953-958 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0102-09352012000400023
    » https://doi.org/10.1590/S0102-09352012000400023
  • Robertson JB, Van Soest PJ. 1981. The detergent system of analysis and its application to human foods. p. 23-158. In: James WP, Theander O. eds. The analysis of dietary fibre in Food. Marcel Dekker, New York, NY, USA.
  • Sá Júnior A, Carvalho LG, Silva FF, Alves MC. 2012. Application of the Köppen classification for climatic zoning in the state of Minas Gerais, Brazil. Theoretical and Applied Climatology 108: 1-7. https://doi.org/10.1007/s00704-011-0507-8
    » https://doi.org/10.1007/s00704-011-0507-8
  • Sankhyan SK, Shinde AK, Bhatta R, Karim SA. 1999. Comparison of diet and faecal collection methods for assessment of seasonal variation in dry matter intake by sheep maintained on a Cenchrus ciliaris pasture. Animal Feed Science and Technology 82: 261-269. https://doi.org/10.1016/S0377-8401(99)00104-2
    » https://doi.org/10.1016/S0377-8401(99)00104-2
  • Smith C, Karunaratne S, Badenhorst P, Cogan N, Spangenberg G, Smith K. 2020. Machine learning algorithms to predict forage nutritive value of in situ perennial ryegrass plants using hyperspectral canopy reflectance data. Remote Sensing 12: 928. https://doi.org/10.3390/rs12060928
    » https://doi.org/10.3390/rs12060928
  • Soder KJ, Gregorini P, Scaglia G, Rook AJ. 2009. Dietary selection by domestic grazing ruminants in temperate pastures: current state of knowledge, methodologies, and future direction. Rangeland Ecology & Management 62: 389-398. https://doi.org/10.2111/08-068.1
    » https://doi.org/10.2111/08-068.1

*Corresponding author

<danielcasagrande@ufla.br>

Edited by:

Antonio Faciola

Conflict of interest

The authors declare that there is no conflict of interest.

Publication Dates

  • Publication in this collection
    21 Nov 2025
  • Date of issue
    2025

History

  • Received
    17 Sept 2024
  • Accepted
    11 Apr 2025
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E-mail: scientia@usp.br
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