Combining Ability in Mixtures of Prairie Grass and Clovers

Arturi, Miguel Jacinto; Aulicino, Mónica Beatriz; Ansín, O. E.; Gallinger, Gustavo; Signorio, Rodolfo Domingo

doi:10.4236/ajps.2012.310163

Cited by 6 publications

(3 citation statements)

References 33 publications

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“…Other findings also indicated that mixtures gave higher green forage yields than the pure stands [5] . This finding is in line with other scholars who reported that higher mean biomass yield was obtained from the mixture as compared to their components grown in monoculture [22] . Generally, the result shows that seeding ratio of 50:50 and 25:75 for alfalfa and Rhodes grass were showed the highest total biomass yields for the Rhodes grass and alfalfa in the intercropping system.…”

Section: Dry Matter Yieldsupporting

confidence: 93%

Effect of Seeding Ratios of Alfalfa (Medicago sativa) and Rhodes Grass (Chloris gayana) Mixtures on Dry Matter Yield and Nutritive Quality of the Fodder

Abate¹,

Tilahun²,

Husen³

et al. 2022

J. Sci. Innov. Res.

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The study was conducted at Adami Tulu on-station and Shashemene (FTC) sites for two (2019-2020) consecutive years with the objective to determine the appropriate proportions of seeding ratio that could optimize the dry matter yield and quality of Alfalfa and Rhodes grass mixture. The treatment was laid out in a randomized complete block design (RCBD) with three replications. Different seeding ratios of Alfalfa and Rhodes grass were arranged according to the following treatments: T1; 100% Alfalfa +0 % Rhodes, T2; 0% Alfalfa +100% Rhodes, T3; 50% Alfalfa +50% Rhodes, T4; 75% Alfalfa +25% Rhodes and T5; 25% Alfalfa +75% Rhodes. The results showed that number of tillers per plant of Rhodes grass and leaf to stem ratio of alfalfa, CP% content, NDF% and ADF% were showed a significance (p<0.05) difference among the seeding ratios. The result indicated that seeding ratio has significant (p<0.05) effect on the total dry matter yield of the mixture of alfalfa and Rhodes at both sites. The highest dry matter yield (8.47 t ha-1 ) was obtained from seeding ratio of 25:75, followed by seeding ratio of 50:50 (7.84 tha-1 ). The land equivalent ratios for the mixture were more than one showing that mixture of alfalfa with Rhodes is more advantageous than pure stand of forage. The highest CP% content (21.2%) was recorded from pure stand of alfalfa followed by seeding ratio 75:25 (18.5%), 50:50 (16.8%) and 25:75 (14.6%) while pure stand of Rhodes grass produced the least (11.1%) CP% value. The highest values of NDF% (34.48%) and ADF% (21.25%) were obtained from pure stands of Rhodes grass while the least values were recorded from pure Alfalfa. Thus, it can be concluded that seeding ratio combination of 50:50 could be recommended for use in the study areas and similar agro-ecologies due to its high dry matter yield, good quality and more balanced mixture of forage.

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Section: Dry Matter Yieldsupporting

confidence: 93%

Effect of Seeding Ratios of Alfalfa (Medicago sativa) and Rhodes Grass (Chloris gayana) Mixtures on Dry Matter Yield and Nutritive Quality of the Fodder

Abate¹,

Tilahun²,

Husen³

et al. 2022

J. Sci. Innov. Res.

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“…Red clover can be established as a pure stand or in grass/legume mixtures, as a pasture for livestock. The cultivation of mixed grass/legume grasslands has been increasing because of many potential advantages in comparison to monocultures (Arturi et al, 2012). In Serbia, red clover is mostly grown in pure stands on arable land, but it is also seeded in grass mixtures, and occurs to a limited extent in permanent swards (Simić et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Biodiversity of a red clover collection based on morpho-productive traits

Radinovic¹,

Vasiljević²,

Branković³

et al. 2022

Acta agriculturae Serbica

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Red clover (Trifolium pratense L.) is a meadow and pasture species in natural habitats and also a cultivated species used for animal nutrition. The aim of this research was the assessment of the diversity of 46 red clover accessions based on morpho-productive traits. The traits were investigated according to the UPOV descriptors for red clover-number of internodes, number of branches, stem length, stem thickness, middle leaflet length, middle leaflet width, green matter yield and dry matter yield. The principal components analysis (PCA) explained 74% of the variance of the standardized data and showed relationships between 46 red clover accessions and eight morpho-productive traits, associations among traits and performance of accessions. Among the determined Euclidean distances, the smallest value was obtained for the accessions Rotra and Titus (0.048), the largest value was 1.099 for a pair of NCPGRU2 and Čortanovci accessions, and the average value was 0.380. Two clusters of 46 red clover accessions were separated in the dendrogram based upon UPGMA (Unweighted Pair-Group Method with Arithmetic mean) for eight morpho-productive traits. The first cluster included two subclusters, while the second cluster contained four subclusters. The grouping of the accessions from the red clover collection by the UPGMA cluster analysis can be linked to the geographical origin of the accessions: central and Southern Europe for three subclusters and northeastern Europe for one subcluster.

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“…This fixation of atmospheric nitrogen makes red clover an ideal rotational crop; particularly in organic agricultural systems where no synthetic nitrogen fertilizers are used [4]. A range of studies have observed that the establishment of red clover was more successful when sown in mixtures with grass species rather than in pure, monocultural stands [5,6]. In Estonia, the application of red clover in trials results in a mixed-species approach with other grass species blended to increase its commercial application value, where the complexity of estimation might be higher than monocropping systems.…”

Section: Introductionmentioning

confidence: 99%

The Application of an Unmanned Aerial System and Machine Learning Techniques for Red Clover-Grass Mixture Yield Estimation under Variety Performance Trials

Burnside

Lima

et al. 2021

Remote Sensing

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A significant trend has developed with the recent growing interest in the estimation of aboveground biomass of vegetation in legume-supported systems in perennial or semi-natural grasslands to meet the demands of sustainable and precise agriculture. Unmanned aerial systems (UAS) are a powerful tool when it comes to supporting farm-scale phenotyping trials. In this study, we explored the variation of the red clover-grass mixture dry matter (DM) yields between temporal periods (one- and two-year cultivated), farming operations [soil tillage methods (STM), cultivation methods (CM), manure application (MA)] using three machine learning (ML) techniques [random forest regression (RFR), support vector regression (SVR), and artificial neural network (ANN)] and six multispectral vegetation indices (VIs) to predict DM yields. The ML evaluation results showed the best performance for ANN in the 11-day before harvest category (R² = 0.90, NRMSE = 0.12), followed by RFR (R² = 0.90 NRMSE = 0.15), and SVR (R² = 0.86, NRMSE = 0.16), which was furthermore supported by the leave-one-out cross-validation pre-analysis. In terms of VI performance, green normalized difference vegetation index (GNDVI), green difference vegetation index (GDVI), as well as modified simple ratio (MSR) performed better as predictors in ANN and RFR. However, the prediction ability of models was being influenced by farming operations. The stratified sampling, based on STM, had a better model performance than CM and MA. It is proposed that drone data collection was suggested to be optimum in this study, closer to the harvest date, but not later than the ageing stage.

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Combining Ability in Mixtures of Prairie Grass and Clovers

Cited by 6 publications

References 33 publications

Effect of Seeding Ratios of Alfalfa (Medicago sativa) and Rhodes Grass (Chloris gayana) Mixtures on Dry Matter Yield and Nutritive Quality of the Fodder

Effect of Seeding Ratios of Alfalfa (Medicago sativa) and Rhodes Grass (Chloris gayana) Mixtures on Dry Matter Yield and Nutritive Quality of the Fodder

Biodiversity of a red clover collection based on morpho-productive traits

The Application of an Unmanned Aerial System and Machine Learning Techniques for Red Clover-Grass Mixture Yield Estimation under Variety Performance Trials

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