2021
DOI: 10.1080/27658511.2021.1895475
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Adaptability, forage yield and nutritional quality of alfalfa (Medicago sativa) genotypes

Abstract: Livestocks fed with high-quality forage deliver better milk and meat, which could benefit the nutritional health of their keepers and consumers. Six alfalfa genotypes were assessed across four locations, Arba Minch, Areka Mante Dubo, Bonga and Hawassa Dilla, for adaptability, forage dry matter (DM) yield, crude protein (CP) concentration, nutrient composition and digestibility characteristics from August 2016 to January 2019. The genotypes were evaluated in a randomized complete block design with four replicat… Show more

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Cited by 13 publications
(12 citation statements)
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“…These results are in harmony with those reported by [ 32 ], that the investigated six alfalfa genotypes exhibited high total variability for plant height and forage yield. Some previous studies showed the broadest range of variation for some alfalfa cultivars in all morphological traits evaluated [ 33 , 34 ]. Generally, the alfalfa forage yield depends on plant height, and number of tillers.…”
Section: Resultsmentioning
confidence: 99%
“…These results are in harmony with those reported by [ 32 ], that the investigated six alfalfa genotypes exhibited high total variability for plant height and forage yield. Some previous studies showed the broadest range of variation for some alfalfa cultivars in all morphological traits evaluated [ 33 , 34 ]. Generally, the alfalfa forage yield depends on plant height, and number of tillers.…”
Section: Resultsmentioning
confidence: 99%
“…Alfalfa ( Medicago sativa ) is a perennial leguminous plant cultivated worldwide [ 7 ]. It is the most important forage in stockbreeding, and it has good quality, high yield, and strong resistance to stress [ 8 , 9 ]. However, low seed yields have limited the long-term development of the alfalfa industry.…”
Section: Introductionmentioning
confidence: 99%
“…The 10-m alfalfa map was derived from the 10-m Sentinel-2 images, which may facilitate the mapping of smallholder alfalfa fields that are not achievable from MODIS or Landsat images due to their coarseness and lack of high spatial resolution. Moreover, we interpolated the Sentinel-2 data to obtain a complete time series data set, filling in the abnormal values affected by clouds and thereby improving the identification accuracy; (2). Using GEE platform to process large-scale remote sensing data, it overcome the problems of cloud cover and insufficient computing resources in traditional remote sensing methods, and enhanced the processing efficiency and quality of remote sensing data; (3).…”
Section: Alfalfa Remote Sensing Recognition and Area Extractionmentioning
confidence: 99%