Journal of Agriculture and Food Research (Mar 2024)

Genetic and seasonal variation in forage quality of lucerne (Medicago sativa L.) for resilience to climate change in arid environments

  • Samir Tlahig,
  • Mohamed Neji,
  • Ahlem Atoui,
  • Mabrouk Seddik,
  • Mohamed Dbara,
  • Hedi Yahia,
  • Kamel Nagaz,
  • Sghaier Najari,
  • Touhami Khorchani,
  • Mohamed Loumerem

Journal volume & issue
Vol. 15
p. 100986

Abstract

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This study assesses seasonal variation in forage quality traits among 12 lucerne (Medicago sativa L.), half-sib breeding lines tailored for Tunisian arid regions. Distinct classes of lines were identified based on chemical composition, in vitro digestibility, the relative feed value (RFV) and total digestible nutrients (TDN). The A56 line displayed poor quality, characterized by high acid detergent fiber (ADF) and neutral detergent fiber (NDF) content. Moderate quality was seen in the A17, S47, S71, and A73 lines, with A17 exhibiting better relative feed value and higher dry matter production. The local 'Gabssia' genotype lines (L4, L23, L39) featured high protein content (CP) but low digestibility due to elevated fiber percentages, primarily ADF. ABT21 and ABT52 lines were most digestible, while ABT32 and E34 had superior relative feed values. These findings illuminate the seasonal dynamics of lucerne forage quality in arid environments, providing insights for breeding strategies in enhancing nutritional value. Meticulous exploration of parameters including seasonal variations, cutting cycles, and genotypic differences reveal the multifaceted nature of forage quality. Furthermore, it highlights impacts of each element on nutritional traits, along with correlations between parameters and climatic variables. Heritability estimates range from 0.01 to 0.61, underscoring genetics-environment interplay. These values highlight potential for targeted breeding, while moderate heritability emphasizes external factors' influence. Insights contribute to discussions on sustainable forage production, aiding precision breeding strategies for improved livestock nutrition in challenging environments.

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