Silage Yield and Quality of Forage Peas and Hungarian Vetch and Triticale Binary Mixtures

This study was conducted in order to determine silage quality in binary mixtures of forage pea (Pisum sativum ssp. arvense L. "FP") and Hungarian vetch (Vicia pannonica C. "HV") and triticale (X triticosecale Wittmack. "T") in 2021-2022 vegetation period. Hungarian vetch and forage pea and triticale seeds were sown in 6 different mixture ratios (legume/triticale; 100%/0, 80/20%, 60/40%, 40/60%, 20/80%). The experiment was established according to randomized blocks experimental design with 3 replications. In the study, dry matter content, pH, flieg score, quality class, crude protein, ADF, NDF, Ca, K, Mg, P, lactic acid and acetic acid contents were analyzed for silage yield and quality. The dry matter of silages was between 23.83 and 36.49%, while the pH was between 4.57 and 5.18. The highest crude protein was determined in pure forage peas (22%) and it was determined that it increased in parallel with the increase in the legume ratio in the mixture. Mineral contents were found to be high in sole and intense legume silages, similar to crude protein. In terms of silage quality in the examined parameters, mixed sowing gave better results than sole sowing. As a result of the study, 80:20 T/HV mixture ratio sowing is recommended for Yozgat and regions with similar ecology in terms of silage yield and quality.

Authors

Institutions

Publication Details

Journal
Selcuk Journal of Agricultural and Food Sciences
Published
2024-12-16
DOI
https://doi.org/10.15316/sjafs.2024.039
Citations
1
Primary Topic
Agronomic Practices and Intercropping Systems
Type
article
Field-Weighted Citation Impact
0.57

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Silage Yield and Quality of Forage Peas and Hungarian Vetch and Triticale Binary Mixtures

Ahmet MİRZA, Medine ÇOPUR DOĞRUSÖZ
1 citations
Selcuk Journal of Agricultural and Food Sciences
Agronomic Practices and Intercropping Systems
0.57
article

Silage Yield and Quality of Forage Peas and Hungarian Vetch and Triticale Binary Mixtures

Ahmet MİRZA, Medine ÇOPUR DOĞRUSÖZ
article en
1 citations

Abstract

This study was conducted in order to determine silage quality in binary mixtures of forage pea (Pisum sativum ssp. arvense L. "FP") and Hungarian vetch (Vicia pannonica C. "HV") and triticale (X triticosecale Wittmack. "T") in 2021-2022 vegetation period. Hungarian vetch and forage pea and triticale seeds were sown in 6 different mixture ratios (legume/triticale; 100%/0, 80/20%, 60/40%, 40/60%, 20/80%). The experiment was established according to randomized blocks experimental design with 3 replications. In the study, dry matter content, pH, flieg score, quality class, crude protein, ADF, NDF, Ca, K, Mg, P, lactic acid and acetic acid contents were analyzed for silage yield and quality. The dry matter of silages was between 23.83 and 36.49%, while the pH was between 4.57 and 5.18. The highest crude protein was determined in pure forage peas (22%) and it was determined that it increased in parallel with the increase in the legume ratio in the mixture. Mineral contents were found to be high in sole and intense legume silages, similar to crude protein. In terms of silage quality in the examined parameters, mixed sowing gave better results than sole sowing. As a result of the study, 80:20 T/HV mixture ratio sowing is recommended for Yozgat and regions with similar ecology in terms of silage yield and quality.

Selcuk Journal of Agricultural and Food Sciences
Yozgat Bozok Üniversitesi (TR)
Division of Graduate Education
Zero hunger
Openalex Percentile: Top 27%
Agronomic Practices and Intercropping Systems
0.57
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.