Interannual Climatic Variability Modulates Biostimulant and Herbicide Effects on Yield and Seed Quality of White Lupin Under Rainfed Conditions

White lupin (<i>Lupinus albus L</i>.) is increasingly promoted as a sustainable protein crop; however, the consistency of agronomic input responses under rainfed continental conditions remains insufficiently documented. This study evaluated the interannual consistency of a foliar amino acid-based biostimulant (Aminotop N) and herbicide-based weed control on morphological traits, grain yield, seed physical quality (thousand-seed weight and hectoliter mass), and seed nitrogen and crude protein concentration of white lupin (cv. Măriuca). A 2 × 2 factorial field experiment arranged in a randomized complete block design was conducted across two consecutive growing seasons (2024-2025). Two-way ANOVA revealed significant effects of year and significant year × treatment interactions for grain yield and seed physical traits (<i>p</i> ≤ 0.05), indicating season-dependent treatment responses. Statistically significant treatment differences were detected in 2024, whereas no differences were observed among treatments in 2025. Seed total nitrogen concentration and crude protein content remained statistically stable across treatments and years. Principal component analysis explained 98.2% of total variance, with the first component primarily separating years rather than treatments. These results demonstrate that treatment effects were not consistently expressed across seasons and highlight the necessity of multi-year validation when assessing agronomic input effectiveness in white lupin under rainfed conditions.

Authors

Institutions

Publication Details

Journal
Plants
Published
2026-02-27
DOI
https://doi.org/10.3390/plants15050726
Primary Topic
Botanical Research and Chemistry
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Interannual Climatic Variability Modulates Biostimulant and Herbicide Effects on Yield and Seed Quality of White Lupin Under Rainfed Conditions

Danut Petru Simioniuc, Ioan Puiu, Teodor Robu, Florin Velică et al.
Plants
Botanical Research and Chemistry
article

Interannual Climatic Variability Modulates Biostimulant and Herbicide Effects on Yield and Seed Quality of White Lupin Under Rainfed Conditions

Danut Petru Simioniuc, Ioan Puiu, Teodor Robu, Florin Velică, Carmen-Simona Ghițău
article en

Abstract

White lupin (<i>Lupinus albus L</i>.) is increasingly promoted as a sustainable protein crop; however, the consistency of agronomic input responses under rainfed continental conditions remains insufficiently documented. This study evaluated the interannual consistency of a foliar amino acid-based biostimulant (Aminotop N) and herbicide-based weed control on morphological traits, grain yield, seed physical quality (thousand-seed weight and hectoliter mass), and seed nitrogen and crude protein concentration of white lupin (cv. Măriuca). A 2 × 2 factorial field experiment arranged in a randomized complete block design was conducted across two consecutive growing seasons (2024-2025). Two-way ANOVA revealed significant effects of year and significant year × treatment interactions for grain yield and seed physical traits (<i>p</i> ≤ 0.05), indicating season-dependent treatment responses. Statistically significant treatment differences were detected in 2024, whereas no differences were observed among treatments in 2025. Seed total nitrogen concentration and crude protein content remained statistically stable across treatments and years. Principal component analysis explained 98.2% of total variance, with the first component primarily separating years rather than treatments. These results demonstrate that treatment effects were not consistently expressed across seasons and highlight the necessity of multi-year validation when assessing agronomic input effectiveness in white lupin under rainfed conditions.

PlantsVol. 15(5)
"Ion Ionescu de la Brad" Iasi University of Life Sciences (RO)
Zero hunger
Openalex Percentile: Top 56%
Botanical Research and Chemistry
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.