Rhizobial inoculation and UAV-derived vegetation index associated with grain yield in common bean
Taine Teotonio T da Rocha , Vitório Antônio P de Souza , Adriano Teodoro Bruzzi , Mateus Ribeiro Piza , Márcia Rufini , Fatima Maria de S Moreira , Paulo Henrique Frois C Barros , Antônio Henrique F de Carvalho , Júlia Silva P dos Santos , Raphael Rodrigues Pereira , Marcelo Araújo Junqueira Ferraz
AIMS Agriculture and Food ›› 2026, Vol. 11 ›› Issue (4) : 1011 -1025.
Common bean is one of the most important food legumes worldwide. However, low grain yields among smallholder farmers are often associated with insufficient mineral fertilization and difficulties in identifying nutrient deficiencies. The crop can establish symbiotic associations with nitrogen-fixing bacteria, meeting part of its nitrogen requirements through biological nitrogen fixation (BNF). We aimed to evaluate the effects of rhizobial inoculation and mineral nitrogen fertilization on the grain yield of common bean cultivars, as well as to assess the potential of the modified photochemical reflectance index (MPRI) as an indicator associated with grain yield. The experiment was conducted under field conditions in Lavras, Minas Gerais, Brazil. Seven common bean cultivars and four nitrogen sources were evaluated: inoculation with the UFLA 02-100 and CIAT 899 strains, mineral nitrogen fertilization, and a non-fertilized control. Agronomic and physiological traits were evaluated throughout the crop cycle, and aerial images were obtained at 50 days after sowing to determine MPRI. The cultivar × nitrogen source interaction was not significant for the evaluated traits. Inoculation with UFLA 02-100 resulted in grain yield comparable to mineral nitrogen fertilization despite lower shoot N accumulation, whereas CIAT 899 did not differ from the non-fertilized control in grain yield. MPRI was significantly associated with grain yield but not with shoot N accumulation, indicating its potential as a non-destructive indicator of crop performance.
Phaseolus vulgaris / Rhizobium / nitrogen / genetic variability / inoculation
| [1] |
|
| [2] |
|
| [3] |
|
| [4] |
|
| [5] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
|
| [15] |
|
| [16] |
|
| [17] |
|
| [18] |
|
| [19] |
|
| [20] |
|
| [21] |
|
| [22] |
|
| [23] |
R Core Team (2024) R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria. |
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [30] |
|
| [31] |
|
| [32] |
|
| [33] |
|
| [34] |
|
| [35] |
|
| [36] |
|
| [37] |
|
| [38] |
|
| [39] |
|
| [40] |
|
| [41] |
|
/
| 〈 |
|
〉 |