the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Nov 2025
Comparative Impact of Bio-Organic and Inorganic Fertilizer Application on Soil Health, Grain Quality and Yield Stability in Nutrient Deficient Regions
Abstract. Soil fertility limitations in arid regions restrict wheat productivity and grain nutritional quality, with zinc (Zn) deficiency being a major concern. Sustainable soil amendments combining organic and microbial inputs offer potential to address these constraints. This study aimed to evaluate the effectiveness of bio-organic fertilization in enhancing wheat growth, yield, grain Zn biofortification, and soil fertility under deficient arid field conditions. Two field trials were conducted in Bahawalpur and Bahawalnagar, Pakistan, using a randomized complete block design. Treatments included compost, ZnO (2 %), ZnSO4, zinc-solubilizing bacteria (ZSB), and their combinations. Wheat growth, yield, grain nutrient concentrations, and soil fertility indicators (organic matter, microbial biomass nitrogen (MBN), microbial biomass carbon (MBC), and nutrient availability) were measured. Microbial populations were determined through colony-forming units. Correlation and principal component analysis (PCA) were applied to explore associations among variables. The integrated application of compost + ZnO + ZSB significantly improved wheat height (19 %), biomass (20 %), yield attributes (10 %), and grain Zn concentration (39 %) compared with the control. Soil fertility parameters also increased (organic matter, 39 %; MBN, 32 %; MBC, 27 %). Correlation and PCA highlighted strong positive relationships among microbial populations, soil fertility, and crop performance. Bio-organic fertilization provides an eco-friendly and effective strategy to improve wheat yield, Zn biofortification, and soil fertility in arid agroecosystems.
- Preprint
(1225 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 18 Dec 2025)
-
CC1: 'Comment on egusphere-2025-4852', Usman Jamshaid, 17 Nov 2025
reply
-
AC1: 'Reply on CC1', azhar Hussain, 18 Nov 2025
reply
We sincerely thank the professor/scientist/researcher for this encouraging remark. We appreciate the positive evaluation and remain confident that the insights presented in this study will contribute meaningfully to ongoing efforts in sustainable soil management and climate-resilient agriculture.
Citation: https://doi.org/10.5194/egusphere-2025-4852-AC1
-
AC1: 'Reply on CC1', azhar Hussain, 18 Nov 2025
reply
-
RC1: 'Comment on egusphere-2025-4852', Rubab Sarfraz, 21 Nov 2025
reply
Please elaborate how PCA in this study predicts the relationship between crop performance and microbial population?Â
Why significance level upto 0.0001 has been described?Â
How LSD was calculated? Is it for overall treatment effect ? Why it is significant to calculate here?Â
-
AC2: 'Reply on RC1', azhar Hussain, 26 Nov 2025
reply
Response 1: We thank the reviewer for this suggestion. Principal Component Analysis (PCA) in our study is used as an exploratory multivariate tool to summarize covariation among many soil, microbial and plant variables and to visualize which variables move together (i.e., covary). PCA does not perform causal prediction in the strict sense, but it identifies the main axes (principal components) that explain the majority of variance in the dataset. In our results, PC-1 explained the large majority of variance (92.6% in Trial I, 91.5% in Trial II) and variables such as organic matter (OM), total organic carbon (TOC), nitrogen (N), phosphorus (P), microbial biomass carbon (MBC), microbial biomass nitrogen (MBN) and colony forming unit (CFU) had strong positive loadings on PC-1. Treatments with high positive PC-1 scores (e.g., Compost + 2% ZnO + ZSB) therefore cluster together with higher microbial indicators and better crop performance, demonstrating a strong co-variation between microbial population/biomass and crop performance. In short, PCA shows that microbial population and crop performance co-vary along the same major gradient (PC-1), supporting the interpretation that improved microbial activity and soil fertility are associated with improved crop growth and yield in our trials.Â
Response 2:Â
Thank you, The manuscript used conventional significance notation (asterisks) to indicate ranges of p-values; the table legend defined **** as p < 0.0001, while the global decision threshold for tests was α = 0.05. The appearance of **** (p < 0.0001) simply reflects that some comparisons produced very small p-values (highly significant differences) when evaluated by ANOVA / post-hoc tests in Statistix / OriginPro. We will clarify the legend and methods, so readers are not confused: we will keep α = 0.05 as the threshold for declaring significance but will report p-value ranges using the asterisk scheme.
Response 3:Â
The ANOVA F-test was used to evaluate the overall treatment effect (i.e., whether any treatment means differ). Where the ANOVA F-test was significant, we used the Least Significant Difference (LSD) procedure to perform pairwise comparisons between treatment means. LSD was calculated from the ANOVA residual mean square (MSE) and the number of replicates according to the standard formula:
LSDα=tα/2,  df error × √2 ×​​ MSE/r
where tα/2, df error ​​ is the t-value at the chosen α (0.05) and the residual degrees of freedom, MSE is the mean square error from the ANOVA, and r is the number of replicates (here r = 3). The LSD values reported in Table 1 are the LSD at p ≤ 0.05 computed from ANOVA outputs in Statistix 8.1. LSD is appropriate here because the experiment used an RCBD with balanced replications and our objective was to identify which specific treatments differed (pairwise) after a significant overall ANOVA.
Citation: https://doi.org/10.5194/egusphere-2025-4852-AC2
-
AC2: 'Reply on RC1', azhar Hussain, 26 Nov 2025
reply
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 105 | 52 | 19 | 176 | 10 | 7 |
- HTML: 105
- PDF: 52
- XML: 19
- Total: 176
- BibTeX: 10
- EndNote: 7
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
This study makes a valuable scientific contribution by demonstrating how balanced fertilizer strategies can restore degraded soils and support sustainable agriculture.