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Randomized Controlled Trial
. 2023 May 10;18(5):e0285482.
doi: 10.1371/journal.pone.0285482. eCollection 2023.

Evaluating the impact of Trichoderma biofertilizer and planting dates on mustard yield performance using the InfoCrop growth model

Affiliations
Randomized Controlled Trial

Evaluating the impact of Trichoderma biofertilizer and planting dates on mustard yield performance using the InfoCrop growth model

Shams Shaila Islam et al. PLoS One. .

Abstract

A crop simulation model is adopted to calculate the potential yield in a certain location. The data sets generated in each scenario (2021-2022) were used to evaluate the InfoCrop model. A field experiment using a randomized complete block design was conducted at the Agronomy Department's research field, Hajee Mohammad Danesh Science and Technology University. The following two factors: 1) factor A: sowing dates (Planting date 1: PD1 = 5th November and Planting date 2: PD2 = 15th November 2021) and 2) factor B: Trichoderma biofertilizers (T1 = control, T2 = 50% chemical fertilizer + 2,000 kg ha-1 Trichoderma biofertlizer, T3 = fully chemical fertilizer; and T4 = fully 3,000 kg ha-1 Trichoderma biofertilizer). Three BARI (Bangladesh Agricultural Research Institute) released varieties (V1 = BARI Sarisa-14, V2 = BARI Sarisa-16, and V3 = BARI Sarisa-17) used for the completion of the experiment. The Trichoderma biofertilizer and planting dates had a significant influence on yield and yield attributes of mustard. Results showed that plant height, leaf width, leaves per plant, pods per plant, harvest index, maturity date, and yield were significantly affected by Trichoderma biofertilizer treatments, two different conditions, and varieties. The regression analysis indicated a significant linear relationship between two different growing conditions especially for harvest index PD2>PD1 (0.88>0.83), grain yield (0.94>0.90), flowering date (0.95>0.91) and maturity date (0.95>0.90). It was found that the model significantly overestimated all the parameters with an acceptable error range (<15%) while growth and yield characteristics including flowering and maturity dates and yield were simulated and results were compared to observed data. BARI Sarisa 16 had the highest simulated yield of 2.5 t ha-1 and showed a high yielding variety among the used varieties in the experiment. As a result, it can be concluded that if the InfoCrop growth model is carefully calibrated, it will be an excellent tool for evaluating and identifying the best yielding variety.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Weather conditions during the experimental year. A: Maximum and Minimum temperature and B: Cumulative rainfall and relative humidity.
Fig 2
Fig 2
Linear regression relationships between Trichoderma biofertilizer treatments with different planting dates with Plant height (A), leaves per plant (B), leaf width (C), pods per plant (D), harvest index (E), grain yield (F), flowering days (G), and maturity days (H). *** Significant at p < 0.001.
Fig 3
Fig 3. Plot of Pearson’s correlation analysis among the yield traits of mustard.
Blue, dark blue and sky blue shaded indicated strong and positive correlation among yield attributes. Red color indicates negative correlation. The color intensity is proportional to the computed coefficients. PH = Plant Height, MD = Maturity Date, FD = Flowering Date, GY = Grain Yield, P_P = Pods per Plant, HI = Harvest Index, L_P = Leaves per Plant, and L_W = Leaves per Width.
Fig 4
Fig 4. 1: 1 graph showing the relationship between simulated and measured data.
A: Pods per plant, B: Leaves per plant, and C: Harvest index.
Fig 5
Fig 5. 1: 1 graph showing the relationship between simulated and measured data.
A: Grain yield, B: Flowering date, and C: Maturity date.

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