Browsing by Person "Rahman, Niaz Md. Farhat"

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Regression approaches for modeling genotype-environment interaction and making predictions into unseen environments
(2026) Hrachov, Maksym; Piepho, Hans-Peter; Rahman, Niaz Md. Farhat; Malik, Waqas Ahmed; Hrachov, Maksym; Biostatistics Unit, Institute of Crop Science, University of Hohenheim, 70593, Stuttgart, Germany; Piepho, Hans-Peter; Biostatistics Unit, Institute of Crop Science, University of Hohenheim, 70593, Stuttgart, Germany; Rahman, Niaz Md. Farhat; Bangladesh Rice Research Institute (BRRI), Gazipur, Bangladesh; Malik, Waqas Ahmed; Biostatistics Unit, Institute of Crop Science, University of Hohenheim, 70593, Stuttgart, Germany
In plant breeding and variety testing, there is an increasing interest in making use of environmental information to enhance predictions for new environments. Here, we will review linear mixed models that have been proposed for this purpose. The emphasis will be on predictions and on methods to assess the uncertainty of predictions for new environments. Our point of departure is straight-line regression, which may be extended to multiple environmental covariates and genotype-specific responses. When observable environmental covariates are used, this is also known as factorial regression. Early work along these lines can be traced back to Stringfield & Salter (1934) and Yates & Cochran (1938), who proposed a method nowadays best known as Finlay-Wilkinson regression. This method, in turn, has close ties with regression on latent environmental covariates and factor-analytic variance-covariance structures for genotype-environment interaction. Extensions of these approaches – reduced rank regression, kernel- or kinship-based approaches, random coefficient regression, and extended Finlay-Wilkinson regression – will be the focus of this paper. Our objective is to demonstrate how seemingly disparate methods are very closely linked and fall within a common model-based prediction framework. The framework considers environments as random throughout, with genotypes also modeled as random in most cases. We will discuss options for assessing uncertainty of predictions, including cross validation and model-based estimates of uncertainty, the latter one being estimated using our new suggested approach. The methods are illustrated using a long-term rice variety trial dataset from Bangladesh.
Sustaining rice productivity through weather‐resilient agricultural practices
(2023) Rahman, Niaz Md. Farhat; Malik, Waqas Ahmed; Baten, Md. Azizul; Kabir, Md. Shahjahan; Rahman, Mohammad Chhiddikur; Ahmed, Rokib; Hossain, ABM Zahid; Hossain, Md. Mofazzel; Halder, Tuhin; Bhuiyan, Md. Khairul Alam; Khan, Mohammad Ashik Iqbal; Khan, Raihanul Haque; Ahasan, Nazmul; Piepho, Hans‐Peter
BACKGROUND: Enhancing productivity and profitability and reducing climatic risk are the major challenges for sustaining rice production. Extreme weather can have significant and varied effects on crops, influencing agricultural productivity, crop yields and food security. RESULTS: In this study, a comparative evaluation of two crop management systems was performed involving farmers adopting a weather forecast-based advisory service (WFBAS) and usual farmers’ practice (FP). WFBAS crop management followed the generated weather forecast-based advice whereas the control farmers (FP) did not receive any weather forecast-based advice, rather following their usual rice cultivation practices. The results of the experiments revealed that WFBAS farmers had a significant yield advantage over FP farmers. With the WFBAS technology, the farmers used inputs judiciously, utilized the benefit of favorable weather and minimized the risk resulting from extreme weather events. As a result, besides the yield enhancement, WFBAS provided a scope to protect the environment with the minimum residual effect of fertilizer and pesticides. It also reduced the pressure on groundwater by ensuring efficient water management. Finally, the farmers benefited from higher income through yield enhancement, reduction of the costs of production and reduction of risk. CONCLUSION: A successful and extensive implementation of WFBAS in the rice production system would assist Bangladesh in achieving Sustainable Development Goal 2.4, which focuses on rice productivity and profitability of farmers as well as long-term food security of the country.