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Related papers: Phenotypic variability in Italian rice germplasm

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Development of either drought-resistant or drought-tolerant varieties in rice (Oryza sativa L.), especially for high yield in the context of climate change, is a crucial task across the world. The need for high yielding rice varieties is a…

A crop can be represented as a biotechnical system in which components are either chosen (cultivar, management) or given (soil, climate) and whose combination generates highly variable stress patterns and yield responses. Here, we used…

Populations and Evolution · Quantitative Biology 2014-03-13 Pierre Casadebaig , Ronan Trépos , Victor Picheny , Nicolas B. Langlade , Patrick Vincourt , Philippe Debaeke

Genotype-to-Phenotype (G2P) prediction plays a pivotal role in crop breeding, enabling the identification of superior genotypes based on genomic data. Rice (Oryza sativa), one of the most important staple crops, faces challenges in…

Genomics · Quantitative Biology 2025-03-17 Yunxuan Dong , Siyuan Chen , Jisen Zhang

Crop yield is a highly complex trait determined by multiple factors such as genotype, environment, and their interactions. Accurate yield prediction requires fundamental understanding of the functional relationship between yield and these…

Machine Learning · Computer Science 2019-06-12 Saeed Khaki , Lizhi Wang

Post-genomic research deals with challenging problems in screening genomes of organisms for particular functions or potential for being the targets of genetic engineering for desirable biological features. 'Phenotyping' of wild type and…

Quantitative Methods · Quantitative Biology 2010-09-06 Hesam T. Dashti , Jernej Tonejc , Adel Ardalan , Alireza F. Siahpirani , Sabrina Guettes , Zohreh Sharif , Liya Wang , Amir H. Assadi

Background and Aims: Prediction of phenotypic traits from new genotypes under untested environmental conditions is crucial to build simulations of breeding strategies to improve target traits. Although the plant response to environmental…

Statistics Theory · Mathematics 2010-10-27 Veronique Letort , Paul Mahe , Paul-Henry Cournède , Philippe De Reffye , Brigitte Courtois

Crop production needs to increase in a sustainable manner to meet the growing global demand for food. To identify crop varieties with high yield potential, plant scientists and breeders evaluate the performance of hundreds of lines in…

Image and Video Processing · Electrical Eng. & Systems 2019-06-25 Ali Moghimi , Ce Yang , James A. Anderson

High-dimensional time series phenotypic data is becoming increasingly common within plant breeding programmes. However, analysing and integrating such data for genetic analysis and genomic prediction remains difficult. Here we show how…

Eradicating hunger and malnutrition is a key development goal of the 21st century. We address the problem of optimally identifying seed varieties to reliably increase crop yield within a risk-sensitive decision-making framework.…

Machine Learning · Computer Science 2017-11-17 Huaiyang Zhong , Xiaocheng Li , David Lobell , Stefano Ermon , Margaret L. Brandeau

Training population selection for genomic selection has captured a great deal of interest in animal and plant breeding. In this article, we derive a computationally efficient statistic to measure the reliability of estimates of genetic…

Methodology · Statistics 2014-05-22 Deniz Akdemir

The application of spectral-shifting films in greenhouses to shift green light to red light has shown variable growth responses across crop species. However, the yield enhancement of crops under altered light quality is related to the…

Quantitative Methods · Quantitative Biology 2025-11-20 Jun Hyeun Kang , Jung Eek Son , Tae In Ahn

Plant breeding and variety trials are usually conducted in multiple environments sampled from a defined target population of environments in order to characterize the performance of breeding lines or varieties. When the population is large…

Applications · Statistics 2026-05-01 Maryna Prus , Lenka Filová , Hans-Peter Piepho , Waqas Ahmed Malik

Soybean production is susceptible to biotic and abiotic stresses, exacerbated by extreme weather events. Water limiting stress, i.e. drought, emerges as a significant risk for soybean production, underscoring the need for advancements in…

In barley plants, water shortage causes many changes on the morphological, physiological and biochemical levels resulting in the reduction of grain yield. In the present study the results of various experiments on the response of the same…

Understanding the genetic basis of phenotypic plasticity is crucial for predicting and managing climate change effects on wild plants and crops. Here, we combined crop modeling and quantitative genetics to study the genetic control of oil…

Developing computer vision-based rice phenotyping techniques is crucial for precision field management and accelerating breeding, thereby continuously advancing rice production. Among phenotyping tasks, distinguishing image components is a…

Accurate prediction of crop yield supported by scientific and domain-relevant insights, can help improve agricultural breeding, provide monitoring across diverse climatic conditions and thereby protect against climatic challenges to crop…

A crop can be viewed as a complex system with outputs (e.g. yield) that are affected by inputs of genetic, physiology, pedo-climatic and management information. Application of numerical methods for model exploration assist in evaluating the…

Quantitative Methods · Quantitative Biology 2016-01-26 Pierre Casadebaig , Bangyou Zheng , Scott Chapman , Neil Huth , Robert Faivre , Karine Chenu

Plant breeding underpins global food security through incremental, accumulating improvements in crop yield, quality and sustainability, achieved via repeated cycles of crop ranking, selection and crossing. Climate change disrupts this…

Machine Learning · Computer Science 2026-05-07 Aike Potze , Fred van Eeuwijk , Ioannis N. Athanasiadis

The prediction of crop yields internationally is a crucial objective in agricultural research. Thus, this study implements 6 regression models (Linear, Tree, Gradient Descent, Gradient Boosting, K Nearest Neighbors, and Random Forest) to…

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