The Impact of Artificial Intelligence on the Role of Management Accountants DOI

Amanda F. Mhlongo

Contributions to finance and accounting, Journal Year: 2025, Volume and Issue: unknown, P. 63 - 82

Published: Jan. 1, 2025

Language: Английский

Transcription factors – insights into abiotic and biotic stress resilience and crop improvement DOI Creative Commons
Roopali Bhoite,

Olive Onyemaobi,

Tanushree Halder

et al.

Current Plant Biology, Journal Year: 2025, Volume and Issue: unknown, P. 100434 - 100434

Published: Jan. 1, 2025

Language: Английский

Citations

4

Approaches for the amelioration of adverse effects of drought stress on soybean plants: from physiological responses to agronomical, molecular, and cutting-edge technologies DOI
Muhammad Faheem Jan, Muhammad Tanveer Altaf, Waqas Liaqat

et al.

Plant and Soil, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 14, 2025

Language: Английский

Citations

2

Functional Phenotyping: Understanding the Dynamic Response of Plants to Drought Stress DOI Creative Commons
Sheikh Mansoor, Yong Suk Chung

Current Plant Biology, Journal Year: 2024, Volume and Issue: 38, P. 100331 - 100331

Published: Feb. 21, 2024

Drought stress, exacerbated by climate change, presents a critical global challenge characterized increasingly severe and prolonged dehydration events. This phenomenon poses significant obstacles to both agricultural productivity ecological stability. One promising strategy for addressing this issue involves functional phenotyping, methodology that provides invaluable insights into the intricate responses of plants water scarcity. A profound understanding these is crucial advancement drought-tolerant crop cultivars/species, optimization irrigation methodologies, implementation effective resource management practices in agriculture. review underscores potential developing an ideal phenotyping tool continuously monitors plant's physiological profile response shifting environmental parameters. Such approach enables multifaceted characterization assessment various phenotypes levels. Through application techniques, we stand gain plant behaviour, thereby contributing development crops establishment sustainable systems.

Language: Английский

Citations

17

Modern Plant Breeding Techniques in Crop Improvement and Genetic Diversity: From Molecular Markers and Gene Editing to Artificial Intelligence—A Critical Review DOI Creative Commons
Lixia Sun,

Mingyu Lai,

Fozia Ghouri

et al.

Plants, Journal Year: 2024, Volume and Issue: 13(19), P. 2676 - 2676

Published: Sept. 24, 2024

With the development of new technologies in recent years, researchers have made significant progress crop breeding. Modern breeding differs from traditional because great changes technical means and concepts. Whereas initially focused on high yields, modern focuses orientations based different crops’ audiences or by-products. The process starts creation material populations, which can be constructed by natural mutagenesis, chemical physical mutagenesis transfer DNA (T-DNA), Tos17 (endogenous retrotransposon), etc. Then, gene function mined through QTL mapping, Bulked-segregant analysis (BSA), Genome-wide association studies (GWASs), RNA interference (RNAi), editing. at transcriptional, post-transcriptional, translational levels, functions genes are described terms post-translational aspects. This article mainly discusses application above scientific technological methods advantages limitations diversity. In particular, editing technology has contributed to research.

Language: Английский

Citations

14

Genomics, Phenomics, and Machine Learning in Transforming Plant Research: Advancements and Challenges DOI Creative Commons
Sheikh Mansoor,

E.M.B.M. Karunathilake,

Thai Thanh Tuan

et al.

Horticultural Plant Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 1, 2024

Advances in gene editing and natural genetic variability present significant opportunities to generate novel alleles select sources of variation for horticulture crop improvement. The improvement crops enhance their resilience abiotic stresses new pests due climate change is essential future food security. field genomics has made strides over the past few decades, enabling us sequence analyze entire genomes. However, understanding complex relationship between genes expression phenotypes - observable characteristics an organism requires a deeper phenomics. Phenomics seeks link information with biological processes environmental factors better understand traits diseases. Recent breakthroughs this include development advanced imaging technologies, artificial intelligence algorithms, large-scale data analysis techniques. These tools have enabled explore relationships genotype, phenotype, environment unprecedented detail. This review explores importance phenotypes. Integration efficient high throughput plant phenotyping as well potential machine learning approaches genomic phenomics trait discovery.

Language: Английский

Citations

12

UAV image acquisition and processing for high‐throughput phenotyping in agricultural research and breeding programs DOI Creative Commons
Ocident Bongomin, Jimmy Lamo,

Joshua Mugeziaubwa Guina

et al.

The Plant Phenome Journal, Journal Year: 2024, Volume and Issue: 7(1)

Published: Feb. 19, 2024

Abstract We are in a race against time to combat climate change and increase food production by 70% feed the ever‐growing world population, which is expected double 2050. Agricultural research plays vital role improving crops livestock through breeding programs good agricultural practices, enabling sustainable agriculture systems. While advanced molecular technologies have been widely adopted, phenotyping as an essential aspect of has seen little development most African institutions remains traditional method. However, concept high‐throughput (HTP) gaining momentum, particularly context unmanned aerial vehicle (UAV)‐based phenotyping. Although into UAV‐based still limited, this paper aimed provide comprehensive overview understanding use UAV platforms image analytics for HTP identify key challenges opportunities area. The discusses field concepts, classification specifications, cases phenotyping, imaging systems processing methods. more required optimize UAVs’ performance data acquisition, limited studies focused on effect operational parameters acquisition.

Language: Английский

Citations

12

Molecular mechanisms underlying plant responses to low phosphate stress and potential applications in crop improvement DOI Creative Commons
Dandan Hu, jinyu zhang, Yuming Yang

et al.

New Crops, Journal Year: 2025, Volume and Issue: unknown, P. 100064 - 100064

Published: Jan. 1, 2025

Language: Английский

Citations

1

Winter Wheat Yield Prediction Using Satellite Remote Sensing Data and Deep Learning Models DOI Creative Commons

Hongkun Fu,

Jian Lü,

Jian Li

et al.

Agronomy, Journal Year: 2025, Volume and Issue: 15(1), P. 205 - 205

Published: Jan. 16, 2025

Accurate crop yield prediction is crucial for formulating agricultural policies, guiding management, and optimizing resource allocation. This study proposes a method predicting yields in China’s major winter wheat-producing regions using MOD13A1 data deep learning model which incorporates an Improved Gray Wolf Optimization (IGWO) algorithm. By adjusting the key parameters of Convolutional Neural Network (CNN) with IGWO, accuracy significantly enhanced. Additionally, explores potential Green Normalized Difference Vegetation Index (GNDVI) prediction. The research utilizes collected from March to May between 2001 2010, encompassing vegetation indices, environmental variables, statistics. results indicate that IGWO-CNN outperforms traditional machine approaches standalone CNN models terms accuracy, achieving highest performance R2 0.7587, RMSE 593.6 kg/ha, MAE 486.5577 MAPE 11.39%. finds April optimal period early wheat. validates effectiveness combining remote sensing prediction, providing technical support precision agriculture contributing global food security sustainable development.

Language: Английский

Citations

1

Morphological characteristic extraction of unopened cotton bolls using image analysis and geometric modeling methods DOI
Rongqiao He, Pei Yang, Chao Tang

et al.

Computers and Electronics in Agriculture, Journal Year: 2025, Volume and Issue: 232, P. 110094 - 110094

Published: Feb. 17, 2025

Language: Английский

Citations

1

Enhancing citrus fruit yield investigations through flight height optimization with UAV imaging DOI Creative Commons

Soon-Hwa Kwon,

Ki Bon Ku, Anh Tuan Le

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 3, 2024

Abstract Citrus fruit yield is essential for market stability, as it allows businesses to plan production and distribution. However, estimation a complex time-consuming process that often requires large number of field samples ensure representativeness. To address this challenge, we investigated the optimal altitude unmanned aerial vehicle (UAV) imaging estimate unshiu fruit. We captured images from five different altitudes (30 m, 50 70 90 110 m), determined resolution approximately 5 pixels/cm necessary reliable size based on average diameter C. (46.7 mm). Additionally, found histogram equalization improved count compared using untreated images. At 30 m height, normal image estimates numbers 73, 55, 88. equalized 88, 71, 105. The actual fruits 124, 141. Using Vegetation Index such I PCA showed similar value equalization, but 1 represents gap yields. Our results provide valuable database future UAV investigations citrus yield. flying platforms like UAVs can step towards adopting sort model spanning ever greater regions at cheap cost, with system generating accurate in manner.

Language: Английский

Citations

8