|
|
|
|
|
Che-Hao Chang, Jason Lin, Jia-Wei Chang, Yu-Shun Huang, Ming-Hsin Lai and Yen-Jen Chang
Recently, data-driven approaches have become the dominant solution for prediction problems in agricultural industries. Several deep learning models have been applied to crop yield prediction in smart farming. In this paper, we proposed an efficient hybri...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sadia Alam Shammi, Yanbo Huang, Gary Feng, Haile Tewolde, Xin Zhang, Johnie Jenkins and Mark Shankle
The application of remote sensing, which is non-destructive and cost-efficient, has been widely used in crop monitoring and management. This study used a built-in multispectral imager on a small unmanned aerial vehicle (UAV) to capture multispectral imag...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhiyang Li, Zhigang Nie and Guang Li
One of the crucial research areas in agricultural decision-making processes is crop yield prediction. This study leverages the advantages of hybrid models to address the complex interplay of genetic, environmental, and management factors to achieve more ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Adriano Mancini, Francesco Solfanelli, Luca Coviello, Francesco Maria Martini, Serena Mandolesi and Raffaele Zanoli
Yield prediction is a crucial activity in scheduling agronomic operations and in informing the management and financial decisions of a wide range of stakeholders of the organic durum wheat supply chain. This research aims to develop a yield forecasting s...
ver más
|
|
|
|
|
|
|
|
|
|
|
Martin Kuradusenge, Eric Hitimana, Damien Hanyurwimfura, Placide Rukundo, Kambombo Mtonga, Angelique Mukasine, Claudette Uwitonze, Jackson Ngabonziza and Angelique Uwamahoro
Although agriculture remains the dominant economic activity in many countries around the world, in recent years this sector has continued to be negatively impacted by climate change leading to food insecurities. This is so because extreme weather conditi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ning Wang, Zhong Ma, Pengcheng Huo, Xi Liu, Zhao He and Kedi Lu
Crop yield prediction is essential for tasks like determining the optimal profile of crops to be planted, allocating government resources, effectively planning and preparing for aid distribution, making decisions about imports, and so on. Crop yield pred...
ver más
|
|
|
|
|
|
|
|
|
|
|
Andualem Aklilu Tesfaye, Berhan Gessesse Awoke, Tesfaye Shiferaw Sida and Daniel E. Osgood
Field-scale prediction methods that use remote sensing are significant in many global projects; however, the existing methods have several limitations. In particular, the characteristics of smallholder systems pose a unique challenge in the development o...
ver más
|
|
|
|
|
|
|
|
|
|
|
Juan J. Cubillas, María I. Ramos, Juan M. Jurado and Francisco R. Feito
Predictive systems are a crucial tool in management and decision-making in any productive sector. In the case of agriculture, it is especially interesting to have advance information on the profitability of a farm. In this sense, depending on the time of...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yanxi Zhao, Dengpan Xiao, Huizi Bai, Jianzhao Tang, De Li Liu, Yongqing Qi and Yanjun Shen
The accuracy prediction for the crop yield is conducive to the food security in regions and/or nations. To some extent, the prediction model for crop yields combining the crop mechanism model with statistical regression model (SRM) can improve the timeli...
ver más
|
|
|
|
|
|
|
|
|
|
|
Subhrajit Satpathy, Dipendra Shahi, Brayden Blanchard, Michael Pontif, Kenneth Gravois, Collins Kimbeng, Anna Hale, James Todd, Atmakuri Rao and Niranjan Baisakh
Sugarcane (Saccharum spp.) is an important perennial grass crop for both sugar and biofuel industries. The Louisiana sugarcane breeding program is focused on improving sugar yield by incrementally increasing genetic gain. With the advancement in genotypi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Abdellatif Moussaid, Sanaa El Fkihi, Yahya Zennayi, Ouiam Lahlou, Ismail Kassou, François Bourzeix, Loubna El Mansouri and Yasmina Imani
The overall goal of this study is to define an intelligent system for predicting citrus fruit yield before the harvest period. This system uses a machine learning algorithm trained on historical field data combined with spectral information extracted fro...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nari Kim, Kyung-Ja Ha, No-Wook Park, Jaeil Cho, Sungwook Hong and Yang-Won Lee
This paper compares different artificial intelligence (AI) models in order to develop the best crop yield prediction model for the Midwestern United States (US). Through experiments to examine the effects of phenology using three different periods, we se...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mohammed Baljon and Sunil Kumar Sharma
Every farmer requires access to rainfall prediction (RP) to continue their exploration of harvest yield. The proper use of water assets, the successful collection of water, and the successful pre-growth of water construction all depend on an accurate ass...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nicoleta Darra, Evangelos Anastasiou, Olga Kriezi, Erato Lazarou, Dionissios Kalivas and Spyros Fountas
Going beyond previous work, this paper presents a systematic literature review that explores the deployment of satellites, drones, and ground-based sensors for yield prediction in agriculture. It covers multiple aspects of the topic, including crop types...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yulin Shen, Benoît Mercatoris, Zhen Cao, Paul Kwan, Leifeng Guo, Hongxun Yao and Qian Cheng
Yield prediction is of great significance in agricultural production. Remote sensing technology based on unmanned aerial vehicles (UAVs) offers the capacity of non-intrusive crop yield prediction with low cost and high throughput. In this study, a winter...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhaoyang Tong, Shirui Zhang, Jingxin Yu, Xiaolong Zhang, Baijuan Wang and Wengang Zheng
The growth and yield of crops are highly dependent on irrigation. Implementing irrigation plans that are tailored to the specific water requirements of crops can enhance crop yield and improve the quality of tomatoes. The mastery and prediction of transp...
ver más
|
|
|
|
|
|
|
|
|
|
|
Md. S. Islam, Per McCord, Quentin D. Read, Lifang Qin, Alexander E. Lipka, Sushma Sood, James Todd and Marcus Olatoye
Genomic selection (GS) has been demonstrated to enhance the selection process in breeding programs. The objectives of this study were to experimentally evaluate different GS methods in sugarcane hybrids and to determine the prospect of GS in future breed...
ver más
|
|
|
|
|
|
|
|
|
|
|
Changchun Li, Yilin Wang, Chunyan Ma, Weinan Chen, Yacong Li, Jingbo Li, Fan Ding and Zhen Xiao
Crop growth and development is a dynamic and complex process, and the essence of yield formation is the continuous accumulation of photosynthetic products from multiple fertility stages. In this study, a new stacking method for integrating multiple growt...
ver más
|
|
|
|
|
|
|
|
|
|
|
Patryk Hara, Magdalena Piekutowska and Gniewko Niedbala
A sufficiently early and accurate prediction can help to steer crop yields more consciously, resulting in food security, especially with an expanding world population. Additionally, prediction related to the possibility of reducing agricultural chemistry...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ioannis E. Livieris, Spiros D. Dafnis, George K. Papadopoulos and Dionissios P. Kalivas
Cotton constitutes a significant commercial crop and a widely traded commodity around the world. The accurate prediction of its yield quantity could lead to high economic benefits for farmers as well as for the rural national economy. In this research, w...
ver más
|
|
|
|
|
|