219   Artículos

 
en línea
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
Revista: Agriculture    Formato: Electrónico

 
en línea
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
Revista: Agronomy    Formato: Electrónico

 
en línea
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
Revista: Agronomy    Formato: Electrónico

 
en línea
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
Revista: Agronomy    Formato: Electrónico

 
en línea
Zihao Zhu and Yonghua Xie    
Black soil plays an important role in maintaining a healthy ecosystem, promoting high-yield and efficient agricultural production, and conserving soil resources. In this paper, a typical black soil area of Keshan Farm in Qiqihar City, Heilongjiang Provin... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Lei Sun, Chongchong Yang, Jun Wang, Xiwen Cui, Xuesong Suo, Xiaofei Fan, Pengtao Ji, Liang Gao and Yuechen Zhang    
Existing maize production is grappling with the hurdles of not applying nitrogen fertilizer accurately due to subpar detection accuracy and responsiveness. This situation presents a significant challenge, as it has the potential to impact the optimal yie... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Li Sun, Jingfa Yao, Hongbo Cao, Haijiang Chen and Guifa Teng    
In agricultural production, rapid and accurate detection of peach blossom bloom plays a crucial role in yield prediction, and is the foundation for automatic thinning. The currently available manual operation-based detection and counting methods are extr... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Jiaqiang Wang, Caiyun Yin, Weiyang Liu, Wenhao Xia and Songrui Ning    
Soil salinity affects nutrient uptake by cotton. The cotton bud stage is a very important period in the process of cotton planting and directly affects the yield of cotton. The nutritional status of the bud stage directly affects the reflectance spectra ... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Qingyan Wang, Longzhi Sun and Xuan Yang    
Rice yield is essential to global food security under increasingly frequent and severe climate change events. Spatial analysis of rice yields becomes more critical for regional action to ensure yields and reduce climate impacts. However, the understandin... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
Zeqin Tian, Dengfeng Chen and Liang Zhao    
Accurate building energy consumption prediction is a crucial condition for the sustainable development of building energy management systems. However, the highly nonlinear nature of data and complex influencing factors in the energy consumption of large ... ver más
Revista: Applied Sciences    Formato: Electrónico

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