Results 241 to 250 of about 2,283,780 (295)

Supply Chain Innovations for Food Waste and Loss: Systematic Literature Review and Future Research Agenda

Business Strategy and the Environment, EarlyView.
ABSTRACT Food waste and loss (FWL) remains a critical challenge across food supply chains (SCs) globally, with approximately one‐third of all food produced for human consumption discarded or lost each year. This study systematically reviews how supply chain innovation (SCI) can mitigate FWL.
Ilias Vlachos
wiley   +1 more source

Electrochemical Biosensors for Oilseed Crops: Nanomaterial-Driven Detection and Smart Agriculture. [PDF]

Foods
Jiang Y, Wan K, Chen A, Tang N, Liu N, Zhang T, Xie Q, He Q.   +7 more
europepmc   +1 more source

Edge Computing-Enabled Smart Agriculture: Technical Architectures, Practical Evolution, and Bottleneck Breakthroughs. [PDF]

Sensors (Basel)
Gong R, Zhang H, Li G, He J.
europepmc   +1 more source

Cauliflower leaf diseases: A computer vision dataset for smart agriculture. [PDF]

Data Brief
Durjoy SH, Shikder ME, Shoib MMH, Bijoy MHI.   +3 more
europepmc   +1 more source

Subnational heterogeneity in climate-smart agriculture green finance and irrigation efficiency across seven African nations. [PDF]

Sci Rep
Bensadi A.
europepmc   +1 more source

Assessing gender disparities in farmers' access and use of climate-smart agriculture in Southern Tanzania. [PDF]

Discov Sustain
Nchanji EB, Ndunguru A, Kabungo C, Katunzi A, Nyamolo V, Ouya FO, Mutua M, Waswa B, Lutomia CK.   +8 more
europepmc   +1 more source

Author Correction: Interspecific competition and survival pressures in endangered Barringtonia racemosa populations of Mainland China

Scientific Reports
Fang Liang, Ju Hu, Yutong Lin, Lin Li, Yanping Yu, Bing Liu, Zongxin Meng, Zaijing Xiang, Xiaohui Tan   +8 more
doaj   +1 more source

"Smart agriculture: a climate-driven approach to modelling and forecasting fall armyworm populations in maize using machine learning algorithms". [PDF]

Front Plant Sci
Kalisetti VS, Sudharshanam U, Mallela Venkata NK, Mandla R, Akula S, Bedika M, Dharavath B, Dogga S, A RB, Javaji C.   +9 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Smart nanobiosensors in agriculture

Nature Food, 2021
Coupling micro- and nanotechnology-based diagnostics devices with machine learning would bring advantages in the food and agriculture sectors that will positively impact our planet.
openaire   +3 more sources

Smart Sensors for Smart Agriculture

2021
Agriculture is the primitive and crucial occupation for the people. Urbanization, which indirectly affected the lives of people in the agricultural sector by increasing level of environmental pollution, climate change, degradation of soil and water quality, increasing population, decreasing income from the farming industry, etc. come as a new challenge
Puja Priya, Gurjit Kaur
openaire   +1 more source