Advances in omics technology for improving crop yield and stress resilience

Effects of marsh migration on flooding, saltwater intrusion, and crop yield in coastal agricultural land subject to storm surge inundation

Water Resources Research ◽

10.1029/2020wr028326 ◽

2020 ◽

Author(s):

Julia A. Guimond ◽

Holly A. Michael

Keyword(s):

Storm Surge ◽

Crop Yield ◽

Saltwater Intrusion ◽

Agricultural Land

Direct and Moderated Relationships Among Stress, Resilience, Neuroticism, Stigma, and PTSD

PsycEXTRA Dataset ◽

10.1037/e550282014-001 ◽

2014 ◽

Author(s):

Gabriel M. De La Rosa ◽

Scott L. Johnston ◽

Jennifer Webb-Murphy ◽

Stephanie Raducha ◽

Elizabeth Vishniak

Keyword(s):

Stress Resilience

First responder stress, resilience, and performance: A national study across first responder groups

PsycEXTRA Dataset ◽

10.1037/e577572014-179 ◽

2013 ◽

Author(s):

Bengt B. Arnetz ◽

Eamonn Arble

Keyword(s):

National Study ◽

First Responder ◽

Stress Resilience ◽

And Performance

Measuring everyday processes and mechanisms of stress resilience: Development and initial validation of the Sustainability of Living Inventory (SOLI).

Psychological Assessment ◽

10.1037/pas0000692 ◽

2019 ◽

Vol 31 (6) ◽

pp. 715-729 ◽

Cited By ~ 8

Author(s):

Wai Kai Hou ◽

Francisco Tsz Tsun Lai ◽

Clint Hougen ◽

Brian J. Hall ◽

Stevan E. Hobfoll

Keyword(s):

Stress Resilience ◽

Initial Validation

A methodology for a combined use of normalised difference vegetation index and CORINE land cover data for crop yield monitoring and forecasting. A case study on Spain

Agronomie ◽

10.1051/agro:2001111 ◽

2001 ◽

Vol 21 (1) ◽

pp. 91-111 ◽

Cited By ~ 66

Author(s):

Giampiero Genovese ◽

C. Vignolles ◽

T. Nègre ◽

G. Passera

Keyword(s):

Land Cover ◽

Crop Yield ◽

Vegetation Index ◽

Corine Land Cover ◽

Land Cover Data ◽

Combined Use ◽

Normalised Difference Vegetation Index ◽

Monitoring And Forecasting ◽

Yield Monitoring

Tolerance limits, self-understanding and stress resilience in the integrative recovery of inflammatory bowel disease (IBD)

Allgemeine Homöopathische Zeitung ◽

10.1055/s-0037-1601210 ◽

2017 ◽

Vol 262 (02) ◽

pp. 2-76

Author(s):

K Skrautvol

Keyword(s):

Inflammatory Bowel Disease ◽

Bowel Disease ◽

Tolerance Limits ◽

Stress Resilience ◽

Inflammatory Bowel

K-MEANS CLUSTERING ALGORITHM BASED CLASSIFICATION OF SOIL FERTILITY IN NORTH WEST NIGERIA

FUDMA Journal of Sciences ◽

10.33003/fjs-2020-0402-363 ◽

2020 ◽

Vol 4 (2) ◽

pp. 780-787

Author(s):

Ibrahim Hassan Hayatu ◽

Abdullahi Mohammed ◽

Barroon Ahmad Isma’eel ◽

Sahabi Yusuf Ali

Keyword(s):

Soil Fertility ◽

Crop Yield ◽

Clustering Algorithm ◽

Soil Samples ◽

North West ◽

R Programming ◽

Available Information ◽

Northwest Region ◽

The Relationship

Soil fertility determines a plant's development process that guarantees food sufficiency and the security of lives and properties through bumper harvests. The fertility of soil varies according to regions, thereby determining the type of crops to be planted. However, there is no repository or any source of information about the fertility of the soil in any region in Nigeria especially the Northwest of the country. The only available information is soil samples with their attributes which gives little or no information to the average farmer. This has affected crop yield in all the regions, more particularly the Northwest region, thus resulting in lower food production. Therefore, this study is aimed at classifying soil data based on their fertility in the Northwest region of Nigeria using R programming. Data were obtained from the department of soil science from Ahmadu Bello University, Zaria. The data contain 400 soil samples containing 13 attributes. The relationship between soil attributes was observed based on the data. K-means clustering algorithm was employed in analyzing soil fertility clusters. Four clusters were identified with cluster 1 having the highest fertility, followed by 2 and the fertility decreases with an increasing number of clusters. The identification of the most fertile clusters will guide farmers on where best to concentrate on when planting their crops in order to improve productivity and crop yield.

Evaluation of nitrogen dynamics and crop yield in a long-term tillage experiment

Cereal Research Communications ◽

10.1556/crc.35.2007.2.151 ◽

2007 ◽

Vol 35 (2) ◽

pp. 769-772 ◽

Cited By ~ 1

Author(s):

Attila Megyes ◽

Tamás Rátonyi ◽

Dénes Sulyok

Keyword(s):

Crop Yield ◽

Nitrogen Dynamics

The Influence of Botanical Composition of Pasture Agrophytocenosis on the Crop Yield of Perennial Grasses

10.15838/alt.2020.3.4.5 ◽

2020 ◽

Author(s):

Elizaveta Stolyarchuk ◽

Vera Vakhrusheva

Keyword(s):

Crop Yield ◽

Perennial Grasses ◽

Botanical Composition

Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i11.468 ◽

2017 ◽

Vol 7 (11) ◽

pp. 79

Author(s):

Sujata Mulik

Keyword(s):

Data Mining ◽

Crop Yield ◽

Crop Production ◽

Climatic Factors ◽

Crop Productivity ◽

Yield Prediction ◽

Data Mining Techniques ◽

Agriculture Sector ◽

Using Data ◽

Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction. The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops.