Crop Yield as Influenced by Irrigation Uniformity

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.

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Spray irrigation on dairy pastures - efficient or not?

Proceedings of the New Zealand Grassland Association ◽

10.33584/jnzg.2006.68.2656 ◽

2006 ◽

pp. 177-181

Author(s):

S.M. Thomas ◽

D. Bloomer ◽

R.J. Martin ◽

A. Horrocks

Keyword(s):

Irrigation System ◽

Groundwater Resources ◽

Dairy Farmers ◽

Large Variability ◽

Irrigation Application ◽

Irrigation Uniformity ◽

Survey Results ◽

Spray Irrigation ◽

Use Efficiency ◽

Distribution Uniformity

Applying water efficiently is increasingly important for dairy farmers and other users of surface and groundwater resources to maintain sustainable production. However, irrigation is rarely monitored. We used a questionnaire survey and measurements of five spray irrigation systems working in normal farm conditions to make observations on how efficiently irrigation is being managed. Survey results from 93 dairy farmers showed that, although the farmers believe they know how much water is being applied during irrigation, only 60% make measurements, and about 18% measure irrigation uniformity. Catch-can measurement of irrigation application depth for the different spray systems indicated large variability in application depths during irrigation, and field distribution uniformity ranged greatly between the different systems, decreasing in the order of centre pivots >travelling irrigators> K-line. Changes in irrigation system settings were sometimes made without considering application depths or uniformity. If our five case studies are typical, they may explain the large range of seasonal irrigation amounts recorded in the survey. We recommend that farmers monitor irrigation application depths and uniformity to help manage irrigation water efficiently and to help them estimate the value of irrigation to their enterprise. Keywords: distribution uniformity, water use efficiency, catch cans

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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

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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

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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.

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