Marahaini Nizar

Marahaini Nizar
Crops For the Future Research Centre · Knowledge Systems

BSc (Hons) Biotechnology

About

12
Publications
11,889
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40
Citations
Introduction
Database design and development - Data management and data curation - Data visualisation - Plant nutritional composition - Underutilised crops market accessibility research
Additional affiliations
November 2016 - May 2020
Crops for the Future Research Centre
Position
  • Executive
Education
July 2011 - July 2015

Publications

Publications (12)
Article
Full-text available
While China has transformed its economy over recent decades, challenges such as climate change and land degradation have continued to impact its agriculture. These effects along with changes in diets and growing food imports will force China to look for alternative cropping options. Despite the broad potential of Bambara groundnut (Vigna subterrane...
Article
Full-text available
Following the development of a database that was specifically designed to store value chain information, particularly for underutilised crops, this article describes the data that are currently stored in the database and accessible through the web portal. The data includes various datasets on utilisation status, agro-ecological requirements and sea...
Article
Full-text available
The diverse underutilised crops of Malaysia are a largely unexplored potential source of food and nutritional security. This study investigated Pouteria campechiana (Kunth) Baehni, which is considered as a rare underutilised crop found locally. The yellow pulp fruit is commonly known as canistel or "kuning telur" by the local population. The fruits...
Article
Full-text available
We investigated the macronutrient, selected mineral and fatty acid composition of Sacha inchi (SI) (Plukenetia volubikis L.) seeds harvested from the grounds of Crops Future, Malaysia. Macronutrient analysis was carried out on both fresh and roasted (160°C for 6 mins) SI seeds. Both fresh and roasted seeds were rich in crude fat (56.2%, 49.8%) and...
Article
Full-text available
Plectranthus rotundifolius (synonym: Solenostemon rotundifolius) (black potato) is an underutilised nutrient-rich crop that has the potential to contribute to food and nutritional security. We examined the macronutrient and selected mineral content of black potato bought at a morning market located in the state of Pahang, Peninsular Malaysia. The p...
Article
Full-text available
Soil data for Sri Lanka are available through semi-detailed series maps that were developed based on limited soil profile data combined with expert knowledge. This data plays a vital role in decisions at national and regional levels. However, the present format of this database does not allow for their wider use in crop simulation modelling and oth...
Article
Full-text available
In this experiment, proximal measurements and Unmanned Aerial Vehicle (UAV) imagery was used to determine growth stages for bambara groundnut (Vigna subterranea (L.) Verdc.). The crop is a high potential crop due to its ability to yield in marginal environments, but neglected and underutilised due to lack of information on its growth in different e...
Article
Full-text available
Shortlisting ecologically adaptable plant species can be a starting point for agricultural diversification projects. We propose a rapid assessment framework based on an ecological model that can accelerate the evaluation of options for sustainable crop diversification. To test the new model, expert-defined and widely available crop requirement data...
Conference Paper
Full-text available
Word embeddings are numerical distributed word representations that have recently sparked significant interest in the research community. They are used by Google and Facebook corporations in various applications such as enhancing search and recommendation engines. Many word embedding techniques such as word2vec, doc2vec, glove, BERT, RoBERT and oth...
Conference Paper
Bambara groundnut (Vigna Subterranea L.Verdc.) is a high potential indigenous legume with origins from Sub-Saharan Africa. Desirable characteristics such as high tolerance to drought, and a more complete nutritional profile nutritional profile has made this legume, a candidate underutilised crop. Underutilised or forgotten crops play an important r...
Presentation
Full-text available
Assessment of land capability for a crop requires the bringing together of data on soils, climates and crop requirements. In Malaysia, the main method to identify suitable species for agriculture is soil-crop suitability classification based on a range of soil properties that can impose limits on crop growth. This method has been used widely by gov...

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Projects

Projects (3)
Project
he database is designed to store data on all aspects of crops from their genetic and genomics to agronomic requirements, ecological conditions, statistics about their production and usage, nutritional aspects, food and products that are made and socio-economic survey data on growing and consumption of crops. The relational format contains about 4000 variables that are organised in 330 relational tables. Each piece of data has a dedicated metadata table based on extended Dublin core metadata schema to store the source of data, accuracy flag (green, amber and red) and geographic location (with Google places ID) of that data if it is available. The database has an online data manager based on SQL Maestro technology that makes editing and modifying the data by non-expert much easier (www.cropbase.org).
Project
CROPSWAP project and app is about using SELECTCROP algorithm in ascertaining the likely impact of change on crop suitability. CROPSWAP visualises the resilience of crops and cropping systems for now compared to the likely change in temperature and rainfall. For now the system is only using the climate variables but by extending the complexity of the algorithm that was developed in SELECTCROP project, it will accept more inputs including soil fertility levels as well impact of socio-economic variables such market value and so on.
Project
SELECTCROP combines location-based climate and soil data to shortlist crop using a physically based model. The main model used only climate variables the algorithm were then extended to include soil variables. The algorithm is written in R statistical language and uses available global climate and soil datasets and APIs to shortlist the crops for decision making regarding agricultural diversification.