TAILIEUCHUNG - Utilization of color parameters to estimate moisture content and nutrient levels of peanut leaves

Leaf nutrient levels are traditionally quantified by laboratory chemical analysis, which is time-consuming and requires intensive labor and investment. The objective of this study was to predict the moisture content (MC) and nutrient content of peanut leaves from color parameters (CIE Lab) using a chromameter. | Turkish Journal of Agriculture and Forestry Turk J Agric For (2013) 37: 604-612 © TÜBİTAK doi: Research Article Utilization of color parameters to estimate moisture content and nutrient levels of peanut leaves 1 2 1, 1 Muharrem KESKİN , Sema KARANLIK , Serap GÖRÜCÜ KESKİN *, Yurtsever SOYSAL Department of Biosystems Engineering, Faculty of Agriculture, Mustafa Kemal University, Antakya, Hatay, Turkey 2 Department of Soil Science and Plant Nutrition, Faculty of Agriculture, Mustafa Kemal University, Antakya, Hatay, Turkey 1 Received: Accepted: Published Online: Printed: Abstract: Leaf nutrient levels are traditionally quantified by laboratory chemical analysis, which is time-consuming and requires intensive labor and investment. The objective of this study was to predict the moisture content (MC) and nutrient content of peanut leaves from color parameters (CIE Lab) using a chromameter. This method is faster and requires less labor and investment compared to laboratory chemical analysis. Fifty peanut leaf samples were collected from a commercial peanut field. The samples were analyzed for MC, N, P, K, Ca, Mg, Fe, Mn, Zn, and Cu concentrations after color parameters were acquired by chromameter. A positive and high correlation was found between MC and brightness (L*; r = ) and MC and yellowness (b*; r = ). The results show the possibility of predicting the MC of peanut leaves from color data (R2 = ). A strong relationship was also observed between the measured and predicted levels of P and K based on the PLS2 regression model (R2 = and R2 = , respectively). P and K concentrations of peanut leaves can be predicted from the color parameters to within approximately ± and ±, respectively. In contrast to MC, P, and K, concentrations of N, Mg, Mn, Zn, and Cu had only moderate correlation, and Fe concentration had the lowest .

• Nông nghiệp
• Leaf nutrient
• Laboratory chemical analysis
• Moisture content
• Peanut Arachis hypogaea L
• Color parameters
• Nitrogen and leaf nutrient
• Rejuvenation pruning
• Nitrogen levels on leaf nutrient status
• Senile apricot (Prunus armeniaca L
• Available nutrient
• Groundnut growing soils
• Srikalahasti division
• Leaf nutrient of groundnut growing soils
• Seasonal variation
• Leaf index tissue
• Sampling date
• Indexing of pear leaf
• Leaf mineral nutrient
• Calcium ammonium nitrate
• Yield and leaf nutrient
• Micro nutrient content in leaf
• Production potential of guava
• Influenced by nitrogen
• Boron levels
• Mandarin orange
• Micro nutrients
• Foliar application
• Leaf nutrient status
• Leaf micro nutrient status
• Byadgi chilli
• Index leaf
• Preliminary leaf nutrient norms
• Byadgi chilli (Capsicum annuum L )
• DRIS approach
• Water relations
• Nutrient uptake
• Temperate fruits
• Temperate fruit crops
• Hoagland solutions
• Solution culture
• Nutrient content
• Leaf tissue concentration
• Nutrient deficiencies
• Gerbera var savannah
• Diatomaceous earth
• Macro nutrient
• Leaf nutrient status of Guava
• Source of silicon
• Response of soil application
• Soil application of diatomaceous earth
• Leaf and fruit nutrients
• Soil microbial population
• Aonla (Emblica officinalis Gaertn
• Integrated nutrient management strategies
• Nutrient status
• Budload and fertilizer application
• Leaf petiole
• Fruit nutrient status
• Grape cv Sahebi
• Model grapevine orchard
• Calcium nitrate
• Colour value
• Byadgi chilli (Capsicum annuum L
• Calcium nitrate foliar application
• Index leaf nutrient concentration yield
• Crassocephalum crepidioides leaf meal
• Labeo rohita
• Indigenous knowledge
• Nutrient utilisation
• Labeo rohita Fingerlings
• Growth and yield attributes
• Economics of sericulture
• Silkworm (Bombyx mori L )
• Different pruning techniques
• Integrated nutrient management on growth
• Leaf yield of mulberry
• Available nitrogen
• Pomegranate fruit yield
• Pomegranate yield
• Leaf major nutrient status
• Relation with pomegranate yield
• Bitter almond
• Wild peach
• Soil moisture tension
• Stomatal conductance
• Zinc sulphate
• Pant prabhat and ZnSO4
• Zinc sulphate on vegetative growth
• Yield of guava
• Yellow leaf disease (YLD)
• Macro and micro nutrient
• Qualitative and quantitative traits
• Quantitative traits
• Yellow leaf disease
• Leaf fall
• Organic manures
• Inorganic fertilizers
• Soybean yield
• Nutrient content and uptake
• Leaf analysis
• Secondary nutrient
• Temporal and axial variation
• Correlation coefficient
• Leaves of litchi
• Secondary nutrient concentrations
• Dry direct seeded rice
• Nutrient management
• Leaf colour chart
• Ricechickpea cropping system
• Seed yield
• Net return
• Integrated nutrient mangment
• Integrated nutrient management
• Farmyard manure
• Green leaf manure
• Poultry manure
• Rice under integrated nutrient management
• Plant Biology
• Nutrient retranslocation
• Temperate desert
• Leaf traits
• Nutrient cycling
• Sodium tress
• Vaccinium arctostaphylos L
• Vaccinium myrtillus L
• Specific leaf area
• Leaf mass per area
• Walkley–Black method
• Light and nutrition
• Radial growth
• Dry mycelial weight
• Bipolaris oryzae
• Brown leaf spot of paddy
• Brown colored conidia