Foliar Analysis as a Guide to NPK Nutrition of Pineapples in the Forest Zone of Ghana

SUMMARYIn a 20 plot experiment with central composite second-order rotatable design, basal non-chlorophyllous sections of “D” leaves of Sugarloaf pineapples were sampled at harvest and analysed for N, P, K. Maximum yield of 17·8 tons per acre of good quality Sugarloaf pineapples and maximum fruit length of 27·4 cm. were associated with the nutrient combination of 36–42–32 lb/acre N P K applied at 4, 6, 11 and 12 months. The nutrient levels in the basal sections of “D” leaves corresponding to maximum fruit yield were 0·35–0·40% N; 0·04% P; 0·44% K; K/P 11·2–11·5: 1. K/P ratio for maximum fruit length was 10·4–11·5: 1. N/K ratio was associated with lodging.

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Modeling of rose coco beans using twenty four points optimum second order rotatable design

International Journal of Advanced Statistics and Probability ◽

10.14419/ijasp.v5i2.8445 ◽

2017 ◽

Vol 5 (2) ◽

pp. 96

Author(s):

Isaac Tum ◽

John Mutiso ◽

Joseph Koske

Keyword(s):

Response Surface ◽

Maximum Yield ◽

Second Order ◽

Three Dimensions ◽

Coefficient Of Determination ◽

Yield Response ◽

Efficient Production ◽

Phosphorus And Potassium ◽

Nitrogen Phosphorus ◽

Rotatable Design

The response surface methodology (RSM) is a collection of mathematical and statistical techniques useful for the modeling and analysis of problems in which a response of interest is influenced by several variables, and the objective is to optimize the response. The objective of the study was to model the rose coco beans (Phaseolus vulgaris) through an existing A-optimum and D-efficient second order rotatable design of twenty four points in three dimensions in a greenhouse setting using three inorganic fertilizers, namely, nitrogen, phosphorus and potassium. Thus, the objective of the study was accomplished using the calculus optimum value of the free/letter parameter f=1.1072569. This was done by estimating the parameters via least square's techniques, by making available for the yield response of rose coco beans at calculus optimum value design for the first time. The results showed that, the three factors: nitrogen, phosphorus, and potassium contributed significantly on the yield of rose coco beans (p<0.05). In GP3G, the second-order model was adequate for 1% level of significance with p value of 0.0034. The analysis of variance (ANOVA) of response surface for rose coco yield showed that this design was adequate due to satisfactory level of a coefficient of determination, R2, 0.8066 and coefficient variation, CV was 10.30. This study demonstrated the importance of statistical methods in the optimal and efficient production of rose coco beans. We do recommend a randomize screening of all the fertilizer components with which it has influence on rose coco beans be done to ascertain the right initial amount of each fertilizer that could achieve maximum yield than this study realized.

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Optimal and efficient production of rose coco beans through the twenty-four points second order rotatable design

International Journal of Advanced Statistics and Probability ◽

10.14419/ijasp.v6i1.8552 ◽

2017 ◽

Vol 6 (1) ◽

pp. 1

Author(s):

Isaac Tum ◽

Joseph Koske ◽

John Mutiso

Keyword(s):

Response Surface ◽

Maximum Yield ◽

Response Surfaces ◽

Second Order ◽

Three Dimensions ◽

Coefficient Of Determination ◽

Efficient Production ◽

Phosphorus And Potassium ◽

Nitrogen Phosphorus ◽

Rotatable Design

The yield results of the twenty four points response surface methodology (RSM) design permitted a response surface to be fitted easily and provided spherical information contours besides the realizations of an optimum combination of the fertilizers in rose coco beans, which resulted in economic use of scarce resources for optimal production of rose coco beans. In this study an existing A-optimum and D-efficient second order rotatable design in three dimensions was used to produce rose coco beans optimally and efficiently. The general objective of the study was to produce rose coco beans (Phaseolus vulgaris) optimally and efficiently using an existing A-optimum and D-efficient twenty four points second order rotatable design in three dimensions in a greenhouse setting using three inorganic fertilizers, namely, nitrogen, phosphorus and potassium. Thus the study was accomplished using the calculus optimum value of the free/letter parameter f=1.1072569. The specific objectives were to estimate the linear parameters, thereby making available for the yield response of rose coco beans at calculus optimum value design for the first time, fitted and tested the model adequacy via lack of fit test, and then found the setting of the experimental factors that produces optimal response using contour plots to assist visualizes the response surfaces. This study demonstrated the importance of statistical methods in the optimal and efficient production of rose coco beans. The results showed that the three factors: nitrogen, phosphorus, and potassium contributed significantly on the yield of rose coco beans (p<0.05). The regression coefficients were determined by employing least square's techniques to predict quadratic polynomial model for group 3 greenhouse (GP3G) for the three fertilizer combinations. In GP3G, the second-order model was adequate at 1% level of significance with a p-value of 0.0034. The analysis of variance (ANOVA) of response surface for rose coco yield showed that this design was adequate due to satisfactory level of a coefficient of determination, R2, 0.8066 (GP3G) and coefficient variation, CV was 10.30. The canonical analysis showed that there was the saddle point for GP3G, meaning there was no unique optimum; therefore, ridge analysis was used to overcome the saddle problem. The result from ridge analysis provided the maximum yield of 70.25grams for the three fertilizer combinations at radii of one. We, therefore, recommend the use of GP3G design since it gave the required coefficient of determination (R2=80.66) and the maximum yield (70. 25grams) was achieved.

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Effects of Indigenous Mulches on Growth and Yield of Tomato

Journal of Agriculture & Rural Development ◽

10.3329/jard.v6i1.1650 ◽

1970 ◽

Vol 6 (1) ◽

pp. 1-6 ◽

Cited By ~ 2

Author(s):

MA Kayum ◽

M Asaduzzaman ◽

MZ Haque

Keyword(s):

Yield Components ◽

Water Hyacinth ◽

Significant Variation ◽

Maximum Yield ◽

Growth Yield ◽

Fruit Yield ◽

Growth And Yield ◽

Rainfed Condition ◽

Tomato Yield ◽

Banana Leaf

Three popular tomato varieties namely, Ratan, BARI tomato-3 and BARI tomato-6 were experimentally evaluated to identify the potential mulch on growth and yield, where the experiment consisted of four mulching treatments viz. water hyacinth, straw, am-ada leaf and banana leaf with a control (no mulch). The experiment was conducted under rainfed condition. In the experiment, mulching showed significant effect on growth, yield components and thus on the yield of tomato. Yield contributing characters were significantly higher when water hyacinth mulch was used. The variety Ratan produced the highest (53.74 t/ha) fruit yield, while BARI tomato-3 showed the lowest (48.89 t/ha) fruit yield. The combination of mulching and variety exhibited significant variation in some yield components and yield. The combination of water hyacinth and Ratan produced the maximum yield (62.16 t/ha) and thus the experiment revealed that water hyacinth and straw mulches have potentiality to increase the yield of tomato. Key words: Indigenous mulch, growth, yield, tomato.doi:10.3329/jard.v6i1.1650 J Agric Rural Dev 6(1&2), 1-6, June 2008

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OPTIMIZING THE PROCESS OF TRANSFORMING COFFEE HUSKS INTO BIOCHAR BY MEANS OF HYDROTHERMAL CARBONIZATION

Vietnam Journal of Science and Technology ◽

10.15625/2525-2518/54/4b/12034 ◽

2018 ◽

Vol 54 (4B) ◽

pp. 138

Author(s):

Tran Thi Hien

Keyword(s):

Maximum Yield ◽

Hydrothermal Carbonization ◽

Optimal Conditions ◽

Coffee Husk ◽

Optimal Value ◽

Face Centered ◽

Composite Face ◽

Temperature Time ◽

Central Composite ◽

Water Ratio

The conditions of the hydrothermal carbonization process to produce biochar from coffee husk will be optimized for maximum yield. Besides, response surface methodology (RSM) and central composite face-centered (CCF) method will be used in designing experiments. Also, the optimal value of factors such as temperature, time and biomass: water ratio which can provide a maximum yield of biochar will be worked out using Modde 5.0. As a result, the optimal conditions for maximum yield of biochar was obtained as temperature of 180 oC, 3.5 h and biomass: water ratio of 15 %. It can also be concluded that temperature has greater impact on the transformation of biochar than time and biomass: water ratio.

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The D-, A-, E- and T-optimal Values of a Second Order Rotatable Design in Four Dimension Constructed Using Balanced Incomplete Block Designs

American Journal of Applied Mathematics ◽

10.11648/j.ajam.20200803.12 ◽

2020 ◽

Vol 8 (3) ◽

pp. 83

Author(s):

Kabue Timothy Gichuki ◽

Koske Joseph ◽

Mutiso John

Keyword(s):

Second Order ◽

Block Designs ◽

Incomplete Block ◽

Balanced Incomplete Block Designs ◽

Optimal Values ◽

Balanced Incomplete Block ◽

Rotatable Design

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Assessment of wild tomato accessions for fruit yield, physicochemical and nutritional properties under a rain forest agro-ecology

Genetic Resources ◽

10.46265/genresj.bjcv8100 ◽

2020 ◽

Vol 1 (2) ◽

pp. 1-11

Author(s):

Dorcas Ibitoye ◽

Adesike Kolawole ◽

Roseline Feyisola

Keyword(s):

Rain Forest ◽

Agronomic Traits ◽

Block Design ◽

Principal Component ◽

Fruit Yield ◽

Soluble Solids ◽

Forest Zone ◽

Breeding Lines ◽

Wild Tomato ◽

Solanum Lycopersicum L

Tomato (Solanum lycopersicum L.) is a broadly consumed fruit vegetable globally. It is one of the research mandate vegetable of the National Horticultural Research Institute (NIHORT), Ibadan, Nigeria. The institute’s contains diverse collections of tomato accessions and wild relatives, without utilization information for the African continent. With the decline in diversity and potential of cultivars, a robust tomato breeding pipeline with broad genetic base that eliminates redundancy in the development of lines with desired horticultural traits is paramount. This study evaluated the mean performance and variations of thirteen wild tomato accessions obtained from the C.M. Rick Tomato Genetic Resource Center, University of California, Davis, USA, evaluated for agronomic, nutritional and physicochemical traits under a rain forest zone in Nigeria. The accessions were planted and grown in three replications with randomized complete block design. Agronomic traits, physicochemical and nutritional parameters were measured and analyzed. There was significant (P < 0.001) variation among accessions for all traits measured. Accession LA0130 was separated from others by cluster analysis and was outstanding for its unique attributes which include: fruit yield parameters, total soluble solids, acidity and content. The principal component analysis suggests fruit yield related traits, acidity and contributed most to the variation among the 13 accessions. The results obtained can be used to breed materials adapted to a rain forest . These wild tomato accessions have genes with desirable agronomic, nutritional and physicochemical traits that could be into breeding lines to improve commercial tomato varieties.

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Central Composite Design and Desirability of RSM for Optimization of Biodiesel Production from Mixture of Animal Waste Fat Oil and used Cooking Oil

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.d1724.029420 ◽

2020 ◽

Vol 9 (4) ◽

pp. 1565-1571

Keyword(s):

Reaction Time ◽

Sodium Hydroxide ◽

Maximum Yield ◽

Animal Waste ◽

Sodium Hydroxide Concentration ◽

Used Cooking Oil ◽

Input Parameters ◽

Desirability Approach ◽

Central Composite ◽

Waste Fat

In this work, central composite design(CCD) and desirability approach of Response surface methodology (RSM) has been used for optimization of biodiesel yield produced from mixture of animal waste fat oil and used cooking oil (AWO) in the ratio of 1:1through alkaline transesterification process. In this work, methanol quantity, reaction time and sodium hydroxide concentration are selected as input parameters and yield selected as response. The combined effect of methanol quantity, reaction time and sodium hydroxide concentration were investigated and optimized by using RSM. The second order model is generated to predict yield as a function of methanol quantity, reaction time and sodium hydroxide concentration. A statistical model predicted the maximum yield of 96.9779% at 35ml methanol quantity (% v/v of oil), 75 min. reaction time and 0.6g (% wt./v of oil) of sodium hydroxide. Experimentally, the maximum yield of 97% was obtained at the above optimized input parameters. The variation of 0.02% was observed between experimental and predicted values. In this work, an attempt has also made to use desirability approach of RSM to optimize the input parameters to predict maximum yield. Desirability approach predicts maximum yield (97.075%) at CH3OH (35.832% vol. /vol. of oil), NaOH (0.604 % wt./vol. of oil) and reaction time (79.054min.) was found for the AWO.

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Selection of Second Order Models’ Design Using D-, A-, E-, T- Optimality Criteria

Asian Journal of Probability and Statistics ◽

10.9734/ajpas/2019/v5i230134 ◽

2019 ◽

pp. 1-15

Author(s):

Wangui Patrick Mwangi ◽

Ayubu Anapapa ◽

Argwings Otieno

Keyword(s):

Optimality Criteria ◽

Second Order ◽

Factorial Designs ◽

Economical Design ◽

Wide Range ◽

Eigen Value ◽

Average Variance ◽

Rsm Technique ◽

Central Composite ◽

Selection Of

There are numerous designs for fitting second order models that can be used in conjunction with the response surface methodology (RSM) technique in optimization processes, be it in agriculture, industries and so on. Some of the designs include the equiradial, Notz, San Cristobal, Koshal, Hoke, Central Composite and Factorial designs. However, RSM can only be applied in conjunction with a single design at a time. This research aimed at choosing a design out of the most widely employed designs for fitting 2nd order models involving 3 factors for optimization of French beans in conjunction with the RSM technique. The most commonly used designs for second order models were first identified as Box-Behnken designs, Hoke D2 and Hoke D6 designs, 3k factorial designs, CCD face centred, CCD rotatable and CCD spherical. Design matrices for these 7 designs were formed and augmented with 5 centre points (chosen through lottery methods), and information and optimal design matrices were formed. Then, for each design, the analysis of D-, A- E-, T- optimality (D-Determinant, A-Average Variance, E-Eigen Value and T-Trace) was carried out according to Pukelsheim’s definitions. The results were ranked for each criterion and the ranks corresponding to each design were averaged. The design chosen was Hoke D2 with the least average- 1.75. The Hoke D2 was found to be optimal in minimizing the variance of prediction and the most economical design among the seven. The findings are in agreement with other researchers and scientist that a design may be optimal in one criterion but fails in another criterion. Further, Hoke designs are in the class of the economical designs. It is recommended that more optimality criteria be applied and a wide range of designs be involved to see whether the results would still agree with these findings.

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