Determining Suitable Shade Trees, Panting Pattern and Spacing for Arabica Coffee Production in South and Southwestern Ethiopia

In an attempt to determine suitable shade trees, planting pattern and optimum population density that promote productivity of Arabica coffee, two separate field experiments were carried out in south and south western coffee growing tracts of Ethiopia. In experiment one, seeds of thirteen shade trees were collected and established at Jimma Agricultural Research Center. Coffee berry disease resistant cultivar was stripe planted and intercropped with the shade trees in split-plot design with three replications, where shade trees and planting patterns assigned as main- and sub-plot, respectively. In experiment two, prominent shade trees were established at Gera Agricultural Research Sub-center and Metu and Wenago trial sites. The trial was laid out in split-plot design with three replicates, where shade trees and spacing between coffee trees assigned in the respective main and sub-plots. The results depicted that shade trees significantly (P < 0.05) affected coffee yield. The highest yield was noted for coffee trees planted under Millettia ferruginea, Albizia maronguensis, Acacia abyssinica, Albizia tanganica, Erythrina abyssinica, Calpurnea subdecondra and Cordia africana. The trees produced 1240 - 4512 kg ha-1 annum-1 litter fall and intercept 26 - 60% light intensity. Besides, the shade trees have mean canopy diameter ranged between 6 m * 6 m to 20 m * 20 m. Stripped plots significantly (P < 0.05) out yielded intercropped plots by 20.40%. In the overall year mean coffee population density of 5917, 3906 and 5102 trees ha-1 gave the highest yield at Gera, Metu and Wenago, respectively. It is, therefore, concluded that productivity of coffee trees can be improved by planting at its optimum population density in strip between the aforementioned prominent shade trees. However, investigation should continue to evaluate the effect of the shade trees on the row and liquor quality of coffee, smothering of weed growth, plant nutrient supply, soil moisture dynamics and physico-chemical properties of soil in major coffee growing areas of the country. Keywords: Arabica coffee, intercropped, planting pattern, spacing, shade trees, stripped 

Drawing Binary Tanglegrams: An Experimental Evaluation

A binary tanglegram is a pair of binary trees whose leaf sets are in one-to-one correspondence; matching leaves are connected by inter-tree edges. For applications, for example in phylogenetics or software engineering, it is required that the individual trees are drawn crossing-free. A natural optimization problem, denoted tanglegram layout problem, is thus to minimize the number of crossings between inter-tree edges. The tanglegram layout problem is NP-hard and is currently considered both in application domains and theory. In this paper we present an experimental comparison of a recursive algorithm of Buchin et al., our variant of their algorithm, the algorithm hierarchy sort of Holten and van Wijk, and an integer quadratic program that yields optimal solutions.Comment: see http://www.siam.org/proceedings/alenex/2009/alx09_011_nollenburgm.pd

Optimal Sparse Decision Trees

Decision tree algorithms have been among the most popular algorithms for interpretable (transparent) machine learning since the early 1980's. The problem that has plagued decision tree algorithms since their inception is their lack of optimality, or lack of guarantees of closeness to optimality: decision tree algorithms are often greedy or myopic, and sometimes produce unquestionably suboptimal models. Hardness of decision tree optimization is both a theoretical and practical obstacle, and even careful mathematical programming approaches have not been able to solve these problems efficiently. This work introduces the first practical algorithm for optimal decision trees for binary variables. The algorithm is a co-design of analytical bounds that reduce the search space and modern systems techniques, including data structures and a custom bit-vector library. Our experiments highlight advantages in scalability, speed, and proof of optimality.Comment: 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canad

Boosted Decision Trees as an Alternative to Artificial Neural Networks for Particle Identification

The efficacy of particle identification is compared using artificial neutral networks and boosted decision trees. The comparison is performed in the context of the MiniBooNE, an experiment at Fermilab searching for neutrino oscillations. Based on studies of Monte Carlo samples of simulated data, particle identification with boosting algorithms has better performance than that with artificial neural networks for the MiniBooNE experiment. Although the tests in this paper were for one experiment, it is expected that boosting algorithms will find wide application in physics.Comment: 6 pages, 5 figures; Accepted for publication in Nucl. Inst. & Meth.

Stomatal Conductance and Chlorophyll Characteristics and Their Relationship with Yield of Some Cocoa Clones Under Tectona Grandis, Leucaena SP., and Cassia Surattensis.

An optimum physiological condition will support high yield and quality of cocoa production. The research was aimed to study the effects of stomatal conductance and chlorophyll content related to cocoa production under three shade regimes.This research was conducted in Kaliwining Experimental Station, elevation of 45 m above sea level with D climate type based on Schmidt & Fergusson. Cocoa trees which were planted in 1994 at a spacing of 3 X 3 m were used in the study planted by using split plot design. The shade tree species were teak (Tectona grandis), krete (Cassiasurattensis), and lamtoro (Leucaena sp.) as the main plots, and cocoa clones of Sulawesi 01,Sulawesi 02, KKM 22 and KW 165 as sub plots. This study showed that there was interaction between cocoa clone and shade species for stomatal conductance where stomatal diffusive resistance of KKM 22 was the best under Leucaena sp.and Cassiasurattensis with the values of 1.38 and 1.34 s.cm -1, respectively. The highest chlorophyll content, stomatal index and transpiration values was under Leucaena sp. shade. There was positive correlation between chlorophyll content and transpiration with pod yield of cocoa. The highest yield and the lowest bean count wereobtainedon Sulawesi 01 clone under Leucaenasp. shade