Regulations imposed on the use of chemical insecticides call for the development of environmental-friendly pest management strategies. One of the most effective strategies is the push–pull system, which takes advantage of the behavioral response of the insect to the integration of repellent stimuli; it expels the pest out of the main crop (push), while attracting stimuli (attractants) pull the pest to an alternative crop or trap (pull). The objective of this study was to design a push–pull system to control Spodoptera frugiperda in maize crops (Zea mays) in Morelos, Mexico. Data on reproductive potential, larvae development, food consumption and olfactometry were used to obtain a Trap Plant Selection Index (TRAPS) based on Principal Component Analysis. This TRAPS was used to select the most suitable plants. The degree of repellency of potential plants to be used as the trap crop was studied with four-way olfactometers. S. frugiperda females oviposited more eggs on Brachiaria hybrid cv. Mulato II, Panicum maximum cv. Mombasa and Panicum maximum cv. Tanzania than on Z. mays, regardless of the fact that these plants delayed the development of their offspring. Dysphania ambrosioides, Tagetes erecta and Crotalaria juncea were less attractive to S. frugiperda females. Therefore, the former plants could be used as crop traps, and the latter as intercropped repellent plants in a push–pull system.

Chemical control is the main method used to combat fall armyworm in maize crops. However, its indiscriminate use usually leads to a more complex scenario characterized by loss of its effectiveness due to the development of resistance of the insect pest, emergence of secondary pests, and reduction of the populations of natural enemies. For this reason, efforts to develop strategies for agroecological pest management such as Push–Pull are increasingly growing. In this context, the present study was carried out to evaluate field effectiveness of Push–Pull systems for S. frugiperda management in maize crops in Morelos, Mexico. In a randomized block experiment, the incidence and severity of S. frugiperda, the development and yield of maize were evaluated in nine Push–Pull systems and a maize monoculture. The Push–Pull systems presented incidence/severity values lower than those of the monoculture. Morphological development and maize yield in the latter were lower than those of most Push–Pull systems. Mombasa—D. ambrosioides, Mulato II—T. erecta, Mulato II—C. juncea, Tanzania—T. erecta and Tanzania—D. ambrosioides systems presented higher yields than those of monocultures.

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The objective of this study was to obtain regression equations and artificial neural networks (ANNs) for prediction and prognosis of the yield of Pinus caribaea var. caribaea Barrett & Golfari. The data used for modeling comes from measuring the variables diameter at breast height (DBH) and total height (Ht) in 550 temporary plots and 14 circular permanent plots with 500 m 2 in Pinus caribaea var. caribaea plantations, aged between 3 and 41 years old. In growth prediction, the results indicated Schumacher model as the best fit to the data. On prognosis, the modified Buckman system was better than Clutter's. ANNs presented a similar performance to the Buckman model in volume prognosis, however these were superior for basal area prognosis.