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Soybean bugs are major crop pests that cause significant reduction in harvest yield and influence grain quality. The aim of this study was to verify the spatial distribution of Euschistus heros (F.) (Hemiptera: Pentatomidae) in conventional and transgenic soybean cultivars. The experiment was conducted during the 2010-2011 crop season in UNESP/FCAV, Jaboticabal, SP, Brazil, in two fields of 10,000-m(2) area that were subdivided into 100 plots (10 m × 10 m). The cultivars sown were M 7908 RR and its isoline M-SOY 8001. The number of the first to fifth instars and the number of adults were determined. To evaluate insect dispersion in the area, the following indices were used: variance/mean ratio, Morisita index, Green coefficient, and the k exponent of the negative binomial distribution. To study probabilistic models to describe the spatial distribution of the insects, the adjustments of the Poisson and negative binomial distributions were tested. The first to third instars showed aggregated spatial distribution, whereas the fourth and fifth instars, and adults, isolated or grouped, showed variation in the arrangement, ranging from moderately aggregated to randomly dispersed. During the adjustment of probability distributions, the negative binomial distribution model showed adjustment for the first to third instars, fourth and fifth instars, adults, and fourth and fifth instars plus adults.

Huanglongbing (HLB) is the most devastating disease of citrus worldwide. It is caused by bacteria of the genus 'Candidatus Liberibacter' and transmitted by two psyllid species, the Asian citrus psyllid (ACP) Diaphorina citri, and the African citrus psyllid Trioza erytreae. Considerable research has been conducted toward developing and implementing HLB and ACP management strategies. With respect to ACP control, of interest is that reports indicate guava, Psidium guajava, can be repellent to ACP. We conducted research to further evaluate repellency of guava to ACP. In one set of experiments, guava oil from five Brazilian guava cultivars ('J3', 'Pedro Sato', 'Século XXI', 'Thailand' and 'Paluma') was extracted from leaves (immature and mature) by hydrodistillation in a Clevenger-type apparatus and evaluated for psyllid repellency. In a second set of experiments, repellency of guava leaves to ACP was investigated using leaves (immature and mature) from two guava cultivars in Florida, 'Pink' and 'Thai White'. In each set of experiments, repellency was evaluated by releasing ACP adults into a cage with two large vials, one containing a young flush shoot (= immature leaves) of Murraya exotica (a favored host plant of the psyllid, the flush of which is highly attractive to ACP) and one with M. exotica flush and the test material of interest (guava oil, immature guava leaf or mature guava leaf). The adults were free to move throughout the cage and into the vials, and the number of psyllids in each vial was counted after 24 h. The results showed that all guava materials tested had at least some repellency to ACP. Mature leaves tended to have a greater repellent effect than immature leaves. Each of the five oils exhibited repellency. A report in the literature suggested that sulfur compounds associated with guava may be responsible for ACP repellency. Interestingly, the five guava oil extracts we studied were repellent to ACP but none contained any sulfur compounds. Identification of the constituents responsible for repellency could lead to new ACP management tactics.

impacts of LUC on soil C budget to deep sub-soil layers in agricultural systems. Finally, the data indicate that expansion of sugarcane over coffee and citrus agrosystems may impact the sustainability of ethanol production because of LUC-induced depletion of soil C stock and degradation of soil quality.

Yield estimation is an important factor in a production process planning. In the case of citrus crops, can be useful in industrial management and as guidance for farmers, showing a decisive role in the product market strategies and cultivation practices. Several techniques are being studied for estimating citrus crop yield. On the basis of the known correlation between the number of visible fruits in a digital image and the total of fruits present in an orange tree, we developed a method for green fruit feature extraction with a combination of the techniques of color model conversion, thresholding, histogram equalization, spatial filtering with Laplace and Sobel operators and Gaussian blur. In addition, we built and tested an algorithm to recognize and count them, with detection rates of false-positives of 3% in images acquired in good conditions. It is possible to estimate the mean number of visible fruits in the trees within a tolerated error of 5% with up to 46 images and taking approximately 8 min without any human interaction.

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ABSTRACT-Among the pests of citrus, one of the most important is the red and black flat mite Brevipalpus phoenicis (Geijskes), which transmits the Citrus leprosis virus C (CiLv-C). When a rational pest control plan is adopted, it is important to determine the correct timing for carrying out the control plan. Making this decision demands constant follow-up of the culture through periodic sampling where knowledge about the spatial distribution of the pest is a fundamental part to improve sampling and control decisions. The objective of this work was to study the spatial distribution pattern and build a sequential sampling plan for the pest. The data used were gathered from two blocks of valencia sweet orange on a farm in São Paulo State, Brazil, by 40 inspectors trained for the data collection. The following aggregation indices were calculated: variance/ mean ratio, Morisita index, Green's coefficient, and k parameter of the negative binomial distribution. The data were tested for fit with Poisson and negative binomial distributions using the chi-square goodness of fit test. The sequential sampling was developed using Wald's Sequential Probability Ratio Test and validated through simulations. We concluded that the spatial distribution of B. phoenicis is aggregated, its behavior best fitted to the negative binomial distribution and we built and validated a sequential sampling plan for control decision-making. Index terms: red and black flat mite, negative binomial, Poisson distribution, decision making, integrated pest management. DISTRIBUIÇÃO ESPACIAL E AMOSTRAGEM SEQUENCIAL DE Brevipalpus phoenicis EM CITRUSRESUMO-Dentre as pragas dos citros, uma das mais importantes é o ácaro da leprose Brevipalpus phoenicis (Geijskes), que transmite o vírus da leprose dos citros (CiLv-C). Quando um plano racional de controle de pragas é adotado, é importante se determinar o tempo correto para se dar início ao plano de controle. Para tanto, é necessário acompanhamento constante da cultura através de amostragens periódicas, onde o conhecimento do comportamento espacial da praga é fundamental. O objetivo deste trabalho foi estudar o padrão de distribuição espacial e desenvolver um plano de amostragem sequencial para a praga. Os dados utilizados foram coletados em dois talhões de laranja valência em uma fazenda no estado de São Paulo, Brasil, por 40 inspetores treinados para a atividade.

The banana root borer, Cosmopolites sordidus Germar (Coleoptera: Curculionidae), is a major pest in many banana (Musa spp.)‐producing regions of the world, causing yield losses of up to 100%. The aims of this study were to define the spatial distribution pattern of C. sordidus in banana plantations, to determine the probability distribution model that best describes the sampling data, and to develop a sequential sampling plan for this pest. Aggregation was investigated using aggregation indices and theoretical frequency distributions. To quantify the number of insects, 80 traps were distributed in a commercial banana plantation with an area of 4 ha and inspections were performed every 2 wk from 2005 to 2008. The sequential sampling plan was based on Wald's sequential probability ratio test. The calculated indices indicated moderate aggregation, with a common k parameter of the negative binomial distribution equal to 3.29. The best model for predicting the spatial distribution of the insects was the negative binomial distribution, which fit 93% of the inspections, followed by the Neyman Type A distribution, which fit 90% of the surveys, and Poisson's distribution, which fit only one survey. A sequential sampling plan was generated with Type I and II error rates of 5%, for which 19 was the maximum expected number of samples required to reach a decision for an infestation mean of approximately 3.7 insects per trap. The validation showed that the constructed plan is reliable and provides correct recommendations for decision‐making in pest control. The banana root borer has an aggregated spatial distribution in the field. Negative binomial distribution is the best model to explain species spatial pattern. A sequential sampling plan was developed and validated. The sequential sampling plan showed reliable decision rates. The sequential sampling plan showed a reasonable number of required sample units.