RESUMO: Diante da importância de descrever o acúmulo de matéria seca total em acessos de alho e a vantagem dos Modelos Não Lineares Mistos (MNLM) nesse processo, o presente trabalho teve como objetivo comparar quatro equações não lineares (Gompertz, Logístico, Richards e von Bertalanffy) no ajuste do acúmulo de matéria seca total por planta de 30 acessos de alho. O objetivo também foi identificar os melhores acessos de acordo com cada parâmetro de crescimento, estimando os efeitos aleatórios em torno da média através do melhor entre os modelos. A análise foi realizada com o uso do software R. O melhor modelo foi o Logístico segundo os critérios utilizados para comparação (AIC, BIC, R a j . 2, EQM e EAM), apresentando estimativas mais próximas dos valores reais observados. De acordo com os efeitos aleatórios estimados por este modelo, que representam desvios da média, os acessos que apresentaram maior peso assintótico foram 4505, 4826 e 4500, enquanto os acessos 4826, 4837 e 4491 demoraram mais para atingir o ponto de inflexão da curva. A abordagem NLME utilizou apenas um ajuste por equação para obter informações sobre todos os indivíduos da amostra, ajustando eficientemente a matéria seca total acumulada e identificando os melhores acessos de acordo com os efeitos aleatórios estimados de seus parâmetros. RESUMO MNLM (MNLM processo Gompertz, Gompertz (Gompertz Bertalanffy 3 crescimento modelos AIC, AIC (AIC BIC 2 EAM, EAM , EAM) observados 4505 482 4500 483 449 curva amostra parâmetros 450 48 44 45 4

ABSTRACT: Given the importance of describing the accumulation of total dry matter in garlic accessions and the advantage of Nonlinear Mixed Effect Models (NLME) in this process, the present work research compared four nonlinear equations (Gompertz, Logistic, Richards, and von Bertalanffy) in the fit of accumulation of total dry matter per plant of 30 garlic accessions. The objective was also to identify the best accessions according to each growth parameter by estimating the random effects around the mean through the best among the models. The analysis was carried out using the R software. The best model was the Logistic according to the criteria used for comparison (AIC, BIC, R a j . 2, MSE and MAE), presenting estimates closer to the actual observed values. According to the random effects estimated by this model, which represent deviations from the mean, the accessions that showed the highest asymptotic weight were 4505, 4826 and 4500, while accessions 4826, 4837 and 4491 took longer to reach the inflection point of the curve. The NLME approach used one fit per equation to obtain information on all individuals in the sample, efficiently adjusting the accumulated total dry matter and identifying the best accessions according to the estimated random effects of its parameters. ABSTRACT (NLME process Gompertz, Gompertz (Gompertz Richards Bertalanffy 3 models software AIC, AIC (AIC BIC 2 MAE, MAE , MAE) values 4505 482 4500 483 449 curve sample parameters 450 48 44 45 4

ABSTRACT. Chickpea is a legume with nutrient-rich grains important for human feeding. Tobacco budworm, Chloridea virescens (Lepidoptera: Noctuidae), is one of the most major pests of chickpea (Cicer arietinum) in Brazil. This pest damages leaves, flowers, pods, and grains. Plant resistance to insects is an important tactic of pest management, which usually facilitates and reduce costs of implementing an Integrated Pest Management for farmers. Thus, this study aimed to evaluate the resistance in chickpea cultivars to C. virescens. Six chickpea cultivars were evaluated for antixenosis, initial antibiotic parameters, and behavior under field conditions. The cultivars BRS Kalifa and BRS Cícero were less attractive in a free-choice test, while Jamu 96 and BRS Kalifa were less attractive in a no-choice test. BRS Kalifa and BRS Toro leaves had a higher trichome density. Jamu 96 and BRS Toro had higher contents of oxalic and malic acids. C. virescens larvae in BRS Cícero, BRS Toro, and BRS Kalifa showed the lowest weights. Jamu 96 pods were the least damaged, and BRS Aleppo and Jamu 96 had the highest yields. The chickpea cultivars Jamu 96 and BRS Aleppo, which had resistance levels and mechanisms, can be used in integrated pest management programs to control C. virescens.

RESUMO Feijão-caupi é uma espécie nutritiva, cultivada em várias partes do mundo, com ampla variabilidade genética que pode ser explorada no melhoramento. Este trabalho teve como objetivo identificar genótipos fenotipicamente divergentes de Vigna unguiculata (L.) Walp., sob esta perspectiva quanto as variáveis agronômicas e fisiológicas visando produção de grãos verdes. Em um experimento conduzido em Fortaleza - CE, 13 variáveis foram avaliadas em 44 genótipos provenientes do Banco Ativo de Germoplasma da Universidade Federal do Ceará. O experimento foi instalado em delineamentos de blocos aumentados, com quatro testemunhas adicionais (cultivares comerciais). Os componentes de variância genético e ambiental foram estimados por máxima verossimilhança restrita e, a partir destes, foi calculado o coeficiente de correlação intraclasse (ICC). Foi realizada análise de componentes principais, agrupamento de Tocher e análise de correlação. As variáveis mais influenciadas pela variação genética foram: produção por planta, comprimento da vagem verde, comprimento do grão verde, massa de grãos por vagem e produtividade total, com ICC > 0.5. A análise de componentes principais permitiu identificar as características fisiológicas: gs, ci, ci.ca, e agronômicas: comprimento da vagem verde, massa de grãos verdes, número de grãos por vagem e precocidade da produção, como sendo importantes na diferenciação de genótipos de feijão-caupi. Os genótipos CE: 02, 151, 165, 172, 189, 244, 986 e 1002 possuem variabilidade genética e são recomendados para uso em um programa de melhoramento genético de feijão-caupi para produção de grãos verdes.

ABSTRACT Cowpea is a nutritious species cultivated worldwide whose high genetic variability can be exploited in breeding programs. The present study aimed to identify phenotypically divergent genotypes of Vigna unguiculata (L.) Walp., from this pe rspective concerning agronomic and physiological variables aiming at green grain production. An experiment was conducted in Fortaleza – CE, to analyse 13 variables in 44 genotypes from the Active Germplasm Bank of the Federal University of Ceará. The experiment was set up in an augmented block design with four additional controls (commercial cultivars). The genetic and environmental variance components were estimated by restricted maximum likelihood, after which the intraclass correlation coefficient (ICC) was calculated. Principal components analysis, Tocher’s clustering and correlation analysis were used in the study. The variables most influenced by genetic variance were production per plant, green pod length, green grain length, grain mass per pod, and total yield, with ICC > 0.5. Principal components analysis signalled the physiological variables gs, ci, and ci.ca and the agronomic variables of green pod length, green grain mass, number of grains per pod, and earliness of production as important for differentiating between cowpea genotypes. CE genotypes 02, 151, 165, 172, 189, 244, 986, and 1002 show genetic variability, and their use is recommended in cowpea breeding programs aimed at green-grain production.

RESUMO A palma forrageira é uma cultura altamente resistente, e oferece benefícios em sua mucilagem para a indústria devido às suas propriedades físico-químicas. Objetivou-se analisar o efeito do manejos de irrigação, época de colheita, tamanho do cladódio e adição de ácido cítrico durante o processamento no rendimento agroindustrial e nas propriedades físico-químicas de mucilagem extraída de cladódios de Nopalea cochenillifera clone Miúda cultivados em sequeiro e irrigados. Foram medidos o rendimento, teor de sólidos solúveis, acidez titulável, pH, teor de K+ e Na+, e condutividade elétrica na mucilagem. As práticas de manejo no campo resultaram em alterações nos ftoquímicos estudados. No cultivo de sequeiro, a colheita noturna dos cladódios maiores aumentou os teores de K+ e sólidos solúveis. A adição de ácido cítrico à extração da mucilagem resultou em maiores quantidades de sólidos solúveis, acidez titulável e condutividade elétrica e menores valores de pH. A maior disponibilidade hídrica promoveu maiores rendimentos de mucilagem.

ABSTRACT Cactus is a highly resistant crop, and offers benefits in its mucilage for the industry due to its physicochemical properties. This study aimed to analyze the effect of irrigation managements, harvest time, cladode size and citric acid addition during the processing on the agro-industrial yield and physicochemical properties of mucilage extracted from cladodes of Nopalea cochenillifera Miúda clone cultivated under rainfied and irrigated conditions. The yield, soluble solids content, titratable acidity, pH, K+ and Na+ contents, and the electrical conductivity were measured in the mucilage. The management practices in the field resulted in changes in the studied phytochemicals. For the rainfied cultivation, the night harvest of the biggest cladodes increased the K+ and soluble solids contents. The addition of citric acid to the mucilage extraction resulted in higher amounts of soluble solids, titratable acidity and electrical conductivity and lower pH values. The highest water availability promoted higher mucilage yields.

ABSTRACT. Spatial data (e.g., phytopathogenic data) do not always meet assumptions such as stationarity, isotropy and Gaussian distribution, thereby requiring complex spatial methods and models. Some deterministic assumption-free methods such as the inverse distance weighting can also be applied to predict spatial data, but their output is limited for graphical solutions (mapping). We adapted a computer-based prediction method called Circular Variable Radius Moving Window (CVRMW) that is based on two others: moving window kriging (MWK) and inverse squared-distance weighting (ISDW). The algorithm is developed to meet an objective function that minimizes the index of variation of the spatial observations inside the moving window. A code in R language is presented and thoroughly described. The outputs include the range of the spatial dependence as the radius calculated at every target location and the standard error of the predicted values, mapped to provide a useful tool for spatial exploratory analysis. The method does not make any assumptions about the spatial process, and it is an alternative for dealing with spatial heterogeneity.

ABSTRACT Multidimensional scaling is a multivariate analysis technique that can be used to exploit genetic diversity, aiming at the selection of Capsicum genotypes with desirable characteristics for in-pot ornamental purposes. This work aimed to select genotypes with ornamental potential within F4 populations of ornamental pepper plants. Three F4 families were used (17.18, 30.16, and 56.8). The genotype distance matrices were estimated based on qualitative and quantitative descriptors, separately, combining the standardized distances of Gower and Mahalanobis, respectively. The relation of the distance between genotypes was graphically studied through non-metric multidimensional scaling. Kruskal' Stress was used as the measured misadjustment of the nMDS solution. There is genetic diversity within the analyzed families, allowing to practice selection. The selection in family 17.18 of genotypes 6 and 32 is recommended, as well as in family 30.16 of genotypes 22 and 4, and family 56.8 of genotypes 15 and 36, since they present important characteristics for ornamental purposes. The selection of genotypes is more efficient when using mixed data since it provides a more complete genetic diversity in an improvement program.

ABSTRACT Peppers belong to the Solanaceae family and present a wide genetic variability that may be accessed through phenotypic and genotypic traits. This work aimed to study the genetic divergence in an ornamental pepper F3 population by multivariate methods based on the individual and simultaneous analyses of qualitative, quantitative, and molecular data. The work was developed in the Center of Agrarian Sciences (CCA) of the Universidade Federal da Paraíba (UFPB), Paraíba state, Brazil. 44 progenies from an F3 generation were used and the characterization of 30 qualitative traits, 16 quantitative traits, and 18 pairs of microsatellite primers was performed. Individual and simultaneous analyses of the variables were performed by using the clustering method of Ward’s algorithm. Tocher’s method was used based on distance matrixes. A non-metric multidimensional scaling was applied (nMDS) for the graphic representation of the distance matrixes in the bidimensional space. Data analysis was efficient to separate the genotypes into distinct groups. There is genetic variability among the individuals of the C. annuum F3 population, verified by individual and joint trait measurements. The three clustering methods were efficient to represent the genetic distance between individuals of ornamental pepper plants. Individuals 1, 2, 7, 8, 10, 11, 21, 27, 29, 35, and 38 are indicated to advance generation and continue the breeding program.

RESUMO A área foliar é uma variável essencial para a quantificação de outras importantes características foliares em estudos fisiológicos de plantas, como taxa fotossintética e teor de fósforo, normalizados por área. Essa é uma das razões para a necessidade de métodos rápidos e precisos para estimar a área foliar. O objetivo deste trabalho foi ajustar modelos de regressão linear ou não linear para predizer a área foliar de seis espécies de leguminosas forrageiras, a partir de imagens digitais analisadas com o pacote LeafArea, software R. Em um experimento de campo, foram coletadas aleatoriamente 100 folhas das seguintes espécies: Crotalaria juncea (L.), Canavalia ensiformis (L.), Cajanus cajan (L.), Dolichos lablab (L.), Mucuna cinereum (L.), e Mucuna aterrima (Piper & Tracy) Merr., nas quais foram medidos o comprimento e a largura do folíolo central. Posteriormente, imagens digitais de cada folha foram processadas no software R para estimativa da área foliar. Essas estimativas foram usadas para ajustar modelos de predição de área foliar; de fato, setenta folhas foram usadas para ajustar os modelos; o restante delas foi usado para validação do modelo. Para as seis espécies, o modelo polinomial completo de segundo grau, ou submodelos derivados, pode ser usado para predizer a área foliar em função do comprimento e largura do folíolo central, apresentando R² acima de 0,98 e porcentagem de erro médio absoluto abaixo de 9%. Nestes modelos, o efeito da largura da folha é geralmente maior que o comprimento da folha. O pacote R LeafArea mostrou-se uma ferramenta muito eficiente para a estimativa da área foliar através da execução do software ImageJ, com alta precisão e fácil calibração.

ABSTRACT Leaf area is an essential variable for the quantification of other important leaf characteristics in physiological studies of plants, such as normalized photosynthetic rate and normalized phosphorus content. That is one of the reasons for the need of fast and accurate methods to estimate leaf area. The objective of this work was to fit linear or non-linear regression models to predict the individual leaf area of six species of forage legumes, based on digital images analyzed with the package LeafArea, R software. In a field experiment, 100 leaves were randomly collected from the following species: Crotalaria juncea (L.), Canavalia ensiformis (L.), Cajanus cajan (L.), Dolichos lablab (L.), Mucuna cinereum (L.), and Mucuna aterrima (Piper & Tracy) Merr., in which the central leaflet length and width were measured. Afterwards, digital images of each leaf were processed in R software for leaf area estimation. These estimates were used to fit leaf area prediction models; in fact, seventy leaves were used to fit the models; the rest of them were used for model validation. For the six species, the complete second-degree polynomial model, or derivative submodels, can be used to predict leaf area as a function of length and width of the central leaflet, presenting R² above 0.98 and percentage absolute mean error below 9%. In these models, the effect of leaf width is generally greater than the leaf length. The R package LeafArea showed to be a very efficient tool for the estimation of leaf area through the execution of the software ImageJ, with high precision and easy calibration.

Resumo: Vários fatores interferem na eficiência do teste de condutividade elétrica, com destaque para teor de água inicial e temperatura durante a embebição. Este trabalho objetivou avaliar o efeito do teor de água inicial das sementes de ervilha e da temperatura na eficiência do teste de condutividade elétrica. Utilizaram-se seis lotes de ervilha ‘Mikado’ que foram submetidos a testes para caracterização inicial. No primeiro ensaio, baseado na umidade inicial das amostras, foi ajustado o teor de água para 9, 11, 13 e 15% e, posteriormente, foram submetidas ao teste de condutividade elétrica. No segundo ensaio, a água para embebição das sementes foi mantida por 24 horas a 10, 15, 20, 25 e 30 °C e, após este período, adicionou-se às sementes e foram colocadas para embeber por mais 24 horas nas referidas temperaturas. Observou-se que teor de água inicial e temperatura da água durante a embebição influenciaram nos resultados do teste de condutividade elétrica. Este teste deve ser realizado com água destilada previamente mantida por 24 horas a 25 °C para estabilização da temperatura, posteriormente as sementes, com teor de água entre 11 e 15%, colocadas para embeber na temperatura de 25 °C, mantidas nesta temperatura por 24 horas.

Abstract: Several factors affect the electrical conductivity test efficiency, with emphasis given to the initial water content and the temperature during imbibition. This study aimed to evaluate the effect of the initial water content of pea seeds and the temperature on the electrical conductivity test efficiency. Six lots of ‘Mikado’ pea were used, which were previously tested for initial characterization. In the first trial, based on the initial value of the samples, the seed moisture content was adjusted to 9, 11, 13 and 15% and then the seeds were submitted to the electrical conductivity test. In the second trial, the water for seed imbibition was kept for 24 hours at 10, 15, 20, 25 and 30 ºC, and after that time the seeds were added and soaked for other 24 hours at the temperatures already mentioned. It was observed that initial seed moisture content and water temperature during imbibition influenced the results of the electrical conductivity test. This test should be carried out with distilled water, previously maintained for 24 hours at 25 °C for temperature stabilization. Then, the seeds with seed moisture content between 11 and 15% should be put to soak at 25 °C, and maintained at this temperature for 24 hours.

RESUMO O presente trabalho objetivou estimar a divergência genética entre progênies de meios-irmãos de milho visando direcionar a recombinação entre progênies contrastantes e superiores para a produção de milho-verde. Noventa e seis progênies foram avaliadas no delineamento de blocos casualizados com 3 repetições, sendo mensuradas 18 características associadas à adaptação agronômica e ao rendimento de milho-verde. A divergência genética foi estimada a partir da distância quadrada generalizada de Mahalanobis e as progênies agrupadas pelos métodos UPGMA e de Tocher. A análise de variância conjunta evidenciou variabilidade genética entre as progênies para as características. O método UPGMA foi mais sensível que o de Tocher, pois levou à formação de 11 grupos geneticamente dissimilares em comparação com os 5 de Tocher. O agrupamento identificou progênies superiores e contrastantes para a produção de milho-verde. A recombinação dessas progênies possibilitará incrementar a variabilidade genética e a frequência de alelos favoráveis à produção de milho-verde.

ABSTRACT The present study aimed to estimate the genetic divergence among corn half-sib progenies seeking to direct recombination between contrasting and superior progenies for green corn production. Ninety-six progenies were evaluated in a randomized block design with 3 replications, and 18 characteristics associated with agronomic adaptation and green corn yield were measured. The genetic divergence was estimated using generalized square Mahalanobis distance and the progenies grouped by UPGMA and Tocher’s methods. The joint analysis of variance showed genetic variability among the progenies for the characteristics evaluated. The UPGMA method was more sensitive than Tocher’s, since it led to the formation of 11 groups genetically dissimilar compared to the 5 ones of Tocher’s method. The grouping allowed to identify superior and contrasting progenies for green corn production. The recombination of these progenies allows increasing genetic variability and the frequency of alleles favorable to the green corn production.

RESUMO A lagarta Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) é a principal praga da cultura do milho no Brasil. A ação de substância química de defesa de planta, na biologia e comportamento de inseto é pouco estudada. O objetivo do trabalho foi avaliar a ação de rutina e os efeitos na biologia da lagarta S. frugiperda, utilizando-se dieta artificial acrescida com este flavonoide. O trabalho consistiu de quatro tratamentos: dieta normal (testemunha) e dieta com adição de 1,0; 2,0 e 3,0 mg g-1 de rutina. As lagartas foram avaliadas diariamente, observando os parâmetros biológicos: período, peso e viabilidade larval, período, peso e viabilidade pupal, longevidade de adultos e ciclo total. Utilizou-se o delineamento experimental inteiramente casualizado com 25 repetições. O flavonoide rutina mostrou-se influenciar de forma negativa a biologia de S. frugiperda por prolongar o período larval, diminuir o peso larval e pupal e viabilidade pupal. A adição de rutina nas diferentes concentrações prolongou o ciclo de S. frugiperda. O uso de planta com atividade inseticida tem potencial como estratégia em MIP.

ABSTRACT The fall armyworm Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) is a major pest of maize crops in Brazil. The effects of plant metabolites on the biology and behavior of insects is little studied. The aim of the study was to evaluate the activity of rutin on the biology of the S. frugiperda by using artificial diets containing rutin. The study evaluated four treatments: regular diet (control group) and diets containing 1.0, 2.0 and 3.0 mg g-1 of rutin. The following biological variables parameters of the larvae were evaluated daily: development time (days), larval and pupal weight (g) and viability (%), adult longevity and total life cycle (days). A completely randomized experimental design was used with 25 replication. The rutin flavonoid negatively affected the biology of S. frugiperda by prolonging the larval development time, reducing the weight of larvae and pupae and decreasing the viability of the pupae. The addition of different concentrations of rutin prolonged the S. frugiperda life cycle. The use of plant with insecticidal activity has the potential with strategy in IPM.

Resumo: O objetivo deste trabalho foi construir redes ponderadas de correlação, para descobrir estruturas de correlação e padrões de ligação entre 28 caracteres morfoagronômicos de pimenteiras, relacionados à plântula, planta, inflorescência e fruto. Informações fenotípicas e genotípicas de 16 genótipos de Capsicum foram analisadas. Estruturas de correlação e padrões de ligação podem ser facilmente identificados nas matrizes por meio do algoritmo Fruchterman-Reingold, com as informações da rede de correlações. Ambos os tipos de correlação mostraram o mesmo padrão geral de ligação entre caracteres de frutos, com altos valores de herdabilidade no sentido amplo e grande aptidão desses genótipos para o melhoramento agronômico e ornamental. As dimensões das folhas estão correlacionadas ao grupo de caracteres de fruto. Redes de correlação de caracteres de pimenteiras podem aumentar a eficácia da seleção de genótipos, uma vez que tanto caracteres correlacionados quanto grupos podem ser identificados.

Abstract: The objective of this work was to build weighted correlation networks, in order to discover correlation structures and link patterns among 28 morphoagronomic traits of chili pepper related to seedling, plant, inflorescence, and fruit. Phenotypic and genotypic information of 16 Capsicum genotypes were analyzed. Correlation structures and link patterns can be easily identified in the matrices using the Fruchterman-Reingold algorithm with correlation network information. Both types of correlations showed the same general link pattern among fruit traits, with high broad-sense heritability values and high aptitude of the genotypes for agronomic and ornamental breeding. Leaf dimensions are correlated with a cluster of fruit traits. Correlation networks of chili pepper traits may increase the effectiveness of genotype selection, since both correlated traits and groups can be identified.

ABSTRACT There are many methods for determining precompression stress (σp), whose value is affected by the slope of the soil compression curve. This study was designed to evaluate the hypothesis that for a certain compression curve all methods used to determine σp present the same value and accuracy. The aim of this study was to compare the accuracy and the relationship among seven of these methods by computational simulation of soil compression curves under nine scenarios. The following methods were used: Casagrande, Pacheco Silva, intersection of the initial void ratio with the virgin compression line (VCLzero), and the regression methods based on 2 (reg1), 3 (reg2), 4 (reg3), and 5 (reg4) points for modeling the elastic curve. Under each scenario, created by combining the swelling and the compression indices, 1,000 compression curves were computationally simulated via the Monte Carlo method. Subsequently, 95 % percentile confidence intervals were built using the 1,000 estimates of σp from each method under each scenario. Most of the differences among the methods were detected under scenarios consisting of high swelling and low compression indices. In general, Casagrande, Pacheco Silva, and reg4 were strongly correlated and presented the highest values of σp, as well as similar variability. The latter two can be considered as alternatives to the standard method of Casagrande, except for Pacheco Silva when the curve has a low compression index (≤0.2) and from medium to high swelling index (≥0.025), for which differences (p<0.05) were detected.

Multivariate techniques have become a useful tool for studying the phenotypic diversity of Germplasm Bank accessions, since they make it possible to combine a variety of different information from these accessions. This study aimed to characterize the phenotypic dispersion of garlic (Allium sativum L.) using two multivariate techniques with different objective functions. Twenty accessions were morphologically characterized for bulb diameter, length, and weight; number of cloves per bulb; number of leaves per plant; and leaf area. Techniques based on generalized quadratic distance of Mahalanobis, UPGMA (Unweighted Pair Group Method with Arithmetic Mean) clustering, and nMDS (nonmetrric MultiDimensional Scaling) were applied and the relative importance of variables quantified. The two multivariate techniques were capable of identifying cultivars with different characteristics, mainly regarding their classification in subgroups of common garlic or noble garlic, according to the number of cloves per bulb. The representation of the phenotypic distance of cultivars by multidimensional scaling was slightly more effective than that with UPGMA clustering.

O penetrômetro é o instrumento usualmente indicado para avaliação da resistência mecânica do solo à penetração (RMP). O objetivo deste trabalho foi comparar o desempenho de dois penetrômetros: um eletrônico e outro de impacto, na avaliação da RMP. O trabalho foi realizado na Fazenda Experimental Chã-de-Jardim, Centro de Ciências Agrárias, da Universidade Federal da Paraíba (CCA/UFPB), Areia-PB, em área de Latossolo Amarelo de dimensão 35 × 35 m. Os penetrômetros utilizados foram: um de impacto, modelo IAA/Planalsucar-Stolf, e um digital, Falker, modelo PenetroLOG - PLG 1020, com aptidão eletrônica para aquisição de dados em quatro profundidades. Dentro da área, 40 pontos foram amostrados, seguindo duas direções: Norte, para o penetrômetro eletrônico, e Sul, para o de impacto, com os pontos de coleta de cada penetrômetro espaçados em 0,1 m. Os dados foram analisados segundo o modelo de análise de variância de um experimento em delineamento inteiramente casualizado. Os penetrômetros de impacto e Falker apresentaram médias de 1,75 MPa, sendo, portanto, semelhantes na avaliação da RMP em todas as profundidades analisadas, sugerindo que ambos modelos testados podem ser utilizados para solos com características texturais semelhantes as do solo deste estudo.

The penetrometer is an instrument usually suitable for evaluating the penetration resistance of soil (PR). This study aimed to compare the performance of an electronic penetrometer and an impact penetrometer on the evaluation of the PR. The experiment was carried out at the experimental farm Chã-de-Jardim, CCA/UFPB, Areia - PB, in an area of Yellow Latossoil measuring 35 × 35 m. The impact penetrometer evaluated was an IAA/Planalsucar-Stolf and the digital penetrometer Falker PenetroLOG - PLG 1020, with electronic capability for data acquisition in 4 depths. Within the area, 40 points were sampled following two directions, North for the electronic penetrometer and South for the impact penetrometer, with the sample points of each penetrometer spaced 0.1 m apart. Data were analyzed following the analysis of variance of a completely randomized design. Both penetrometers showed means of 1.75 MPa, being similar on the evaluation of PR for all analyzed depths, suggesting that both devices can be used for soils with textural characteristics similar to those of this study.