ABSTRACT Intensification of the eutrophication process in surface water leads to an increase in the intensity and frequency of cyanobacterial blooms, compromising the availability of drinking water. Therefore, the aim of this study was to investigate the spatio-temporal dynamics of cyanobacteria and identify the most important nutrients for such dynamics in a semiarid artificial lake, the Orós reservoir, in north-eastern Brazil. Seventy-seven water samples were collected in 11 campaigns (six during the dry season and five during the rainy season) from seven points. The attributes under investigation were the Secchi transparency, turbidity, pH, apparent colour, electrical conductivity, total solids, total phosphorus, soluble orthophosphate content, total Kjeldahl nitrogen, ammonia content, nitrate content, and cyanobacteria dynamics, resulting in a total of 924 samples (number of campaigns × number of points × number of attributes). Principal component analysis and cluster analysis were used to investigate the significance and determinant attributes of the spatio-temporal dynamics of cyanobacteria. Of the 17 species of cyanobacteria identified, 10 accounted for 72.47% of the total accumulated variance. During the rainy season, four homogeneous groups of cyanobacteria formed, whereas during the dry season, only three groups formed. The greatest concentrations occurred during the dry season, notably for Aphanocapsa spp., Cylindrospermopsis sp., and Geitlerinema sp., which are potentially toxic and show a greater affinity to the physical attributes of water. Climate seasonality was decisive in the spatio-temporal dynamics of cyanobacteria, and high transparency values limited excessive proliferation of the dominant species.

ABSTRACT In semiarid regions with greater climatic variability, including prolonged droughts and delayed rainy seasons, supplemental irrigation is critical to ensuring yields of forage cactus pear. The objective was to evaluate root distribution and nutrient concentration and accumulation in ‘Gigante’ forage cactus pear subjected to different irrigation regimes. Seven irrigation regimes were tested: no irrigation (rainfed); five liters of medium-salinity water, with an electrical conductivity (EC) of 0.75 dS m−1, applied per linear meter every 15 days; 7% reference evapotranspiration (ETo) with a 15-d irrigation interval (II); 15% ETo with a 7-d II; 33% ETo with a 3-d II; 50% ETo with a 2-d II; and 100% ETo, irrigated daily - high-salinity water, EC of 3.6 dS m−1, was used in the last five treatments. The treatments were laid out in a randomized block design with four replicates. Roots developed best in plants irrigated at 50% ETo with a 7-d II. Applying high-salinity water at 15% ETo with a 7-d irrigation interval promotes higher concentrations of P, Ca, Mg and S in cladodes of cactus pear. Applying high-salinity water at 33% ETo with a 3-d II promotes higher uptake/accumulation of P, Ca, Mg, S and Zn in cladodes of ‘Gigante’ forage cactus pear.

ABSTRACT Arrowroot (Maranta arundinaceae), a traditional plant used to extract medicinal starch that is gluten-free and of excellent nutritional quality, is understudied for its growth and development in the organic crop system. The objective of this study was to evaluate the growth and photoassimilate partitioning in plants of two cultivars, Comum and Seta arrowroot. The design was performed in random blocks with four repetitions. At 57 days after planting (DAP), the plants were collected at regular intervals of 25 days throughout the crop cycle, and the dry mass was determined. Growth analysis was performed using the primary data. The cultivars Comum and Seta show maximum absolute growth rates of 10.51 and 12.42 g plant−1 day−1 and the maximum leaf area index (LAI) of 18.74 and 14.62, as recorded for 216 and 205 DAP, respectively. The higher absolute growth rate and higher growth of arrowroot plants in a shorter time indicate greater precocity of cultivar Seta compared to Comum. The photoassimilate partitioning is balanced between the aerial parts and rhizomes at the end of the cycle. Both cultivars can be recommended for the organic crop system in the Zona da Mata region of Minas Gerais.

ABSTRACT Sugarcane is one of the main agricultural crops in Brazil and the presence of weeds in production areas can affect growth, development and accumulation of nutrients of the crop, which may relate to the density and area of influence of the weeds in the field. Therefore, this study aimed to evaluate the effects of the density and distance of crabgrass (Digitaria horizontalis Willd) on the development of pre-sprouted seedlings (PSS) of sugarcane of the variety IAC SP 95-5000. We conducted the experiment in a greenhouse in a randomized design with four repetitions. We evaluated height, leaf area, aerial dry biomass, and nutritional analysis of leaf tissue of the PSS after the weeds flowered at 84 days. The crabgrass did not interfere in the biometric and nutritional parameters when they were 18 and 24 cm away from the crop. Regardless of the planting density and the density of 80 plants m-2 of crabgrass for all distances, we considered the distance of six cm between the crop and the weeds critical for the crop, since they significantly reduced height, leaf area, and aerial dry biomass of the PSS. The crabgrass was a potential competitor for N, P, K, Mn, Fe, and Zn with the PSS in the conditions of 2, 6, and 12 cm when they were in 40 and 80 plants m-2.

ABSTRACT The adequacy of spraying technology in the control of Asian rust to factors related to soybean cultivars and fungicide type is fundamental for the efficiency in the control of this disease. In this context, the objective was to evaluate the chemical control of Asian soybean rust and the deposition of the fungicide applied in the crop, according to different volumes and spray nozzles. Four field experiments were set up during the 2014/2015 season, each carried out with one soybean cultivar, using: NA 5909 RR®, NS 7237 IPRO®, BMX Potência RR® and W 712 RR®. The experimental design was randomized blocks in a 2x2x2 factorial arrangement, with four replications. The first factor corresponded to the use of fungicides: [pyraclostrobin + epoxiconazole] and [pyraclostrobin + epoxiconazole] + mancozeb; the second factor, types of spray nozzle: double and triple fan; and the last factor, application volume: 60 and 120 L ha-1. The highest application volume resulted in greater deposition of droplets in the canopy of the plants, regardless of the fungicide, type of spray nozzle and cultivar. The association of fungicides [pyraclostrobin + epoxiconazole] + mancozeb showed greater efficacy in controlling rust, regardless of the type of spray nozzle and the volume applied when compared to [pyraclostrobin + epoxiconazole]. The highest volume of application promoted less disease evolution in the cultivars NA 5909 RR®, NS 7237 IPRO® and BMX Potência RR®. The yields of the cultivar were higher when the combination [pyraclostrobin + epoxiconazole] + mancozeb was used.

ABSTRACT An experiment was carried out aiming to evaluate the effect of phosphorus rates on beet, in an Oxisol with high phosphorus (P) content, in Jaboticabal city, São Paulo, Brazil. The treatments were arranged in a factorial scheme, in a randomized block experimental design with four replicates. The factors evaluated were P rates (0, 120, 240, 360 and 480 kg ha-1 P2O5) and cultivar ('Early Wonder' and 'Kestrel'). At 50 days after transplanting the seedlings, foliar nitrogen (N), P, potassium (K) and boron (B) contents were evaluated, and there was no effect of the interaction between factors on foliar nutrient contents. The accumulation of these four nutrients was evaluated at harvest. All evaluated nutrients accumulated to higher levels in ‘Early Wonder’ than in 'Kestrel' both in the shoots and tuberous root. N, P and B accumulated more in the tuberous root whilst K accumulated more in the shoots. P dose did not influence the yield. Therefore, phosphate fertilization is not recommended for beet crop when cultivated in an Oxisol with a high content (88 mg dm-3) of available P.

ABSTRACT Passion fruit production has become an attractive activity due to its social and economic benefits, given the rapid economic return and well-distributed income over most of the year. From this perspective, this study aimed to evaluate the technical and economic indicators of yellow passion fruit cultivation by combining irrigation, protected cultivation, and pollination. The experimental design was in randomized blocks set up in split plots (2 x 2 x 2), with eight treatments and four replicates containing four plants per experimental unit. The protected environment was installed on the upper part of each trellis and consisted of 100 m transparent plastic film as cover material. Irrigation was performed using a micro-sprinkler system, and pollination was either manual or natural (entomophilous). The following parameters were evaluated: commercial yield - estimated for one hectare considering the mass of marketable fruits produced in the plot (30 m2); production cost - capital depreciation, input prices, and labor used in cultivation; economic indicators - profitability index, family labor remuneration, profitability, net income, benefit/cost ratio, and fixed, variable, and total costs. The results show that artificial pollination increased the yield and provided a 41% higher profitability rate than natural pollination; supplemental irrigation, compared to rainfed cultivation, has no positive effects on profitability indices; protected cultivation increases the total cost and does not 0increase the yield; organic passion fruit production provides profitability indices ranging from 60% to 70%.

ABSTRACT The South American fruit fly, Anastrepha fraterculus (Diptera: Tephritidae) is the most important insect pest in pear tree crops in Southern Brazil. Several studies pointed to the controversial efficacy of some food lures used for capture and monitoring this species in various fruit species. This study aimed to evaluate the efficacy of food lures available in the Brazilian market in capturing and monitoring A. fraterculus in relation to grape juice. The experiment was conducted during the 2014/2015 and 2015/2016 crop seasons in an Asian pear (Pyrus spp.) orchard located in Caçador, State of Santa Catarina, Brazil. The food lures evaluated were CeraTrap®, BioAnastrepha®, Torula®, Isca Mosca®, BioFruit®, and grape juice (a standard food lure in Southern Brazil). For each attractant substance, population fluctuations of A. fraterculus were recorded as well as the average number of female and male specimens captured, the FTD (fly/trap/day) rate of capture, the number of control indications, and mean weekly evaporation. The first A. fraterculus adults were captured in November, and in both crop seasons the population peak was found in January. CeraTrap® was more effective in capturing females and males and indicated a higher number of control indications compared to the other food lures. Grape juice presented lower effectiveness compared to CeraTrap®, including the evaporation parameter. It was concluded that CeraTrap® is the most effective food attractant in capturing adults of A. fraterculus and more accurate in detecting its population levels in Asian pear orchards, therefore, it is recommended rather than the usual grape juice.

ABSTRACT The use of resistant cultivars is an efficient and recommended method for the management of leafminers, which are the main phytosanitary problem in melons. The objectives of this study were to identify the sources of resistance to the leafminer in yellow melon accessions and to determine the resistance inheritance in acession AM-RT. Two field experiments were conducted in the municipalities of Baraúna, RN and Icapuí, CE, Brazil, to identify the sources of resistance. The design adopted was completely randomized blocks with 22 treatments and four replications. In this evaluation, the number of mines per leaf was quantified. The heterogeneity of the studied materials allowed for the identification of the accessions AM-RT and AM-TM as sources of resistance, considering that they revealed zero mines in the two evaluation environments. The accession AM-RT was selected and used to obtain the S1 population (by self-fertilization), S1:2 population derived from S1, and crossing between AM-RT and ‘Goldex’, which were evaluated in a third laboratory trial to determine the genetic control of resistance in that material. By the segregation pattern of the populations S1, S1:2, and the crossing (AM-RT and ‘Goldex’) and the estimation of the chi-squared (χ2) values, which were 1.33, 3.14, and 0.36, respectively, it was determined that the inheritance of resistance was controlled by only one gene with complete dominance. Therefore, in this study, two sources of resistance to the leafminer were identified, and resistance was conditioned by a gene with complete dominance in the accession ‘AM-RT’.

ABSTRACT Image analysis combined with machine learning models can be an excellent tool for classification of fava (Phaseolus lunatus L.) genotypes and is a low-cost system. Fava is grown by family farmers, mainly, in the Northeast and South regions of Brazil, presenting economic and social importance. Evaluations to gather information on qualitative and quantitative characters of seeds enable the description and distinction of genotypes, allowing the evaluation of variability of plant species, which is essential in breeding programs. The use of image analysis is a fast and economic tool for obtaining large quantity of information. Machine learning techniques have been developed and implemented in the agricultural sector due to technological advances and increasing use of artificial intelligence, which enables the automatization of several processes. In this context, the objective of this work was to evaluate different machine learning models to classify fava genotypes, using data obtained through image analysis. Images of fava seeds were captured using a table scanner (HP Scanjet 2004), set to true color mode, arranged upside down inside of an aluminum box fully closed during the capture of the images for an adequate illumination and prevention of environmental noises. The K-Nearest Neighbor, Naive Bayes, Linear Discriminant Analysis, Support Vector Machine, Gradient Boosting, Bootstrap Aggregating, Classification and Regression Trees, Random Forest, and C50 models were used for the study. Linear Discriminant Analysis was the model that presented the highest efficiency for classifying the genotypes, with an accuracy of 90%.