Search

Chemical desiccation is widely used in agriculture to anticipate harvest and mitigate the effects of adverse environmental conditions. It is applied to both grains and seeds. Although this practice is widely used, there are still significant gaps in understanding the effects of different herbicide application times on seed quality and plant physiological responses. The objective of this study was to evaluate the effects of different herbicide application times on cowpea, focusing on seed quality, physiological responses, and biochemical composition, including chlorophylls, carotenoids, sugars, and proline, under nocturnal desiccation. In the first experiment, eight herbicides and two mixtures were applied at night: diquat, flumioxazin, diquat + flumioxazin, glufosinate ammonium, saflufenacil, carfentrazone, diquat + carfentrazone, atrazine, and glyphosate. All of the tested herbicides caused a reduction in normal seedling formation, with the diquat + carfentrazone combination resulting in 100% abnormal seedlings. A significant decrease in chlorophyll levels (chlorophyll a: 63.5%, chlorophyll b: 50.2%) was observed using diquat, which indicates damage to photosynthetic processes, while the carotenoid content increased. Total soluble sugars and proline were also negatively impacted, reflecting physiological stress and metabolic changes in seedlings. In the second experiment, three application times were tested with diquat, diquat + flumioxazin, and diquat + carfentrazone. Nocturnal application showed the most significant reduction in chlorophyll levels and increased carotenoid levels. Application at noon and late afternoon also significantly changed the soluble sugar and proline levels. These results indicate that the herbicide application time directly influences the seeds’ physiological quality.

Naturally colored fiber cotton has fibers that present natural colors without the need for dyeing processes or dye application. Low nitrogen availability during production can affect fiber quality. Thus, this study aimed to evaluate the fiber quality of naturally colored cotton cultivars as a function of nitrogen fertilization. The research was conducted in an experimental field at the Federal Rural University of Semiarid, Northeast Brazil. The experiment was arranged in a randomized block design, with four replications, in a split-plot scheme. Five nitrogen rates were distributed in the experimental plots, and four naturally colored fiber cotton cultivars were distributed the subplots. The following parameters were evaluated: fiber percentage, fiber length, length uniformity, short-fiber index, strength fiber, fiber elongation, micronaire, fiber maturity, and count strength product. BRS Topázio excelled in most fiber quality characteristics. The 100 kg ha−1 of N and 150 kg ha−1 increase the fiber quality of the cultivars BRS Safira, BRS Topázio, and BRS Rubi. The dose of 200 kg ha−1 of N improved the fiber quality of the BRS Verde cultivar. Nitrogen fertilization positively influenced the fiber quality of naturally colored cotton.

Naturally colored fiber cotton is an essential alternative green and organic for the textile industry, as it does not require chemical dyeing. However, the low availability of potassium during production can directly affect the quality of the fiber. Based on this, this study aimed to evaluate the fiber quality in naturally colored cotton cultivars submitted to potassium fertilization in a semi-arid region. The experimental design was in randomized blocks, with four replications, and the treatments were arranged in split plots. In the plot, the following were allocated: five K rates (0, 60, 120, 180, and 240 kg ha−1 of K2O); and in the subplots, the four colored cotton cultivars (BRS Rubi, BRS Safira, BRS Topázio, and BRS Verde). The results showed that K is involved in the length, uniformity, short fiber index, micronaire index, and reliability index of naturally colored cotton fibers. A longer fiber length of 30.45 mm was obtained at a dose of 240 kg ha−1 of K2O for the cultivar BRS Topázio. In addition, a higher uniformity (84.95%) was achieved with the dose of 240 kg ha−1 of K2O for BRS Verde. The dose of 240 kg ha−1 of K2O reduced (8.62% and 11.28%) the short fiber index in the cultivars BRS Rubi and BRS Safira, respectively.

ABSTRACT: Using non-destructive and low-cost methods to determine leaf area has gained important applications. The research objectives were (i) to propose a non-destructive method to estimate the leaf area of castor bean crops and (ii) to build equations that accurately and quickly estimate the leaf area of specie. One thousand healthy and expanded leaves of five castor bean cultivars (New Zealand Purple, Sipeal, Carmencita, Amarelo de Irecê, and IAC-80) were collected, and 200 leaves were collected from each. The maximum length, maximum width, and leaf area were calculated for each leaf. The product between length and width (LW) were calculated. We performed tests with different linear and non-linear regression models between leaf area and linear leaf dimensions of each cultivar. The models used were linear, linear without intercept, and power. The criteria for choosing the best models to estimate the leaf area of castor beans were a higher coefficient of determination, more elevated Pearson’s linear correlation coefficient, lower Akaike information criterion, higher Willmott agreement index, and smallest root mean square error. The equations that presented the best criteria for estimating the leaf area of castor bean cultivars were those that used the product between length and width, compared to equations that used only one leaf dimension. The model ŷ = 0.439 × LW can be used to accurately and quickly estimate the castor bean leaf area through linear measurements of the leaves, using the product between length and width (LW), regardless of the cultivar chosen.

Proper potassium (K) fertilization management is crucial for optimizing yield and minimizing environmental impacts in colored fiber cotton cultivars, particularly in semiarid regions. This study aimed to assess the efficiency of K use by colored cotton cultivars under K fertilization in a semiarid region. Two experiments were conducted in 2019 and 2021, representing two agricultural seasons. The experimental design employed randomized blocks with split plots and four replications. The main plots consisted of five randomized K doses (0, 60, 120, 180, and 240 kg ha-1 of K2O), while subplots included four cultivars of colored cotton (BRS Rubi, BRS Safira, BRS Topázio, and BRS Verde). The results revealed that BRS Rubi exhibited superior agronomic efficiency with a dose of 60 kg ha-1 of K2O in both agricultural seasons. The maximum efficiency of K use by colored cotton cultivars was achieved with a dose of 240 kg ha-1 of K2O in the semiarid region of Brazil. The cultivars BRS Rubi and BRS Topázio demonstrated the highest use efficiency. Furthermore, BRS Topázio displayed the highest K accumulation in plant shoots during both seasons.

The estimative of the leaf area using a nondestructive method is paramount for successive evaluations in the same plant with precision and speed, not requiring high-cost equipment. Thus, the objective of this work was to construct models to estimate leaf area using artificial neural network models (ANN) and regression and to compare which model is the most effective model for predicting leaf area in sesame culture. A total of 11,000 leaves of four sesame cultivars were collected. Then, the length (L) and leaf width (W), and the actual leaf area (LA) were quantified. For the ANN model, the parameters of the length and width of the leaf were used as input variables of the network, with hidden layers and leaf area as the desired output parameter. For the linear regression models, leaf dimensions were considered independent variables, and the actual leaf area was the dependent variable. The criteria for choosing the best models were: the lowest root of the mean squared error (RMSE), mean absolute error (MAE), and absolute mean percentage error (MAPE), and higher coefficients of determination (R2). Among the linear regression models, the equation yˆ=0.515+0.584*LW was considered the most indicated to estimate the leaf area of the sesame. In modeling with ANNs, the best results were found for model 2-3-1, with two input variables (L and W), three hidden variables, and an output variable (LA). The ANN model was more accurate than the regression models, recording the lowest errors and higher R2 in the training phase (RMSE: 0.0040; MAE: 0.0027; MAPE: 0.0587; and R2: 0.9834) and in the test phase (RMSE: 0.0106; MAE: 0.0029; MAPE: 0.0611; and R2: 0.9828). Thus, the ANN method is the most indicated and accurate for predicting the leaf area of the sesame.

The large variation in the response of sunflower to nitrogen fertilization indicates the need for studies to better adjust the optimum levels of this nutrient for production conditions. Our objectives were to analyze the agronomic yield of sunflower cultivars as a function of nitrogen fertilization; indicate the cultivar with high nitrogen use efficiency; and measure the adequate N dose for sunflower through nutritional efficiency. The completely randomized block design with split plots was used to conduct the experiments. The treatments included five nitrogen rates being allocated in the plots and the four sunflower cultivars. To estimate the nutrient use efficiency in the sunflower, we measured agronomic efficiency (AE), physiological efficiency (PE), agrophysiological efficiency (APE), apparent recovery efficiency (ARE), and utilization efficiency (UE). The results indicate that all cultivars had a reduction in AE due to the increase in N doses in the first crop. For PE, the highest values were observed for Altis 99 during the 2016 harvest. In that same harvest, Altis 99 had the highest APE. The dose of 30 kg ha−1 provided greater ARE for all cultivars in both crops, with greater emphasis on BRS 122 and Altis 99. The cultivation of cultivars Altis 99 and Multissol at a dose of 30 kg ha−1 in is recommended semiarid regions.

Sunflower is an oleaginous plant of great importance worldwide that stands out in the production of edible oil and human food. The identification of differences between cultivars regarding the use of phosphorus and the production of achenes at different levels of phosphate fertilization is a viable strategy to allow its cultivation in soils with different concentrations of phosphorus, without compromising yield and reducing environmental damage associated with excessive applications of phosphate fertilizers. Thus, the objective of this study was to evaluate different levels of phosphorus fertilization and sunflower cultivars regarding the efficiency of phosphorus use in two agricultural crops. The experimental design was in randomized blocks with four replications in split-plots, where four doses of phosphorus (50, 100, 150, and 200 kg ha−1 of P2O5) were allocated in the plots, and in the subplots three sunflower cultivars (Aguará 06, Altis 99, and BRS 122). The phosphorus use efficiency of sunflower cultivars was estimated through agronomic efficiency, vegetative efficiency, agrophysiological efficiency, apparent recovery efficiency, and utilization efficiency. The dose of 50 kg ha−1 of P2O5 provided the best phosphorus efficiency indices for the different sunflower cultivars in the two studied crops. Cultivar Aguará 06 was more efficient in conditions with P2O5 supply below 150 kg ha−1, regardless of the crop. Sunflower cultivars had the best efficiency indices of phosphorus applied in the 2016 harvest.

O município de Mossoró-RN é considerado uns dos polos fruticultores da região Nordeste. O município apresenta constante déficit hídrico, sendo necessário o desenvolvimento da agricultura irrigada com o uso eficiente da água, sendo fundamental o manejo racional da irrigação. Este trabalho objetivou avaliar para as condições climáticas de Mossoró-RN, diferentes métodos de estimativa da evapotranspiração de referência (ETo), comparando-os com o método padrão de Penman-Monteith-FAO 56. Foi utilizada uma série de dados diários de dois anos distintos, um ano chuvoso (2011) e outro seco (2012). Os dados foram obtidos na estação meteorológica da Universidade Federal Rural do Semi-Árido (UFERSA). Foi realizada análise visando identificar os métodos que melhor se ajustam ao de Penman-Monteith-FAO 56, e para isto, foram avaliados 10 métodos mediante índices estatísticos. Destacaram-se os métodos de Penman-Original, Radiação-Temperatura e Hargreaves-Original, os quais atenderam satisfatoriamente a estimativa da ETo para o período chuvoso, enquanto que os métodos de Jensen-Haise, Radiação-Temperatura e Hargreaves-Original obtiveram desempenho satisfatório para o período seco. O método de Hargreaves-Samani não demonstrou viabilidade na utilização de estimativa da ETo, pois foi o pior método em ambos os períodos estudados, não sendo recomendado para o manejo da irrigação.

Brazil is one of the world's largest producers of melon (Cucumis melo L.), and Rio Grande do Norte and Ceará are the largest producers states of the country (99% of exports). This crop had great socio- economic importance in the Brazilian Northeast, however, it is affected by insect pests and consequently, large amounts of pesticides are applied to it, which greatly affect beneficial organisms, such as Chrysopidae. This bioassay evaluated the toxicity of nine insecticides used in commercial crops of muskmelon, applied to first- instar larvae of Chrysoperla genanigra of up to 24-hour-old, from mass rearing cultures. Sublethal effects were evaluated, classifying the insecticides into the toxicity classes recommended by the IOBC. A completely randomized design was used, consisting of ten treatments (clothianidin, pymetrozine, lambda-cyhalothrin, chlorantraniliprole, indoxacarb, pyriproxyfen, beta-cyfluthrin+imidacloprid, imidacloprid, beta-cypermethrin and a control consisted of distilled water). The treatments consisted of exposure of thirty larvae to dry residues of each product in Petri dishes, assessing their mortality, duration of instars, sex ratio, fecundity and viability of eggs from adults of the insects evaluated. The products were classified in toxicity classes as harmful (Class 4) (clothianidin, pymetrozine, indoxacarb, lambda-cyhalothrin, beta-cyfluthrin+imidacloprid, imidacloprid, beta- cypermethrin and pyriproxyfen) and innocuous (Class 1) (chlorantraniliprole) to first -instar larvae of C. genanigra, by calculate their total effect. Based on this work, chlorantraniliprole is the only recommended insecticide for use in integrated pest management (IPM) programs in muskmelon crops.