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Soil salinity affects plant growth, compromising sugarcane cultivation in regions with great production potential. Saccharum complex genotypes that respond positively to growth under saline environment can be used in the diversification of sugarcane cultivars to obtain greater economic returns. The objective of this study was to evaluate growth‐related traits of Saccharum genotypes grown under the presence and absence of salinity. The experiment was carried out in a 32 × 2 factorial scheme in a randomized block design with three replicates. The first factor consisted of 32 genotypes of the Saccharum complex and the second factor consisted of the presence and absence of salinity. The salinity provided higher mean values than the environment without salinity for plant height in the genotypes G9, G11, G13, G22 and G28, leaf number for G9 and G24, leaf area index for G9 and stem diameter for G1, G11 and G24. Among the genotypes tested, G1, G9, G11, G13, G22, G24 and G28 were the most promising genotypes and could be used for breeding new sugarcane cultivars of enhanced salinity tolerance. [ABSTRACT FROM AUTHOR]

In Brazil, grain sorghum has been mainly grown in Cerrado biome during the off‐season, as a succession crop, after the soybean harvest. At this period, rainfall is erratic and insufficient, causing drought stress in pre‐ or post‐flowering of grain sorghum crops. In this scenario, the identification of both drought‐tolerant and irrigation responsive hybrids has been one of the main targets of sorghum breeding programmes. The hypothesis of this research was that grain sorghum genotypes respond differently to different moments of water deficit. This study aimed to evaluate the agronomic performance of sorghum hybrids under full irrigation and drought stress at pre‐ and post‐flowering, in order to identify hybrids tolerant to drought stress and responsive to the water supply. Field trials were carried out in Nova Porteirinha during the 2017/2018 and 2018/2019 crop seasons. Twelve grain sorghum single‐hybrids were evaluated for days to flowering and grain yield in three water availability conditions: drought stress at pre‐flowering, drought stress at post‐flowering and full‐irrigation (control). Tolerant hybrids were identified under both pre‐ and post‐flowering drought stress, as well as hybrids responsive to irrigation. The hybrids 1G282 and 116,748 stood out in the 2017/18 season for high yield and earliness under both drought‐stress conditions, while the hybrid 1G282, AG1090, AS4625 and DKB590 stood out for the 2018/19 season in both stress condition. The hybrid A9904 and 1G282 stood out for its responsiveness to water supply, being recommended to high‐tech farming systems that employ irrigation or for in‐season cultivation. [ABSTRACT FROM AUTHOR]

The search for cotton (Gossypium hirsutum L.) genotypes gathering high yield and fiber quality is the main objective of breeding programs. The objectives of this study were: (a) to verify which effects contribute the largest fraction of the total phenotypic variance of cotton fiber quality traits and (b) to recommend the best genotypes for these traits. Eight competition trials of cotton cultivars were carried out between the 2017 and 2019 seasons. Field trials were carried out in Alagoinha (crops seasons 2017, 2018, and 2019) and Barbalha (2017 and 2018) in a randomized block design with three repetitions. Fifteen genotypes developed by the cotton plant breeding program of Embrapa Algodão were evaluated. The following fiber quality traits were evaluated: fiber percentage (FP), average boll weight (BW), upper‐half mean length, fiber uniformity (UNIF), short fiber index (SFI), fiber strength (STR), elongation (ELG), micronaire (MIC), and fiber maturity. Genotypic values (GVs) for the evaluated traits were estimated. The total phenotypic variance of the fiber quality traits evaluated is mostly composed of genotypic effects. Only the traits FP, BW, and ELG showed significant genotypes × sites interaction. The genotype G1 has high GVs for the traits FP, BW, fiber length, and fiber uniformity. The G15 stood out by gathering high values for UNIF, SFI, and STR. Core Ideas: Cotton genotypes gathering high yield and fiber quality is the main objective of breeding programs.The total phenotypic variance of the fiber quality traits evaluated is mostly composed of genotypic effects.Only the traits fiber percentage, boll weight, and elongation showed significant genotypes—sites interaction. [ABSTRACT FROM AUTHOR]

The use of silo and raffia bags for the temporary grain storage has been increasing in recent years. However, the methods for monitoring a stored product are limited to visual inspections and sampling. Thus, this research aimed to real‐time equilibrium moisture content monitoring to predict grain quality of corn stored in different conditions in silo and raffia bags using wireless sensor network prototype, Internet of Things (IoT) platform, and neural network algorithms. Experiments were conducted using corn grain with two initial water contents of 13% and 18% (w.b.), three storage environments with temperatures of 30, 23, and 17°C, and two types of packaging, that is, silo and raffia bags, for a 3‐month storage evaluation. During the monitoring of stored grain, variations in equilibrium moisture hygroscopic content were observed, which inferred changes in the corn quality. Water contents of 13% under a storage condition of 17°C showed the highest quality results, whereas storage in silo bags with water contents of 13% and 18% showed no differences at 23°C; however, at a temperature of 30°C, the grain suffered a high level of deterioration. The storage time influenced the reduction of grain quality for all factors. The physicochemical quality prediction results indicated a high coefficient of determination of the trained models, presenting itself as a promising perspective, mainly in developing embedded technologies for monitoring and predicting the qualitative variables of grain stored in silo and raffia bags. Practical Applications: The application of sensor technology and the Internet of Thing (IoT) to monitor the temperature and relative humidity of intergranular air in real time for the determination of equilibrium moisture content became possible to predict the physical and physicochemical quality of grains stored in bag silos and raffia bags using artificial neural networks (ANN) algorithms. The results obtained were satisfactory and can replace the punctual sampling of the grains mass stored in hermetic packages. The application of a set of technologies possible to monitor the grain quality in real time and predict the grain storage time in bag and raffia silos to reduce losses. [ABSTRACT FROM AUTHOR]

One of the main objectives of soybean breeding programs is the search for genotypes that are both high yielding and tolerant to abiotic stresses. Brazilian Cerrado, the main grain‐producing region in the country, is characterised by naturally acidic and low fertility soils that consequently have low base saturation. Therefore, identifying genotypes with good performance for favourable and low base saturation stress conditions is of fundamental importance for crop improvement. The objective of this study was to select F3 soybean populations for multiple traits under contrasting base saturation conditions. Field experiments were carried out in two crop seasons in randomised block design with three replicates and 10 F3 populations (P1, P2, P3, P4, P5, P6, P7, P8, P9 and P10). In the first experiment, F3 populations were evaluated without base saturation correction (V = 30%, low saturation), while in the second experiment, limestone was applied 3 months before the start to raise the base saturation to 60% (recommended saturation). We evaluated physiological, nutritional, agronomic and spectral variables. Multivariate analysis was performed to know the populations' performance and the interrelationship between variables and populations in the saturation conditions evaluated. The F3 populations showed differential performance for all traits across the conditions tested, enabling the identification of the best populations for each specific condition and both base saturation environments. Population P2 stood out under both low and recommended base saturation conditions and can be used in F4 plant selection to obtain superior lines for physiological and agronomic traits and vegetation indices. [ABSTRACT FROM AUTHOR]

Knowledge of the physiological mechanisms in saline environment may boost sugarcane breeding programmes targeting abiotic stresses. Our hypothesis is that the physiology of Saccharum genotypes responds differently under salt stress. Thus, the objective of the study was to evaluate the physiological performance of Saccharum complex genotypes grown under presence and absence of saline stress. The experimental design used was randomized blocks arranged in a 32 × 2 factorial scheme (32 genotypes × 2 salinity levels). The presence of salinity provided higher mean values for photosynthetic rate in genotypes G4, G18, G22, G25 and G29 compared with the environment without salinity, with mean values (17.26, 21.49, 24.22 and 26.19 µmol CO2m−2s−1), respectively, for internal CO2 concentration in G2, G6, G9, G14, G17, G19, G23 and G29, with mean values (323.45, 399.64, 386.88, 412.14, 366.31, 250.48, 379.10 and 380.75 µmol CO2 mol air−1), respectively, for transpiration in G18, G24, G25 and G29, with mean values (5.05, 3.30, 4.39 and 4.01 mmol H2O m−2s−1), respectively, and for chlorophyll content in G3, G5, G6, G8, G10, G13, G20, G22, G23, G25, G31 and G32, with mean values (34.18, 43.01, 38.08, 32.38, 37.09, 37.18, 32.47, 38.38, 38.04, 36.95 and 33.32 SPAD units) respectively. Genotypes that under salt stress increase their physiological performance demonstrate superiority over others and should be considered in breeding programmes. Photosynthesis and transpiration is the most adequate combination for screening, but the spad index is the most viable tool because of its ease of determination and cost. [ABSTRACT FROM AUTHOR]

Background and objectives: Adapting production factors and relating them to the effects of rice milling can contribute to obtaining better quality grains in the industry. Thus, the study had an objective to evaluate the effects of cultivars and fertilization levels in the physical, physicochemical, and morphological quality of the polished and brown rice. Findings: The starch underwent minor changes in its structure with increased fertilization levels, conserving the physicochemical rice composition for cultivar IR 431 Cl in the polished rice. However, the combination of cultivar IR 424 Cl and brown rice demonstrated positive correlations in crude protein and starch. In addition, positive correlations between the physical variables were obtained in full milling. Furthermore, brown rice had the highest percentages of whole rice in the high fertilization levels, whereas the polished grain contained the highest percentage of broken and yellow grains in the low fertilization levels. Conclusions: The rice cultivar IR 431 Cl produced with high fertilization levels had high protein and starch quality in the polished grains, while the cultivar IR 424 Cl produced high quality in brown rice. We conclude that the association of cultivars and fertilization levels in rice production obtained high rice quality according to milling type. Significance and novelty: It is possible to define the best way of milling rice in the industry to enhance the final quality, depending on the production factors adopted in the crop, such as the type of cultivar and fertilization levels. [ABSTRACT FROM AUTHOR]

The search for high‐yielding genotypes and that are tolerant to abiotic stresses has been a major goal in plant breeding. Thus, the use of technologies such as precision agriculture associated with remote sensing tools for plant phenotyping has increased. The hypothesis of this research was that soya bean genotypes respond differently to low and adequate base saturation levels in the soil and that vegetation indexes can be efficient auxiliary tools in plant phenotyping for this purpose. The objective of this study was to evaluate the nutritional status and agronomic performance of soya bean genotypes grown in low and recommended base saturation conditions using high‐throughput phenotyping. The research was carried out in 2017/2018 and 2018/2019 crop seasons, in which two field experiments in each season were installed. In experiment I, genotypes (P1, P2, P3, P4, P5, P6, P7, P8, P9 and P10) were evaluated without soil correction (low saturation condition). In experiment II, liming was performed three months before sowing of the genotypes to raise the base saturation to 60% (recommended saturation). Canopy spectral behaviour at the following wavelengths was evaluated: green (550 nm), red (660 nm), red edge (735 nm) and near‐infrared (790 nm), and the vegetation indices (Vis) NDVI, SAVI, EVI and MSAVI were calculated. The variables evaluated were leaf calcium and magnesium contents and grain yield. The use of VI's was efficient in assessing the performance of genotypes soya bean at different base saturation levels. The EVI showed moderate correlation with the nutritional and agronomic variables measured in each base saturation level. The approach used enabled both to identify genotypes tolerant to low base saturation soils and the ones with better response to liming. [ABSTRACT FROM AUTHOR]

The performance of genotypes in a wide range of environments can be affected by extensive genotype × environment (G × E) interactions, making the subdivision of the testing environments into relatively more homogeneous groups of locations (mega‐environments) a necessary strategy. The genotype main effects + genotype × environment interaction biplot method (GGE) allows identification of mega‐environments and selection of stable genotypes adapted to specific environments and mega‐environments. The objectives of this study were to identify mega‐environments regarding sorghum [Sorghum bicolor (L.) Moench] grain yield and demonstrate that the GGE biplot method can identify essential locations for conducting tests in different mega‐environments. A total of 22 competition trials of grain sorghum genotypes were conducted over three crop seasons across several production locations in Brazil. A total of 25, 22, and 30 genotypes were evaluated during the first, second, and third crop seasons, respectively. After identifying the presence of G × E interactions, the data were subjected to adaptability and stability analyses using the GGE biplot method. A phenotypic correlation network was used to express functional relationships between environments. The GGE biplot was found to be an efficient approach for identifying three mega‐environments in grain sorghum in Brazil, selecting representative and discriminative environments, and recommending more adaptive and stable grain sorghum genotypes. Core Ideas: Identifying mega‐environments in Brazil for sorghum planting, during the off‐season.Selecting representative and discriminative environments for sorghum in Brazil.Recommending more adapted and stable grain sorghum genotypes for the off‐season in Brazil. [ABSTRACT FROM AUTHOR]

The states of Mato Grosso (MT) and Mato Grosso do Sul (MS) are located in Midwest Brazil and are dependent on agribusiness, which makes their water regimes of fundamental importance. However, the existing weather stations in these states are limited, and rainfall products are therefore a valuable alternative. The objectives of this study are: (a) to validate the CHIRPS datasets for the states of MT and MS in the Brazilian Midwest region; (b) to evaluate the intraseasonal variability of regional rainfall via CHIRPS; and (c) to define the drought and wet periods on the decennial scale, based on the annual SPI. Three seasons were defined (rainy, drought, and transition), and the differences showed that the MS rainy season (56.65%) was reduced due to the veranicos that occur in February, with an increase in the percentages of the drought (13.83%) and transition (29.52%) seasons. The highest monthly rainfall occurs in the north of MS (328–390 mm), while intermediate rainfall (109–273 mm) occurs in the south of MS. This satisfactorily represents the formation of a rainfall gradient in a N–S direction during the rainy season, similar to other characterizations around the world. Based on the annual SPI assessed per decade, there were moderate droughts annually in the 1990s, 2000s, and 2010s, but not in the 1980s. There were significant differences between the decades due to the intensity and categorization of the ENSO phases (strong and moderate), and drier decades with moderate rainfall reduction in both states can be defined in the last 40 years. The data obtained via CHIRPS are satisfactory for the spatio‐temporal evaluation of regional rainfall, and for the use of SPI to detect drought and wet periods in the states of MT and MS. [ABSTRACT FROM AUTHOR]

Drought stress, salinity and aluminium toxicity are considered the most critical abiotic factors limiting the growth of soya bean plants, accounting for the low yield of the crop in the Cerrado region. Our hypothesis is that soya bean cultivars have differential morphological responses to stressful environmental conditions. Thus, an experiment was carried out with the purpose of identifying and recommending soya bean genotypes that simultaneously combine adaptability and stability for morphological traits when subjected to stressful environmental conditions. Drought, saline and aluminium stresses were induced in seeds of 25 soya bean cultivars. Seed germination, and length and dry mass of the seedlings were measured. For each trait, adaptability and stability were evaluated by the Lin & Binns method and simultaneously considering all traits for the set of environments. There was significant GxE interaction for all traits evaluated. The genotypes 97R50 IPRO, BMX Bônus IPRO and 98R31 IPRO simultaneously combine adaptability and stability for all traits measured. These genotypes can be cultivated both under optimal and abiotic stress conditions, such as those investigated in this study. Additionally, they can be used as parents in crossing blocks aiming at obtaining genotypes resistant to drought, saline and aluminium toxicity stresses. [ABSTRACT FROM AUTHOR]

The current challenge of corn (Zea mays L.) crops is to reach high yield to supply the world's demand for food, especially under different fertilization regimes and using the latest technology. We hypothesized that wavelengths and vegetation indices have a linear relationship with agronomic variables in corn. Our objectives were to verify the formation of super-traits and to study the association between wavelengths and vegetation indices with agronomic traits in corn cultivated under high and low topdressing N. The experiments were carried out in two crop seasons using a randomized block design with three replicates in a factorial scheme (11 genotypes x 2 contrasting levels of N: low, 60 kg ha-1 and high, 180 kg ha-1). At full bloom, the spectral variables green (550 nm), red (660 nm), red-edge (735 nm), and near-infrared (790 nm) and the vegetation indices normalized difference vegetation index (NDVI), normalized difference red-edge index (NDRE), green normalized difference vegetation index (GNDVI), and soil-adjusted vegetation index (SAVI) were evaluated. Agronomic traits evaluated were leaf N, plant height, first pod height, stem diameter, cob length, rows per cob, grains per row, and grain yield. Results showed that SAVI, GNDVI, NDVI, and NDRE and red-edge and red were associated with agronomic traits in corn. The association between the agronomic traits evaluated here can be used to estimate the leaf N content and corn yield. [ABSTRACT FROM AUTHOR]

Gas exchange analysis is an important technique, as the reduction in yield may be related to the decreased photosynthetic activity, due to adverse climatic factors in the growing site. The hypothesis of this study was that contrasting soil water conditions result in different photosynthetic performance in soybean genotypes. Thus, our objective was to analyse the physiological capacity in soybean genotypes under field conditions with optimal soil moisture and under water deficit. The experimental design was random blocks with 10 genotypes (P1, P2, P3, P4, P5, P6, P7, P8, P9 and P10) and three replicates. Individual analysis of variance was performed in both environments (irrigated and rainfed), and a correlation network between the traits was generated. We measured the traits net photosynthesis, stomatal conductance, internal CO2 concentration, instant water‐use efficiency, instant carboxylation efficiency and grain yield. Stressed plants reduce stomatal conductance and transpiration, but increase the instant water‐use efficiency as a defence mechanism in sub‐optimal soil moisture conditions. The P6 genotype obtained better physiological capacity under irrigated conditions, while the P10 genotype showed the better performance under rainfed conditions, which makes it tolerant to water stress. Our findings can contribute to the genotype formation and parental choice steps in breeding programs aimed at obtaining both irrigation‐responsive and drought‐tolerant genotypes. [ABSTRACT FROM AUTHOR]

The objective of this study was to evaluate the annual standardized precipitation index (SPI) obtained from the DrinC software based on multivariate analysis in the identification of rainfall and drought extremes in the State of Alagoas and its relationship with El Niño–Southern Oscillation. Monthly rainfall data from 1960 to 2016 from National Water Agency were analysed. Annual SPI (SPI‐12) has been designed for comparison with ENSO phases via Oceanic Niño Index for 3.4 region and in identifying climate extremes in the State of Alagoas. The principal component analysis and cluster analysis techniques were applied to the rainfall series of SPI‐12. Extreme events were identified in both rainy and drought periods according to SPI‐12, and were associated with the ENSO phases (El Niño, La Niña, and Neutral). The first four principal components explained 46.68% of the variance. Our findings are crucial for agriculture and civil defence since northeastern Brazil has several areas of risk and social vulnerability. [ABSTRACT FROM AUTHOR]

The effects of water and salt stress on rate of germination and seedling growth were investigated under laboratory conditions in 46 soya bean genotypes from Central‐West region of Brazil to verify how these stresses may limit crop establishment during the initial growth stage and also to identify the most tolerant genotypes to drought and salinity. Mild water and salt stresses were imposed by seed exposure to –0.20 MPa iso‐osmotic solutions with polyethylene glycol—PEG 6000 (119.57 g/L) or NaCl (2.357 g/L) for 12 days at 25°C. The germination percentage, seedling length and seedling dry matter were measured, and then, salt or drought tolerance indexes were calculated. The "NS 5909 RG," "NS 7000 IPRO," "NS 7338IPRO," "FPS Solimões RR," "NS 5151 IPRO," "SYN 13610 IPRO," "LG 60177 IPRO," "NS 6909 IPRO" and "BMX Desafio RR" were identified as the most drought‐tolerant genotypes, whereas under salinity conditions, the genotypes "5D 615 RR," "BMX Desafio RR," "5D 6215 IPRO" and "BMX Ponta IPRO" were identified as tolerant. The "BMX Desafio RR" is the genotype most adapted to both stress conditions and, therefore, should be used under conditions of water shortage and excess salt in the soil at sowing time. [ABSTRACT FROM AUTHOR]

Drought and salinity are the main limiting environmental factors that restrict the establishment of soya bean plants. In order to recommend genotypes for cultivation under adverse drought and saline stress conditions, multi‐environment trials (MET) are needed. However, MET analysis is usually performed considering a single trait, which provides lower reliability in recommending genotypes when compared to multi‐trait analysis. Thus, this study was carried out to investigate the stability of multi‐trait stability index (MTSI) in 46 soya bean cultivars under the effects of drought and saline stress on seed germination and initial seedling growth. Drought and saline stresses were imposed by seed exposure to −0.20 MPa iso‐osmotic solutions with polyethylene glycol—PEG 6000 (119.6 g/L) or NaCl (2.36 g/L) for 12 days at 25°C. The germination rate, seedling length and seedling dry matter were measured. We showed here how genotypic stability can be quantified by MTSI when comparing drought and salinity conditions in relation to non‐stressful environment (control) and how this index can be employed under different conditions. When considering the index for multiple environments, we can select as the most stable genotypes TMG 716 RR, FPS Antares RR, AS 3610 IPRO, NS 7300 IPRO and FPS Solar IPRO among the 46 tested genotypes. Owing to high stability and gains with selection verified for these genotypes under salinity and drought conditions, they can be used as genitors in breeding programs aimed at obtaining offspring with higher resistance to antibiotic stresses. [ABSTRACT FROM AUTHOR]

Most of the Brazilian soils, especially in Cerrado biome, have high acidity and toxic aluminium, making the application of limestone an indispensable technique to obtain high yield in soybean crop. The hypothesis of this study was that contrasting base saturation provides changes in water‐use efficiency (WUE) and agronomic traits of soybean populations. Thus, we evaluated the WUE and agronomic performance of F3 soybean populations under different base saturation levels. Each experiment was conducted in a randomized complete blocks design with three replicates and 10 F3 populations (P1, P2, P3, P4, P5, P6, P7, P8, P9 and P10) for two crop seasons. Segregating populations were obtained by bulk method. In the first experiment, F3 populations were evaluated without correction of base saturation (V = 30%), while in the second experiment, limestone was applied three months before sowing to increase base saturation to 60%. The traits evaluated were as follows: calcium, magnesium and potassium contents, water‐use efficiency (WUE), plant height, first pod height, main stem diameter and grain yield. Our findings indicate that WUE and agronomic performance of F3 soybean populations depends on the saturation condition. We identified the P4 and P9 populations as the most promising for use in breeding programmes aiming at higher tolerance to abiotic stress caused by low base saturation in soil. [ABSTRACT FROM AUTHOR]

Reaction norms fitted through random regression models (RRM) have been widely used in animal and plant breeding for analyses of genotype × environment (G × E) interaction. However, in annual crops, they remain unexplored. Thus, this study aimed to evaluate the applicability and efficiency of RRM fitted through Legendre polynomials as a tool to recommend cotton (Gossypium hirsutum L.) genotypes. To this end, a data set with 12 genotypes of cotton evaluated in 10 environments for fiber length (FL) and fiber fineness was used. The restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) procedure was used to estimate the variance components and to predict the genetic values. Results showed that there was genetic variability among cotton genotypes and that the reaction norms over the environmental gradient illustrated the G × E interaction. Very high selective accuracies (rĝg>0.90) were found for both traits in all environments, which indicates high reliability in the genotype's recommendation. The areas under the reaction norms were calculated for the recommendation of genotypes for unfavorable, favorable, and overall environments. Regarding genotypes recommendation, areas under reaction norms allow recommending genotypes for unfavorable and favorable environments, as well as for overall recommendation, for both traits. This study is the first considering reaction norms fitted through RRM for the recommendation of cotton genotypes and demonstrated the potential of this technique in cotton breeding, besides its great potential to deal with G × E interactions. [ABSTRACT FROM AUTHOR]

The search for high yield has identified ammonium toxicity as a problem in arable soils world wide. Ammonia toxicity can be suppressed by the use of silicon, but this fact still needs to be elucidated. Therefore, this review aimed to highlight the harmful effects of ammonium toxicity on model plants, and to determine the effects of Si on the mitigation of abiotic stress. Some plant species are considered as tolerant, and others as sensitive to high N concentrations. In sensitive plants, high ammonium concentrations may hinder the plant's development and even lead to the plant's death due to biochemical, physiological, and nutritional changes. Studies have demonstrated that silicon can mitigate or alleviate the deleterious effects caused by the toxic effect of NH4+. These findings were attributed to improvements in the physiological and nutritional parameters of plants. Given the importance of ionic balance between N forms for the plant's development, further studies must be performed to detect mechanisms promoted by Si to decrease or mitigate the harmful effects caused by excess ammonium in plants. [ABSTRACT FROM AUTHOR]

Understanding of how crop yield is influenced by interactions between the soil and environment is needed to minimize agricultural inputs and reduce the impacts of agriculture on the environment. The objective of this study was to determine the effect of soil chemical attributes, soil type, and rainfall on cotton (Gossypium hirsutum L.) yields and yield variability. In this study, the average cotton fiber yield was collected from 101 fields over nine crop seasons. In these fields, located in central Brazil, the average and standard deviation of normalized difference vegetation index (NDVI) were determined. Growing season rainfall and soil nutrients were measured. The variables analyzed were: average cotton fiber yield, NDVI from Landsat images calculated at the boll development phenological stage (enlargement and fiber filling phases), CV of the NDVI, precipitation during the cycle, and soil chemical attributes. The average field NDVI values collected at the boll development phenological stage were correlated to yield (r = 0.50; p < 0.05). Fields with a higher CV for the NDVI values generally had lower yields. The effect of precipitation depends on the cotton phenological stage and soil type. A high rainfall volume at the beginning of the cropping cycle increased plant height variability, which harmed the cotton fiber yield. The highest average values of aluminum content, aluminum saturation, and potential acidity promoted variability in cotton plant growth. Soil chemical attributes related to aluminum were negatively correlated with yield (r = -0.34; p > 0.05). [ABSTRACT FROM AUTHOR]

A gain in association was obtained by using a new multivariate index with alleles of TaALMT1 and TaMATE1B genes compared with a previously published index. Wheat is among the major grain crops. Its growth can be affected by aluminum toxicity, an important stress factor that limits plant productivity. Thus, an efficient means to select wheat genotypes that are resistant to this stress is required. Here, 172 wheat cultivars and 23 synthetic hexaploid wheat plants showing different alleles for TaALMT1 and TaMATE1B and different levels of Al resistance in field conditions (phenotyped in two crop seasons) were studied. The modified Lin and Binns method was applied to obtain the phenotype data in a multivariate manner aiming at a general identification of genotypes based on the multiple traits evaluated. The genotype x year interaction was significant for all traits that were evaluated in three growth stages (tillering, silking, and maturation). The top 20 Al-resistant genotypes obtained by the multivariate method were highlighted as having the best combination of the main desirable traits. Correlation analysis showed a gain in the association of the multivariate index with alleles of TaALMT1 and TaMATE1B genes compared with a previously published index. The superior TaMATE1B allele (having an insertion in the promoter region) contributed a greater Al resistance independent of the TaALMT1 allele. The higher association with Al resistance qualifies the selection index described in this study to be used for wheat breeding programs with the aim of improving the performance of wheat when grown under Al stress. [ABSTRACT FROM AUTHOR]

The performance of textile processes and the quality of the products depends on the several cotton (Gossypium hirsutum L.) fiber quality traits, such as micronaire index, fiber length, and fiber strength. This research aims to recommend cotton genotypes for the Brazilian Cerrado based on fiber yield and fiber quality traits. Nineteen cotton cultivar variety trials were performed in the 2013–2014 and 2014–2015 crop seasons. Each trial was conducted as a randomized complete block design with 12 treatments and four replications. The evaluated traits were fiber yield, fiber length, fiber strength, and micronaire. For each trait, a modified Lin and Binns method was used to recommend the best genotypes for all environments (favorable and unfavorable). This method was also used in a multivariate manner, aiming at a general recommendation of genotypes based on the multiple traits evaluated. The genotype × environment interaction was significant for all evaluated traits. Genotypes with high adaptability and stability were identified for each trait. The multivariate method identified IMA 08 WS and BRS 335 as the genotypes that had the best combination of main desirable traits. The analysis further revealed that new crosses could be performed between genotypes with high yield adaptability and stability and genotypes with adequate fiber quality traits. [ABSTRACT FROM AUTHOR]

Microorganisms are widely used in agriculture. Among them, the bacterial genus Bradyrhizobium is commonly found in cultivated soils, forming symbiotic relationships with legume species. This work aimed to evaluate whether co-inoculation with Bradyrhizobium japonicum and Azospirillum brasilense influences the components of production, yield, and physiological quality of soybean seeds. The experiment was conducted in three consecutive crop seasons (from 2014-2015 to 2016-2017), in the municipality of Chapadão do Sul, state of Mato Grosso do Sul, Brazil. The experiment consisted of a randomized complete block design, with seven treatments and four replications, using the following treatments: T1, control (without inoculation); T2, inoculation with B. japonicum (150 mL); T3, inoculation with A. brasilense (150 mL); T4, co-inoculation with B. japonicum + A. brasilense (75 mL + 75 mL); T5, co-inoculation with B. japonicum + A. brasilense (150 mL + 150 mL); T6, coinoculation with B. japonicum + A. brasilense (225 mL+ 225 mL); and T7, co-inoculation with B. japonicum + A. brasilense (300 mL+ 300 mL). Each treatment (dose) was applied to 50 kg of soybean seeds. The study evaluated the agronomic variables number of nodules per plant, dry shoot biomass per plant, plant height, number of pods per plant, number of seeds per plant, mass of 100 seeds, and grain yield; and the seed quality variables first germination count, germination, emergence, emergence speed index, electric conductivity, accelerated aging, and tetrazolium. The co-inoculation of soybean seeds with B. japonicum and A. brasilense benefits the development of plants, increasing yield components, grain yield, and seed quality. The most effi- cient level was 225 mL of each inoculant for 50 kg of seed. [ABSTRACT FROM AUTHOR]

Determination of the spray application rates (SAR) of crop protection products for different crops is subjective. The study aimed to develop an equation to estimate optimal spray application rates using a vegetation index (VI) and an expected relative spray deposition for summer corn crop. An experiment was performed in the crop year 2015 to 2016, and 2016 to 2017, with a plant density of 60,000 plants ha-1 with 0.45-m row spacing, under the no-tillage system, in the municipality of Chapadão do Sul. An active multispectral sensor (Crop Circle ACS-470) was used to obtain the VI Red Edge, Normalized Difference Red Edge (NDRE), and Normalized Difference Vegetation Index (NDVI), using the red, red edge, and near-infrared bands. The experiment consisted of plots subdivided in a 4 × 4 factorial scheme (four spray application rates and four phenological stages), with four replications for each treatment. The mass balance analysis measured leaf deposits. The relationship between vegetation index values and middle stratum deposits showed a quadratic trend. When the vegetation index values are increased, the spray application rate (from 40 to 100 L ha-1) needs to also increase to maintain the same spray deposition (from 50 to 100%) in the middle stratum of corn plants. The vegetative indices studied (VI Red Edge, NDRE, and NDVI) positively correlated to the spray deposition in the middle stratum of corn plants, which also depends on the SAR. Furthermore, the relationship between vegetation index and spray deposits need to be studied for other crops, plant architecture, and stand density. [ABSTRACT FROM AUTHOR]

In Brazil, cotton cultivars are tested annually in different environments at the final stages of breeding programs. Thus, identifying groups of environments with similar edaphoclimatic characteristics is crucial to determine the environments with higher discriminating ability of genotypes, known as essential environments. This work aimed to divide the Brazilian Cerrado environments into mega-environments in relation to fiber yield of cotton genotypes and identify essential environments for the conduction of trials in each mega-environment. Fiber yield was evaluated in 19 competition trials of cotton cultivars in the 2013-2014 and 2014-2015 seasons. The experimental design was a randomized block with 12 treatments and four replications. After verifying significant genotype × environment (G×E) interaction, mega-environments and essential environments were identified using the genotype + G×E (GGE) biplot method. Two mega-environments were detected. Megaenvironment 1 was formed by Santa Helena do Goias-Goiás State (GO), Primavera do Leste-Mato Grosso State (MT), and São Desidério-Bahia State (BA). Mega-environment 2 was formed by: Trindade-Minas Gerais (MG), Campo Verde-MT, Pedra Preta-MT, Luiz Eduardo Magalhães-BA, Magalhães de Almeida-Maranhão State (MA), Teresina-Piauí State (PI), and Chapadão do Sul-Mato Grosso do Sul State (MS). Primavera do Leste in mega-environment 1 and Pedra Preta in mega-environment 2 are the optimal sites to conduct trials with cotton genotypes because due to high yield discriminating ability and more representative. This information is useful for breeders to plan the next steps for trials in the Brazilian Cerrado, minimizing resources, such as labor and trial time. [ABSTRACT FROM AUTHOR]

Cowpea is one of the world's most important tropical and subtropical food sources. In Brazil, it is grown principally in three regions: the Midwest, the Northeast, and the North. This makes the genotype × environment (G×E) interaction a challenge on the recommendation of the best genotypes for these regions. The aim of this study was to use the additive main effects and multiplicative interaction model under the Bayesian approach to recommend the best genotypes for the Brazilian Midwest. Six trials using cowpea genotypes were conducted in the municipalities of Aquidauana, Chapadão do Sul, Dourados, and Primavera. The experimental design included a randomized block design with 20 treatments (17 lines and three cowpea cultivars) and four replications. We identified only two genotypes (G15 and G2) with more expressive genotypic values and whose credibility regions do not include zero. From the credibility regions built for the genotypic and environmental scores, we verify that these genotypes contributed to the G×E interaction, presenting specific adaptability to the subgroup of environments (E5, E6). These results indicate that it is not possible to carry out the general recommendation of high-yielding cowpea genotypes for the Brazilian Midwest region. [ABSTRACT FROM AUTHOR]

This study shows the relationship between the fire foci and the MCD12Q1 product (MODIS) for the land use and occupation in the state of Rio de Janeiro (SRJ) and evaluates the growth and decay of trends fire foci through nonparametric tests, applied to the number of fire foci in the 2000-2012 period. The study period was divided into (1) 2001 to 2013 for assessment of the product MCD12Q1 back for the land use and occupation and application of nonparametric tests and (2) 2000 to 2012 for the descriptive statistics (total and percentage-%) of fire foci geared for regional assessment. To evaluate growth trends and decay of fire foci, the nonparametric tests (Mann-Kendall and Pettitt) were utilized. Based on data obtained by Instituto Brasileiro de Geografia e Estatística (IBGE), the land use and occupation in the SRJ has been modified from the last two census years (1995 and 2006). The Mann-Kendall test was significant for the year 2001, with trends of 0 · 19 and 0 · 08 (Mann-Kendall). Fire foci for the years 2001 and 2013 grew with an increase of 0 · 05 and 0 · 01 per year, respectively. The Pettitt statistic test applied for the year 2001 showed that almost 70% of the studied municipalities were above the critical threshold, which has not occurred for the year 2013. The North Fluminense Region with 596 fire foci (30 · 35%) was the one with the largest number of fire foci, and the municipality of Campos dos Goytacazes was the largest contributor, with 344 fire foci (57 · 72%). The Pasturage class (MCD12Q1 product) had the biggest number of fire foci, with 354 foci (56 · 64%) in 2001 and 564 foci (42 · 28%) in 2013 and the largest amount in the north of the SRJ. The study indicated that there was a significant increase in average fire foci. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]