ABSTRACT In subsurface drip irrigation systems, knowledge of the three-dimensional advancement of water in the soil is essential for selecting emitter spacing and installation depth. This research aimed to develop and test different mathematical models to estimate water distribution in the soil under subsurface drip irrigation. The experiment was set up in a completely randomized design with four replicates. The experimental arrangement was of split-plot in time, with different dripper installation depths in the plots (0, 5, 10, 15, 20, 25, and 30 cm) and in the subplots irrigation application times (0, 60, 120, 180, and 240 min). Three models (SLIDE 6.0, polynomial regression, and SPSS 2.0) were constructed to estimate the water distribution in the soil profile. All models showed statistical indexes within acceptable ranges. In comparison, the model generated in the numerical software SLIDE 6.0 was the one that presented the best performance, followed by SPSS 2.0 and polynomial regression. The generated models were efficient and simple, producing good results in predicting the water distribution in the soil profile under the studied conditions. systems threedimensional three dimensional depth replicates splitplot split plot time 0, 0 (0 5 10 15 20 25 3 cm 60 120 180 24 min. min . min) 6 regression 2 ranges comparison 6. performance 2. simple conditions ( 1 12 18

RESUMO Em sistemas de irrigação por gotejamento subsuperficial, o conhecimento do avanço tridimensional da água no solo é essencial na seleção do espaçamento e profundidade de instalação dos emissores. O objetivo desta pesquisa foi desenvolver e testar diferentes modelos matemáticos para estimar a distribuição de água no solo sob irrigação por gotejamento subsuperficial. O experimento foi montado em delineamento inteiramente casualizado com quatro repetições. O arranjo experimental foi de parcelas subdivididas no tempo, tendo nas parcelas diferentes profundidades de instalação de gotejadoras (0, 5, 10, 15, 20, 25 e 30 cm) e nas subparcelas tempos de aplicação da irrigação (0, 60, 120, 180 e 240 min). Foram construídos três modelos (SLIDE 6.0, regressão polinomial e SPSS 2.0) para estimar a distribuição de água no perfil do solo. Todos os modelos apresentaram índices estatísticos dentro de faixas aceitáveis. Na comparação, o modelo gerado no software numérico SLIDE 6.0 foi o que apresentou melhor desempenho, seguido do SPSS 2.0 e regressão polinomial. Os modelos gerados foram eficientes e simples, apresentando bons resultados na predição da distribuição de água no perfil do solo para as condições estudadas. subsuperficial emissores repetições tempo 0, 0 (0 5 10 15 20 2 3 cm 60 120 18 24 min. min . min) 6 aceitáveis comparação 6. desempenho 2. simples estudadas ( 1 12

ABSTRACT The collapse of the Fundão Dam in Mariana, MG, in 2015 introduced the challenge of using Technosol, a soil type formed by deposition of iron mining waste along the Doce River banks, for agricultural purposes. This study aimed to determine the optimal water depth for enhancing production of tropical forage, Megathyrsus maximus cv. Mombasa, when grown on iron ore tailings. Additionally, it sought to establish a crop coefficient applicable to the edaphoclimatic conditions of Viçosa, MG, Brazil. The experiment was conducted throughout the summer, fall, and winter of 2022, employing 21 drainage lysimeters. A completely randomized experimental design was adopted, featuring six treatment groups (plants in Technosol receiving water depths ranging from 20 to 120% of the crop’s evapotranspiration, as derived from the control treatment), along with a control group (plants in Latosol with a depth of 100%), each with three repetitions. Our findings showed that irrigation must replace 40% of the crop evapotranspiration. Moreover, cultivating in Technosol resulted in a reduction of productive capacity by 37.39% during the summer/fall and fall seasons. For Mombasa grass grown in Oxisol, crop coefficients of 1.2 during the summer and 1.5 during the fall and winter are advised. Mariana MG 201 banks purposes forage cv tailings Additionally Viçosa Brazil 2022 2 lysimeters adopted plants 120 crops s evapotranspiration treatment, , treatment) 100%, 100 100% 100%) repetitions 40 Moreover 3739 37 39 37.39 summerfall seasons Oxisol 12 1 1. 15 5 advised 202 10 4 373 3 37.3 37.

RESUMO O rompimento da Barragem do Fundão em Mariana, MG, ocorrida em 2015, trouxe o desafio de usar o Tecnossolo (tipo de solo) formado pela deposição do rejeito de mineração de ferro nas margens do Rio Doce para agricultura. O objetivo desta pesquisa foi obter a lâmina de água para otimizar a produção da forragem tropical Megathyrsus maximum cv. Mombaça, cultivada em rejeito de mineração de ferro e determinar seu coeficiente de cultura para as condições edafoclimáticas de Viçosa, MG. O experimento foi realizado durante as estações de verão, outono e inverno do ano de 2022, com a utilização de 21 lisímetros de drenagem. O experimento foi distribuído em delineamento inteiramente casualizado com 6 tratamentos (plantas em Tecnossolo com lâminas variando de 20 a 120% da evapotranspiração da cultura, obtida do tratamento-testemunha) e adição de uma testemunha (plantas em Latossolo com lâmina de 100%) com três repetições. Recomenda-se irrigação com reposição de 40% da evapotranspiração da cultura. O cultivo em Tecnossolo diminuiu a capacidade produtiva em 37,39% nos ciclos das estações do verão/outono e outono. Recomenda-se os coeficientes de cultura de 1,2 no verão e 1,5 no outono e no inverno, para o capim-Mombaça cultivado em um Latossolo. Mariana MG 2015 tipo solo agricultura cv Mombaça Viçosa 2022 2 drenagem plantas 120 tratamentotestemunha tratamento tratamento-testemunha 100% 100 repetições Recomendase Recomenda se 40 3739 37 39 37,39 verãooutono 12 1 1, 15 5 capimMombaça capim 201 202 10 4 373 3 37,3 37,

ABSTRACT This efficiency in the application of water is associated with the evolution of irrigation equipment and systems and can be illustrated by the drippers in the case of localized irrigation, the sprinklers in the case of sprinkler irrigation, and the low-pressure emitters used in a central pivot. Given the context presented, this study aimed to carry out a theoretical approach on the classification and use of emitters used in pressurized sprinkler irrigation systems, carrying out bibliographical research on the subject. The research is exploratory, where articles and books with related subjects were researched: “classification and use of emitters used in pressurized sprinkler irrigation systems”. The research was carried out via the Google Academic platform and in libraries. The type of emitter to be chosen depends on many factors that influence the efficiency of the system. Therefore, a well-designed project, with the correct choice of the type of emitter, maximizes the application efficiency, minimizes energy expenditure, and increases the producer's profitability. lowpressure low pressure pivot presented subject exploratory researched systems. . systems” libraries system Therefore welldesigned well designed project expenditure producers producer s profitability

ABSTRACT The collapse of the Fundão dam in Brazil caused one of the biggest environmental disasters. One of the challenges was how to manage the tailings so that affected areas could be reused. This study aimed to verify whether applying different irrigation depths to Xaraés grass grown with iron mining tailings would affect grass shoot and root dry masses. The experiment was set up in a randomized design with five irrigation depths (40%, 60%, 80%, 100%, and 120% of crop evapotranspiration) and two additional treatments (grass grown in tailings with soil conditioner, and grass grown in natural soil), each with three repetitions. The grass was cut four times, and the shoot dry mass was evaluated after each cut, while the root dry mass was evaluated at the end of the experiment. Our results showed that irrigation depths had a positive linear effect on shoot dry mass and an exponentially increasing effect on root dry mass, with the highest averages in the treatment applying 120% of crop evapotranspiration. This study showed that even in adverse conditions, Xaraés grass was able to grow and develop well. disasters reused masses 40%, 40 (40% 60 60% 80 80% 100 100% 120 evapotranspiration conditioner soil, , soil) repetitions times conditions well 40% 4 (40 6 8 10 12 (4 1 (

Abstract Among agricultural components, crop ecophysiological parameters play an essential role in garlic growth and yield. This study aimed to characterize the structure and spatialization of garlic crop parameters, evaluating spatial correlations among yield, lateral shoot growth, and plant ecophysiological components. These consisted of intercellular CO2 concentration, stomatal conductance, transpiration, water-use efficiency, carboxylation efficiency, photosynthetically active radiation, relative humidity around leaves, relative humidity in leaves, air temperature, leaf temperature, vapor pressure deficit, and water content in the air and leaves. Our results showed that irrigated purple garlic yield, lateral shoot growth, and ecophysiological components are spatially dependent. A cross-semivariogram between plant ecophysiological parameters showed negative spatial correlations and spatial dependence, with a coefficient of determination (r2) above 0.730. These findings indicate a close correlation between garlic yield and lateral shoot growth with the ecophysiological parameters studied. In short, purple garlic production had a high inter-spatial correlation with plant transpiration and water contents in the air and leaves.

ABSTRACT Peanut (Arachis hypogaea L.) is a legume belonging to the Fabaceae family, whose production aims at high pod yields and quality. This study aimed to investigate peanut physical traits and point out their relationship with total pod mass. Therefore, we evaluated total pod mass and the pod physical components: grain mass, pod shell mass, pod length, greatest and smallest transverse pod diameters, number of grains per pod, pod area, pod perimeter, and fruit volume. Initially, these morphological variables were correlated by Pearson’s coefficient, and a correlation network was used to graphically express the obtained results. Path analysis identified that pod total mass has a cause-and-effect relationship with the variables number of grains per pod, grain mass, and pod shell mass. As a result, these variables can be used in indirect selection for higher crop yields; therefore, monitoring pod total mass before harvest is a strategy to predict the final yield of peanuts.

ABSTRACT Iron mining tailings have limitations for plant growth and development due to low fertility, coupled with great restriction of physical characteristics such as low water retention, high density, and lack of structure. This study aimed to evaluate whether different irrigation depths applied to Xaraés grass grown in mining tailings influence its yield and bromatological aspects. The experiment was carried out in a completely randomized design with five irrigation depths (40, 60, 80, 100, and 120% of the crop evapotranspiration), two additional treatments consisting of grass grown in tailings with soil conditioner and in natural soil, and three repetitions. Forage dry mass, plant height, leaf: stem ratio, as well as neutral detergent fibre, acid detergent fibre, crude protein, and mineral matter content, were evaluated during four cutting cycles. Xaraés grass could establish and produce forage despite cultivation limitations in iron mining tailings, which are due to their properties. Irrigation depths showed positive and linear effects on Xaraés grass dry matter yield and heights of plants grown in iron mining tailings. The soil conditioner has potential for use in pasture cultivation in iron mining tailing.

ABSTRACT Studies that seek to identify a smaller number of soil attributes that represent others can generate less expenditure of time and financial resources for monitoring cultivated areas. Thus, this study aimed to analyze the spatial distribution and spatial autocorrelation of physical attributes of an Oxisol (Latossolo Vermelho Amarelo, Brazilian Soil Classification System). The evaluated attributes consisted of soil density (SD), total porosity (TP), free porosity (FP), field capacity (FC), permanent wilt point (PW), and total water availability (TW). Semivariogram adjustments and semivariance estimates were performed to characterize the structure and magnitude of the spatial dependence of soil attributes. The attributes were distributed on thematic maps and the spatial autocorrelation was estimated by the Moran index, which quantifies the degree of autocorrelation. TP showed a high positive correlation with PWP. Soil TW showed a high positive correlation with SD and a high negative correlation with FP. In turn, FP showed a high negative correlation with SD. The results showed spatial dependence for all attributes, standing out the apparent soil density and permanent wilt point, which were good evaluators of strong spatial dependence.

Abstract The Penman-Monteith equation is recommended for the estimation of reference evapotranspiration (ETo). However, it requires meteorological data that are commonly unavailable. Thus, this study evaluates artificial neural network (ANN), multivariate adaptive regression splines (MARS), and the original and calibrated Hargreaves-Samani (HS) and Penman-Monteith temperature (PMT) equations for the estimation of daily ETo using temperature. Two scenarios were considered: (i) local, models were calibrated/developed and evaluated using data from individual weather stations; (ii) regional, models were calibrated/developed using pooled data from several stations and evaluated independently in each one. Local models were also evaluated outside the calibration/training station. Data from 9 stations were used. The original PMT outperformed the original HS, but after local or regional calibrations, they performed similarly. The locally calibrated equations and the local machine learning models exhibited higher performances than their regional versions. However, the regional models had higher generalization capacity, with a more stable performance between stations. The machine learning models performed better than the equations evaluated. When comparing the ANN models with the HS equation, mean RMSE reduced from 0.96 to 0.87 and from 0.84 to 0.73, in regional and local scenarios, respectively. ANN and MARS performed similarly, with a slight advantage for ANN.

Abstract Background: Weeds reduce water use efficiency in crops due to water used by the weed and to the reduction in crop yield. In addition to the usual presence of weeds in the interrow of different crops, the management of these plants has moved away from the idea of total control. Thus, the amount of water lost through the evapotranspiration of weeds (ETW) must be understood. Objective: Determine the water use and crop coefficient (Kc) of the weed species Commelina diffusa, Cyperus rotundus, and Cynodon dactylon using drainage lysimeters associate with the Normalized Difference Vegetation Index (NDVI). Methods: The experiment was carried out at the Lysimetric Station of the Federal University of Viçosa, in Viçosa-MG, in a randomized block design, with four treatments and four replicates. Reference evapotranspiration (ETo), necessary to calculate Kc, was obtained in situ through lysimeters cultivated with Paspalum notatum. Results: The highest Kc values were found in the final third of the experimental cycle, equal to 1.32, 0.93, and 0.90 for C. diffusa, C. rotundus, and C. dactylon, respectively. The NDVI showed a good correlation with Kc and biomass, with R2 ranging from 30.9 to 54.6% and from 46.1 to 63.1%, respectively. Accumulated ETW values ranged from 336 to 473 mm, with C. diffusa showing the highest water consumption, followed by C. rotundus and C. dactylon. Conclusions: C. diffusa has higher Kc and water consumption than C. rotundus and C. dactylon. NDVI can be used in the estimation of the Kc and biomass of weeds.

Abstract Optimization of water use for irrigation will only be possible with the adjustment of management, which is directly related to the correct estimate of the actual evapotranspiration of the crop. The present study aimed to evaluate different mathematical approaches used in estimating the actual evapotranspiration of a new soybean cultivar (BRS 7581RR) subjected to different water deficit conditions. For this, the ETa estimated by the FAO56 Dual, Jensen and Hermann, AquaCrop and Ritchie models was evaluated. The experimental design was randomized with five treatments and four replicates. Irrigation management in the treatments was conducted so as to maintain different levels of water available in the soil (AW). The T1 treatment was performed applying 80 to 100% AW; in T2 treatment, the allowed variation was 60 to 80% AW; in T3 treatment, it was 40 to 60% AW; in T4, from 20 to 40% AW; and in T5, from 0 to 20% AW. The results showed that the FAO56 Dual model showed better performance in soybean ETa estimation for winter conditions in most treatments, with NSE ranging from 0.42 to 0.83. In the summer, the Jensen and Hermann model showed the best results, with NSE ranging from 0.70 to 0.94.

RESUMO Em regiões onde a área irrigada é crescente e a disponibilidade hídrica é reduzida, como o Oeste do Estado da Bahia, Brasil, o emprego de técnicas que contribuam para melhorar a eficiência de uso de água é primordial. Uma das formas de melhor adequação da irrigação é através da melhoria do cálculo da evapotranspiração atual (ETa), que entre outros fatores, é influenciada pelo secamento do solo, sendo importante entender essa relação, que geralmente é contabilizada nos modelos de manejo de irrigação por meio do coeficiente de estresse hídrico (Ks). Este estudo objetivou estimar o coeficiente de estresse hídrico (Ks) por meio de informações obtidas via sensoriamento remoto, combinadas com informações de campo. Para isto, realizou-se um estudo no município de São Desidério, área localizada no Oeste da Bahia, utilizando imagens do satélite Landsat-8. O Ks foi calculado pela relação entre a evapotranspiração da cultura e a ETa, calculada pelo Simple Algorithm for Evapotranspiration Retrieving (SAFER). O Ks estimado por sensoriamento remoto apresentou para os estádios em desenvolvimento e médio, erros médios da ordem de 5,50%. No estádio final de desenvolvimento do milho os erros obtidos foram de 23,2%.

ABSTRACT In regions where the irrigated area is increasing and water availability is reduced, such as the West of the Bahia state, Brazil, the use of techniques that contribute to improving water use efficiency is paramount. One of the ways to improve irrigation is by improving the calculation of actual evapotranspiration (ETa), which among other factors is influenced by soil drying, so it is important to understand this relationship, which is usually accounted for in irrigation management models through the water stress coefficient (Ks). This study aimed to estimate the water stress coefficient (Ks) through information obtained via remote sensing, combined with field data. For this, a study was carried out in the municipality of São Desidério, an area located in western Bahia, using images of the Landsat-8 satellite. Ks was calculated by the relationship between crop evapotranspiration and ETa, calculated by the Simple Algorithm for Evapotranspiration Retrieving (SAFER). The Ks estimated by remote sensing showed, for the development and medium stages, average errors on the order of 5.50%. In the final stage of maize development, the errors obtained were of 23.2%.

ABSTRACT Monitoring of large agricultural lands is often hampered by data collection logistics at field level. To solve such a problem, remote sensing techniques have been used to estimate vegetation indices, which can subsidize crop management decision-making. Therefore, this study aimed to select vegetation indices to detect variability in irrigated corn crops. Data were collected in São Desidério, Bahia State (Brazil), using an OLI sensor (Operational Land Imager) embedded to a Landsat-8 satellite platform. Five corn growing plots under central pivot irrigation were assessed. The following vegetation indices were tested: NDVI (Normalized Difference Vegetation Index), EVI (Enhanced Vegetation Index), SAVI (Soil Adjusted Vegetation Index), GNDVI (Green Normalized Difference Vegetation Index), SR (Simple Ratio), NDWI (Normalized Difference Water Index), and MSI (Moisture Stress Index). Among the tested indices, SR was more sensitive to high corn biomass, while GNDVI, NDVI, EVI, and SAVI were more sensitive to low values. Overall, all indices were found to be concordant with each other, with high correlations among them. Despite this, the use of a set of these indices is advisable since some respond better to certain peculiarities than others.

ABSTRACT Correct determinations of distribution (Ed) and application (EA) efficiencies allow adequate estimations of the gross irrigation depth. This study aimed: i) to determine the distribution efficiency using the Christiansen uniformity coefficient (CUC) in a sprinkler irrigation system under different weather conditions and working pressures; ii) to compare the mean, median, and cumulative CUC values; and iii) to evaluate the predictive capacity of four EA estimation models. CUC values were determined from 80 assessments, as well as the mean, median, and cumulative. The precipitated water depth accumulated in each collector was considered for the accumulated CUC. More uniform evaluations were used for EA (working pressure of 196 kPa), resulting in 20 samples. Besides being measured, EA was estimated by Keller & Bliesner, Playán, Tarjuelo, and Beskow methods. Statistical indicators were the root mean square error, mean bias error, Willmott agreement index, mean absolute error, and Pearson correlation coefficient. CUC values ranged from 66.51 to 92.04%, and the accumulated CUC provided an improvement over the isolated evaluations. The Beskow model had the best EA estimations in conventional spraying.

ABSTRACT Surface temperature (Ts) is a determining factor to obtain energy balance parameters, being relevant to understand the influence of this variable on the estimation of evapotranspiration. Thus, the objective of this study was to simulate errors in Ts estimation to verify the consequences of actual evapotranspiration (ETa) estimated by the SAFER (Simple Algorithm for Evapotranspiration Retrieving) model. For this, an image of the Landsat-8 satellite was used to induce errors from 0.2K to 10K in the variable Ts, allowing verifying the consequences in the ETa data. After the estimations of Ts and ETa, the quantitative consequences and dynamics of Ts impact on the ETa data were verified along the different land uses in the study area. The results showed that the precise estimation of Ts is essential to obtain ETa accurately. The image of ETa errors presented the highest relative errors on the surface with exposed soils and with high Ts values. However, the highest residuals of ETa images occurred on the surfaces with milder Ts and higher evapotranspiration rates (irrigated surfaces).