ABSTRACT Soybean seeds (Glycine max) were dried under real scale conditions to different final moisture content (m.c.) (9.1, 9.7, 10.9 %, and control with 16.2 %) and processed through extruding-expelling. Results indicated that soybean seed m.c. affected the composition of the soybean expeller and, thus, the oil extraction efficiency (OEE), which increased as the seed m.c. decreased. A polynomic model was proposed for predicting OEE as a function of soybean m.c., indicating that drying soybean to 10 % resulted in an OEE of approximately 65 %. A thin layer drying experiment of soybean seeds indicated that the protein dispersibility index (PDI) was not affected as regards drying air temperatures up to approximately 69 °C, and a bi-linear model with a non-pre-established break point was fitted. The real scale drying treatment in a rack type dryer (mixed flow) did not show any effect (p > 0.05) on the PDI at 80 °C, while at 115 °C a reduction (p < 0.05) was observed (PDI reduction was 0.8 and 2.1 percentage points, respectively).

ABSTRACT Termites can create structures that alter the physical and chemical properties of soils. In this process, termites are selective about the soil constituents they will use to construct their mounds. Considering the common occurrence of termite mounds in Brazilian soils, this study aimed to investigate the selective action of termites in the mound building process. Samples were collected from six termite mounds and control soils (at a distance of 15 to 30 m from the termite mound) in different regions in Brazil to analyze the fine earth fraction. The content of clay fraction, organic C and Fe in pedogenic iron oxides increased in the mounds resulting in specific surface area increments. X-ray diffraction indicated a selectivity of termites by clay-sized particles such as kaolinite, gibbsite and iron oxides (hematite and goethite) rather than larger particles such as quartz. The proportion of low-crystalline iron oxides and the maghemite amount decreased in the mounds. The change of color parameters in the termite mounds was due to a combination of increase in clay fraction, organic carbon and iron oxides. The techniques used were sensitive, indicating changes and similarities between the control soils and the termite mounds.

ABSTRACT Determining what and how much each environmental factor affects pregnancy is crucial to the sustainability and management of beef cow herds. The study evaluated through logistic regression the effect of environmental variables on the increase or reduction in the pregnancy rate of beef cows. The average pregnancy rate in the cows was 73 %, with an average age for the herd of 3.7 years. An increase in age of one year represented a 30 % increase in pregnancy, while a reduction of one year reduced the odds of pregnancy in the cows by 23 %. During the lactation period, an extra seven days’ lactation reduced the odds of pregnancy by 12 %. For every seven days that weaning was brought forward, the cows’ pregnancy odds increased by 14 %. An increase of 0.1 kg in average daily gain represented an increase of 17 % and 15 % in the odds of pregnancy during the first 60 days post-partum and 60 days to the end of the reproductive period. On the other hand, the loss of 0.1 kg in average daily gain resulted in a 14 % and 13 % reduction in the cows’ pregnancy odds, respectively. Factors such as age, the precocity of calving in the calving season, the time the calf remains with the cow and better performance in cows between calving and the end of the mating are strategies that increase the chances of pregnancy in beef cows.

ABSTRACT The Ethiopian Drylands are rich in their variety of local earthworm species. However, the category of species, and the effect of their performance on additions to plant nutrients have not been adequately evaluated. Thus, local earthworm samples were collected from the three major agroecological zones (highland, midland, and lowland) in Tigray (northern Ethiopia) and classified down to species level. Moreover, a vermicomposting experiment with four treatments (three local earthworm species, Eisenia fetida , and a conventional composting method) and three replications was established. Finally, each bin’s mature compost sample was taken to analyze plant nutrient content. The study results indicated that earthworm species in the highland, midland and lowland agroecological zones were Dendrobaena veneta, Eisenia andrie and Lumbricus rubellus , respectively. The use of these earthworms in the composting process (average of the four earthworm species) yielded higher nutrient content, ranging from 21.9 % for Sodium to 3300 % for Boron, compared to the conventional one. The highest total nitrogen (an increase of 44.4 %) and organic carbon (an increase of 33.4 %) were recorded in the Eisenia fetida and Dendrobaena veneta treated bins, respectively. Composting with Eisenia andrie has resulted in increases in P (96.1 %), K (125 %), Mg (83 %) and all micro-nutrients (between 91 % for Zn and 4400 % for B). Both Eisenia andrie and Lumbricus rubellus species contributed to the increased additions of Sulfur (85.7 %) compared to the control. It can be concluded that the use of local earthworms (particularly Eisenia andrie) in the composting process plays a significant role in plant nutrient addition.

ABSTRACT Stony soils have been increasingly used for agriculture production; however, little is known about their hydraulic properties due to problems, such as sample deformation and hydraulic continuity between samples and suction devices when the sampling and measurements are accomplished with traditional techniques. In this study, the traditional ring sampling technique was replaced by the sampling of undisturbed soil blocks coated with paraffin wax to preserve their structure. A saturated paste of fine-grained mineral particles was used to ensure contact and hydraulic continuity between samples and suction devices (sand table and ceramic plates). This allowed us to determine 30 water retention curves for three stony soils with coarse particle contents (> 2 mm) ranging from zero to 69 %. The van Genuchten model was fitted to the measured retention data and the root mean square errors were between 0.0034 and 0.0331 m3 m–3, with no outliers or odd behavior in the retention curves. These results showed that consistent water retention curves for stony soils can be determined with the technique proposed. Fine-grained minerals sandwiched between the surface of suctions sources and sampled blocks improve hydraulic continuity between them. These techniques can be applied to determine water retention properties in structured soil samples with coarse particles where it is unfeasible to collect structured soil samples with metal sampling rings.

ABSTRACT Protein quality is related to amino acid composition and digestibility. Accurate evaluation of apparent digestibility coefficients (ADCs) of nutrients in commonly used feedstuffs is paramount for formulating efficient aquafeed. ADCs of soybean meal (SBM) and poultry by-product meal (PBM) were evaluated using reference diets formulated with two types of ingredients (semi-purified [SP] and practical [P]) for juvenile Nile tilapia ( Oreochromis niloticus, Linnaeus) of the GIFT strain. Groups of 20 juveniles (65.05 ± 12.37 g) were fed twice a day to apparent satiety with one of the four experimental diets (SBM-SP, SBM-P, PBM-SP, and PBM-P) in quadruplicate for 30 days. After the last feeding, feces were collected by siphoning hourly and the ADCs of dry matter, protein, and amino acids (AAs) were calculated. Nile tilapia exhibited a high capacity to digest SBM and PBM, with most ADCs exceeding 90 %. The type of reference diet affected the ADCs of protein and AAs on the test ingredients, with the SP reference diet providing the highest ADC, mainly in SBM. Digestibility data generated with a P-type reference diet demonstrated more practical relevance than those generated with an SP-type reference diet. They can be applied in digestibility studies for Nile tilapia.

ABSTRACT This study aimed to determine the efficacy of a finishing diet added with sugar beet pulp to reduce backfat skatole of entire male pigs, using the optimised high-performance liquid chromatographic (HPLC) method. The study comprised 72 males Pietrain (Large White × Landrace), divided into two groups of 36 animals each. Pigs in group A (treatment) were fed a supplemented formula (addition of 10 % beet pulp). while animals in group B (control) received a commercial feed, both for a period of 14 days before slaughter. The isocratic HPLC method achieved the chromatographic separation of indolic compounds in approximately 3 min. Skatole was significantly lower ( p = 0.002) in group A, showing that beet root supplementation reduced skatole levels in pig fat. In addition, the optimised HPLC method was reliable, less time-consuming, and showed a resolution suitable for small amounts of skatole.

ABSTRACT Most commercial apple orchards are established on either Marubakaido (Malus prunifolia Borkh.) (high vigor), M-9 (Malus pumila) (low vigor), or a combination of both rootstocks through the intergrafting technique. The Geneva® Series rootstocks were developed as an alternative to orchards modernization. The vigor of rootstocks influences the anatomical xylem formation and, therefore, the canopy cultivar’s hydraulic conductivity. When affected by embolism, hydraulic conductivity harms plant metabolism, reducing crop yield and fruit quality. This study aimed to evaluate four Geneva® Series rootstocks with potential use in southern Brazil, in terms of hydraulic conductivity (K) and percentage loss of conductance (PLC), during the winter period in two different years. The G.213 rootstock presented the best performance for the variables analyzed; however, higher values of xylem functionality loss were observed in G.814.

ABSTRACT Due to its high nutritional value, broccoli (Brassica oleracea var. italica Plenck) is one of the most popular vegetables worldwide. This study assessed 36 phenotypic characteristics of 111 broccoli varieties to understand the phenotypic diversity of new broccoli varieties and improve their breeding speed with advantages and characteristics in China, including 108 new varieties and three varieties of common knowledge. The genetic diversity, the principal component, and the cluster of phenotypic characteristics of broccoli varieties were further investigated. The results showed that the coefficients of variation of 36 characteristics ranged between 11.18 % and 94.99 %, with their diversity index between 0.26 and 1.82. The 111 broccoli varieties were further classified into eight groups, primarily attributed to the differences in phenotypic characteristics, including curd weight, main stem thickness, plant development degree, plant height, and anthocyanin coloration. The cumulative contribution rate of the first five principal components reached 81.186 %, corresponding to 12 representative phenotypic traits. The analysis indicated that the phenotypic characteristics of broccoli were rich in diversity, especially for several characteristics appreciated by the market, such as weight, curd firmness, and anthocyanin coloration. This study revealed the basic information on the genetic diversity of new broccoli varieties in China from 2017 to 2019 and provided potential breeding strategies for broccoli to meet diverse market demands.

ABSTRACT Regression analysis is highly relevant to agricultural sciences since many of the factors studied are quantitative. Researchers have generally used polynomial models to explain their experimental results, mainly because much of the existing software perform this analysis and a lack of knowledge of other models. On the other hand, many of the natural phenomena do not present such behavior; nevertheless, the use of non-linear models is costly and requires advanced knowledge of language programming such as R. Thus, this work presents several regression models found in scientific studies, implementing them in the form of an R package called AgroReg. The package comprises 44 analysis functions with 66 regression models such as polynomial, non-parametric (loess), segmented, logistic, exponential, and logarithmic, among others. The functions provide the coefficient of determination (R2), model coefficients and the respective p-values from the t-test, root mean square error (RMSE), Akaike’s information criterion (AIC), Bayesian information criterion (BIC), maximum and minimum predicted values, and the regression plot. Furthermore, other measures of model quality and graphical analysis of residuals are also included. The package can be downloaded from the CRAN repository using the command: install.packages(“AgroReg”). AgroReg is a promising analysis tool in agricultural research on account of its user-friendly and straightforward functions that allow for fast and efficient data processing with greater reliability and relevant information.

ABSTRACT Top-quality pellets can significantly increase density and durability of agricultural residues, reducing logistic costs. However, these pellets depend on numerous parameters, including feedstock properties and production conditions. To ensure high-quality pellets, a single-factor experiment and the response surface methodology were used to investigate the effects of particle size, moisture content, molding pressure, pelleting time, ultrasonic power, and interaction effects between variables on density and durability of pellets for ultrasonic vibration-assisted pelleting of corn stover. The response surface models between variables and response were established. The results showed that all variables affect the density and durability of pellets. An optimal condition for density and durability was obtained, and a further experiment was conducted to validate the values. The results suggested that desirability (0.999) under optimal conditions confirmed the validation of models. The optimal combination of process parameters included particle size of 1.5 mm, moisture content of 10 %, molding pressure of 379 kPa, pelleting time of 80 s, ultrasonic power of 250 W, with values of 1,381.14 kg m–3 and 97.58 % for density and durability of pellets, respectively.

ABSTRACT The present study explored the predictive values of milk leukocyte differentials (MLD) as a basis for improving the diagnosis of intramammary infections (IMIs) and subclinical mastitis. Quarter milk samples were collected for bacteriological analysis, quarter somatic cell count (qSCC), and MLD. The MLD were assessed using the cytospin technique, direct microscopic smears, and flow cytometry. The predictive values of each single leukocyte population and useful potential indices that could better reflect immune complexity were also calculated. Changes in the percentage of any leukocyte alone failed to substantially improve the predictive value of qSCC in diagnosing IMIs. Although certain parameters increased the area under the receiver operating characteristic curve (ROC curve) as a result of increased specificity values, a slight reduction in sensitivity was observed. The so-called CD8 complex was a unique parameter which improved both the sensitivity (78.79 %) and the specificity (80.77 %) in IMI diagnosis, resulting in the highest area under the ROC curve (0.87). To diagnose subclinical mastitis, the percentage of macrophages and the sum of the percentage PMNLs and T CD8+ cells divided by the percentage of macrophages showed the highest predictive values (sensitivity = 79.63, specificity = 73.68, and area under the ROC curve = 0.83) in the differentiation of the inflammatory condition status of cows. In conclusion, this study provides further insights into using T CD8+ lymphocytes in diagnosing bovine IMIs, combined with PMNLs and macrophages. The antidromic trend of macrophages vs. PMNLs and T CD8+ lymphocytes due to the increasing qSCCs was crucial to differentiating quarters under both inflammatory and non-inflammatory conditions.

ABSTRACT: Microbial biodiversity of an environment can contribute to plant growth and increase crop yield. Plant extracts from soybean (Glycine max (L.) Merrill) were investigated on soybean plants grown after inoculation with these extracts. Soil samples were collected from two important Brazilian soybean-growing regions to produce the extracts used in the experiments. The extracts were produced with material collected from aboveground biomass and rhizosphere of soybean plants cultivated in a controlled greenhouse (phase 1). The extracts produced in phase 1 were applied in a sequential experiment (phase 2). Phase 2 was conducted to examine the plant microbiome after the microbial alteration process in the greenhouse through seed inoculation with the extracts produced previously. Samples of aboveground biomass were collected to determine root dry matter and crop yield. Bacterial 16S rRNA sequences were processed to determine the final microbial content of soybean. The inoculated treatments had lower species diversity; however, the phyla Firmicutes and Bacteroidetes were more abundant in the treatments than in the non-inoculated treatment. The soybean plant stem in the inoculated treatment also had a positive response to enrichment of the bacterial classes Betaproteobacteria, Bacilli and Flavobacteria. Inoculation affected the microbial composition of soybean plants. The alteration of microbiome changes revealed differences for crop yield between the inoculated and non-inoculated treatments, with up to 93.5 % higher crop yields per plant according to the extract applied.