The objective was to evaluate the influence of supplementation of L-arginine at 10g/kg on the performance of lactating sows and their litters by evaluating the milk amino acid composition, serum hormone levels, mammary tissue redox status indicators, mammary tissue histomorphology, and the expression of genes related to mammary gland metabolism. The study was conducted in the municipality of Oliveira, Minas Gerais, Brazil, in 2019. A total of 24 sows were selected. A completely randomized design was used in a 2 × 3 factorial arrangement, with two diets (control and 10g L-arginine/kg) and three mammary gland positions (thoracic, abdominal and inguinal), totaling six treatment groups. Each dietary treatment consisted of 12 replicates, with each replicate equivalent to one experimental unit, which was considered a sow and its litter. Females that were fed a diet supplemented with L-arginine had lower feed intake and greater weight loss. Piglets from sows that received L-arginine supplementation presented reduced weaning weight variation. L-arginine supplementation did not affect the amino acid composition of the milk, the plasma hormone levels of the sows, the oxidative stress parameters of redox, or breast tissue morphology. However, it may modulate the expression of genes important for mammary gland metabolism, such as the COX1 and SLC27A4. Piglets that suckled teats in the thoracic and abdominal positions had higher mean weights at 14 and 23 days, as well as greater daily weight gains. L-arginine supplementation to sows improves litter quality by increasing weaning weight uniformity; piglets that occupy the thoracic and abdominal positions perform better.

The facilities where the livestock carry their production cycle must have as main characteristic the control of influence of variation of environmental factors on the animals, which can be controlled through the use of different ventilation systems. In this way, the objective of this research was to evaluate the influence of different conditioning systems in the swine farrowing house. Three treatments were tested in a farrowing house located in Parana, Brazil: refrigerated ventilation (T1), forced ventilation (T2) and natural ventilation (T3), on 12 females with 11 piglets each. The climatic parameters evaluated were temperature, velocity and relative humidity of the air. For the females were analysed the parameters: surface temperature (laser thermometer and thermal image), average weight and feed conversion at the end of lactation; and for the piglets: surface temperature (thermal image), average weight and weekly feed conversion. The data were interpreted statistically by analysis of variance and Tukey’s test with 5% probability of error, using the program SAS (2008). The use of the refrigerated ventilation system decreased the temperature of the air and the superficial temperature of the females, without affecting the comfort of the piglets. There was no difference in the productive indexes of the animals, thus other aspects of the production chain could be explored to reflect a higher financial gain.

Agriculture, as the largest consumer of freshwater, plays a crucial role in managing limited water resources. However, uncertainties in water supply, particularly in water-scarce regions, hinder further agricultural development. Balancing agricultural development with environmental sustainability is especially demanding in the Karkheh River Basin (KRB), western Iran. Traditional irrigation networks in the upper KRB are inefficient, exacerbated by unregulated water use and over-extraction. This study explores the Water Supply-Demand Balance (WSDB) dynamics under current cropping patterns in the semi-arid Honam sub-basin of the upper KRB. Time-series Landsat imagery and Machine Learning (ML) algorithms classified crop types and estimated major crop cultivation area during 2019-2021. Regional Crop Water Requirement (ETcreg) and Regional Net Irrigation Requirement (INETreg) estimated the Regional Gross Irrigation Water Demand (GIWDreg), while inflow-outflow analyses determined Surface Irrigation Water Supply (SIWS). The study achieved high crop classification accuracy, facilitating precise water demand estimation across large-scale traditional irrigation networks. Results indicated the highest GIWDreg in 2020 (11.3 × 106 m3/year), driven by increased forage cultivation with crop water requirements (ETc) exceeding 1000 mm. That year also recorded the maximum SIWS (14.8 × 106 m3/year). The Water Scarcity Index (WSI) classified shortages as severe to extreme, indicating WSDB instability due to drought and cropping pattern shifts. This study highlights the necessity for government initiatives promoting water-efficient cropping to align agriculture with water availability. The proposed approach offers practical insights for policymakers seeking to optimize food security while ensuring sustainable water management in traditional irrigation networks, where cropping patterns are difficult to assess.

The concept of interaction classes (iClasses) for multi-environment trial data was introduced to address the problem of summarising variety performance across environments in the presence of variety by environment interaction (VEI). The approach involves the fitting of a factor analytic linear mixed model (FALMM), with the resultant estimates of factor loadings being used to form groups of environments (iClasses) that discriminate varieties with different patterns of VEI. It is then meaningful to summarise variety performance across environments within iClasses. The iClass methodology was developed with respect to a FALMM in which the genetic effects for different varieties were assumed independent. This was done for pedagogical reasons but it was pointed out that the accuracy of variety selection is greatly enhanced by considering the genetic relatedness of varieties, either via ancestral or genomic information. The focus of the current paper is therefore to extend the iClass approach for FALMMs which incorporate such information. In addition a measure of stability of variety performance across iClasses is defined. The utility of the approach for variety selection is illustrated using a multi-environment trial dataset from the lentil breeding program operated by Agriculture Victoria.

A ruminant model, MINDY, was used to explore the impact of grazing patches of tannin-containing legumes on environmental impact by cows grazing on grass-dominated rangelands swards. MINDY was initialized as a pregnant beef cow grazing on a grass (Bromus biebersteinii; meadow brome-Control), with the addition of a patch with tannin-containing legumes (Lotus corniculatus-birdsfoot trefoil-Tre, or Onobrychis viciifolia-sainfoin-Sain). Twenty-five scenarios (treatments) were established as a product of frequency (weekly, fortnightly, and monthly) and dietary proportions (0.05, 0.10, 0.15, and 0.20 of total forage allocation) of either Sain or Tre. Methane (CH4) production and nitrogen (N) excretion increased with legume availability. As legume proportion increased, dry matter intake (DMI), animal performance, CH4 production and urinary nitrogen (UN) excretion increased with a greater magnitude for Sain. Methane yield was lower than the Control at weekly allocation of legumes. Environmental costs in terms of CH4 emission increments per unit of production relative to Control were greater at monthly allocations when the levels of legume in the diet were low (0.5 – 0.10). Legumes in the diet at 0.15 – 0.20 yielded the lowest costs regardless of frequency of allocation. Environmental costs in terms of UN increments per unit of production relative to Control were lowest at 0.15 – 0.20 of legumes in the diet regardless of frequency of allocation. This study suggests that strategic allocation of either sainfoin or birdsfoot trefoil when beef cattle graze grass-dominated rangelands swards can reduce environmental impact, while increasing secondary production of the system at the same levels of resource allocation.