Fragrant rice is an important export commodity of Thailand and obtaining seasonal production estimates well in advance is important for marketing and stock management. Rice4cast is a software platform that has been developed to forecast rice yield several months prior to harvesting; it links a rice model with a Minimum Data Set (MDS) and Weather Research Forecast (WRF) data. The current study aimed to parameterize and evaluate the model and to demonstrate the use of the Rice4cast platform in forecasting seasonal KDML 105 rice yield and production with local data set. The study area encompassed 77 districts in Thailand, covering 0.94 of the total area of KDML 105 in the country. Minimum Data Sets for the 2013–2015 growing seasons were used for model parameterization and evaluation. The annual statistics from the Office of Agricultural Economics (OAE) were used as a reference basis and planted areas from the Geo-Informatics and Space Technology Development Agency (GISTDA) was used for production estimation. Model evaluation showed good to fairly good agreement between the predicted and reported OAE yield. Production forecasts, however, over-estimated the OAE values considerably, primarily because of the use of GISTDA planted areas that were larger than the harvested areas in the production estimates. Adjustment of the planted areas to account for damaged areas need to be explored further. Nevertheless, the results demonstrated the capability of yield predictions with the Rice4cast, making it a valuable tool for in-season estimates for fragrant rice yield and production.

In areas where water is scarce, the use of regulated deficit irrigation, combined with decision support system tools, may decrease the impact of agriculture on natural water resources, as well as on energy consumption, thereby improving the profitability of farms. With this aim, the SUBSTOR-Potato model (incorporated in the DSSAT Program) was evaluated with a 2-year field test (2011 and 2012) conducted in a semi-arid area (Albacete, Spain) applying four irrigation levels (120, 100, 80 and 60% of irrigation requirements). Subsequently, the model was used for simulating the potato yield under several deficit irrigation strategies (ISs) during 30 years of a semi-arid climate (1988–2017) and determining the most profitable option. The considered ISs were deemed those most suitable from the yield and water productivity point of view by some authors. The model performance for tuber yield was satisfactory with an index of agreement >0.91 and errors between 0.71 and 3.06 × 103 kg/ha. The ISs simulated with SUBSTOR-Potato showed that slight deficit irrigation (5–10%) may increase the water productivity and profitability of the farms. Moreover, tuber formation (from onset of tuber initiation to harvest) was shown to be the most sensitive stage, therefore it is highly recommended to avoid deficit during this stage, which would cause a large reduction in yield (around 8 t/ha, depending on the level of deficit suffered by the crop).

Light competition increases and plants’ growth pattern change to optimize light utilization when the leaf area index increases. It has been previously shown that using 95% canopy light interception (LI) as a grazing frequency criterion resulted in a greater proportion of leaves and a lower proportion of stem. The objective of the study was to characterize the forage production, morphological composition and nutritive value of Panicum maximum cv Mombaça. The experiment was carried out during summer, autumn–winter and spring. Treatments corresponded to combinations of two pre-grazing conditions (95% and maximum LI at pre-grazing; LI95% and LIMax, respectively) and two post-grazing heights (PGHs; 30 and 50 cm). The statistical design was a randomized complete block, with a 2 × 2 factorial arrangement. Swards managed with LI95% had greater proportions of leaves and lower proportions of stems compared to LIMax. Leaf proportion was lower during autumn–winter compared to summer and spring. The LI95% had greater crude protein (CP) and digestibility (IVOMD), and lower acid detergent fibre (ADF) concentrations than LIMax. The 50 cm PGH pastures had greater CP content and IVOMD, and lower ADF content than 30 cm PGH pastures. Lower IVOMD was observed during autumn–winter than summer and spring. The variability observed on morphological characteristics was primarily associated with seasonality, whilst the nutritive value was primarily affected by grazing management. The pre-grazing target of LI95% combined with 50 cm PGH was the combination that resulted in an increased proportion of leaves, decreased stems in basal stratum and the greatest nutritive value of the produced forage.

Field experiments were carried out in order to investigate if brown manuring (BM) using Sesbania plants can be used to control weeds in maize, especially Cyperus rotundus (Experiment I), and further to optimize the BM technology through appropriate Sesbania seed rate (S), 2,4-D application time (T) and dose (D) (Experiment II). Each BM treatment received a pre-emergence application of pendimethalin 1.0 kg a.i./ha. Experiment I showed that the BM practice using 15 kg/ha Sesbania seed and 2,4-D 0.50 kg a.i./ha applied at 25 DAS led to better control of weeds, especially C. rotundus and higher maize grain yield. Further optimization studies (Experiment II) indicated that among the factors S, T and D, the BM combination S~25 kg/ha, D~0.50 kg a.i./ha and T~25 DAS (i.e. S25T25D0.50) resulted in lowest weed density (3.1/m2) and dry weight (3.8 g/m2) and highest weed control index (89.2%) at 60 days after sowing (DAS) which was at par with another BM practice S15T25D0.50. However, the later BM combination led to significantly higher maize productivity (5.25 t/ha) and profitability (net returns (NR) $878/ha), which were 103 and 280% higher, respectively, than the weedy check (WC). The Sesbania seed rate S~15 kg/ha gave 7% higher maize grain yield and 12% higher NR than its corresponding level S~25 kg/ha. Therefore, Sesbania BM with 15 kg seeds/ha and 2,4-D at 0.50 kg a.i/ha applied at 25 DAS can be recommended for effective and eco-friendly weed management in maize, which would provide higher maize grain yield and enhance farmers' profitability.

In the present study, an effective secondary selection of transgressive variants from a homozygous population of Pusa Sugandh 3 (PS3) has led to the development of basmati variant SKUA 494. SKUA 494 exhibited a grain yield (7.9 t/ha) with superiority of 21.5% over its progenitor (6.5 t/ha). Besides, the genotype revealed an earliness of about 13 and 15 days for flowering and maturity, respectively. Hulling, milling and head rice recovery traits of SKUA 494 were comparatively better over the controls PS3 and Pusa Basmati 1509. No significant differences in the cooking quality were observed in SKUA 494 over its parental line. Quality traits of SKUA 494 revealed an intermediate score for alkali spreading value, besides similar values for gel consistency and amylose content in comparison to PS3. On the basis of stability variables, stability index and overall mean for most of the traits, SKUA 494 depicted stable performance across the locations and over the years. Molecular analysis based on simple sequence repeat markers revealed polymorphism at locus flanking the quantitative trait loci for days to heading (Hd6) between SKUA 494 and its parent (PS3). Based on overall superiority in the performance and adaptability of SKUA 494, the variety has been recommended to farmers for general cultivation under temperate ecology.

Using legumes in forage mixes can help decrease the use of nitrogen fertilizers and possibly increase the nutritive value of pasture. The aim of the current study was to determine animal production and behavioural and ingestion parameters by evaluating the production and nutritive value of Aruana grass (Panicum maximum ‘Aruana’) intercropped with forage peanut (Arachis pintoi ‘Amarillo’) or fertilized with nitrogen. The treatments were N200 (200 kg N/ha per season – summer and winter), 100N + PE (100 kg N/ha per season plus pasture mixture with forage peanut) and N100 (100 kg N/ha per season). The presence of forage peanut in the pasture did not replace nitrogen fertilization as the pasture fertilized with 200 kg of nitrogen had a greater leaf/stem ratio (0.66 v. 0.54), stocking rate (2600 v. 2290 kg live weight/ha), average daily gain (0.880 v. 0.700 kg/day) and live weight gain (LWG) (652 v. 468 kg/ha) during summer. During winter, no effect of increased nitrogen fertilization on pasture and animal production was observed. In the total study period (summer + winter), a greater LWG (897 v. 741 kg/ha) occurred when a higher quantity of nitrogen (N200) was placed in the pasture compared to the insertion of forage peanuts in the system.

The current study was carried out to examine the effect of cottonseed processing and chitosan supplementation on lamb performance, digestibility and nitrogen digestion. Eighty uncastrated Santa Inês lambs (23 ± 2.2 kg average weight, 4 months old) were distributed in a completely randomized design in a 2 × 2 factorial arrangement that consisted of two cottonseed processing forms (whole or ground) and two chitosan levels (0 or 136 mg/kg live weight). Higher dry matter and organic matter apparent digestibility coefficient (ADC) was achieved with the diets containing the whole cottonseed. Ether extract ADC was higher in the animals fed the chitosan-containing diet. There was an interaction effect on the ADC of neutral detergent fibre corrected for ash and protein, which increased with chitosan inclusion associated with the whole cottonseed. The lambs that received the treatment containing the whole cottonseed showed higher microbial protein synthesis. Chitosan addition increased nitrogen retention. The animals fed chitosan-containing diets showed higher microbial protein synthesis. There was an interaction effect on microbial protein synthesis. Whole cottonseed associated with chitosan in lamb diets increases ether extract ADC and microbial protein synthesis.

The current study evaluated the effects of dietary roughage:concentrate (R:C) ratios and water supply on the carcass characteristics and yield of lambs. Forty Santa Inês crossbred lambs with an average body weight (BW) of 19 ± 2.8 kg were evaluated in a completely randomized design with a 2 × 2 factorial arrangement consisting of two proportions of roughage and concentrate (30:70 and 70:30) and two levels of water supply (ad libitum and restricted to 0.5). The animals were slaughtered at an average weight of 28 ± 31 kg. Centesimal composition, colour parameters (L*, a* and b*), shear force, cooking losses and pH were determined on the Longissimus lumborum muscle. There was no interaction effect between the R:C ratio and water supply on the evaluated variables. Total BW gain, average daily gain and final BW were affected by water restriction and R:C ratio. Water restriction reduced total BW gain, average daily gain and final BW. No effect of water restriction was detected on slaughter weight, centesimal composition, colour variations, shear force, pH, weight or yield of carcass. No effect of water restriction and diets was observed on the cuts, except for neck weight. Carcass weight and yield were affected by the R:C ratios. Restricting the water supply to 0.5 does not affect the carcass weight or yield of Santa Inês crossbred lambs or their meat quality characteristics (centesimal composition, colour, shear force and pH measurements). A higher proportion of concentrate in the diet results in heavier hot and cold carcass weights.

Fifty-one Churra da Terra Quente ewes (4–7 years old) were used to analyse the potential of real-time ultrasound (RTU) to predict the amount of internal adipose depots, in addition to carcass fat (CF). The prediction models were developed from live weight (LW) and RTU measurements taken at eight different locations. After correlation and multiple linear regression analysis, the prediction models were evaluated by k-fold cross-validation and through the ratio of prediction to deviation (RPD). All prediction models included at least one RTU measurement as an independent variable. Prediction models for the absolute weight of the different adipose depots showed higher accuracy than prediction models for fat content per kg of LW. The former showed to be very good or excellent (2.4 ⩽ RPD ⩽ 3.8) for all adipose depots except mesenteric fat (MesF) and thoracic fat, with the model for MesF still providing useful information (RPD = 1.8). Prediction models for fat content per kg of LW were also very good or excellent for subcutaneous fat, intermuscular fat, CF and body fat (2.6 ⩽ RPD ⩽ 3.2), while the best prediction models for omental fat, kidney knob, channel fat and internal fat still provided useful information. Despite some loss in the accuracy of the estimates obtained, there was a similar pattern in terms of RPD for models developed from LW and RTU measurements taken just at the level of the 11th thoracic vertebra. In vivo RTU measurements showed the potential to monitor changes in ewe internal fat reserves as well as in CF.