Increasingly serious shortages of water make it imperative to improve the efficiency of irrigation in agriculture, horticulture and in the maintenance of urban landscapes. The main aim of the current review is to identify ways of meeting this objective. After reviewing current irrigation practices, discussion is centred on the sensitivity of crops to water deficit, the finding that growth of many crops is unaffected by considerable lowering of soil water content and, on this basis, the creation of improved means of irrigation scheduling. Subsequently, attention is focused on irrigation problems associated with spatial variability in soil water and the often slow infiltration of water into soil, especially the subsoil. As monitoring of soil water is important for estimating irrigation requirements, the attributes of the two main types of soil water sensors and their most appropriate uses are described. Attention is also drawn to the contribution of wireless technology to the transmission of sensor outputs. Rapid progress is being made in transmitting sensor data, obtained from different depths down the soil profile across irrigated areas, to a PC that processes the data and on this basis automatically commands irrigation equipment to deliver amounts of water, according to need, across the field. To help interpret sensor outputs, and for many other reasons, principles of water processes in the soil–plant system are incorporated into simulation models that are calibrated and tested in field experiments. Finally, it is emphasized that the relative importance of the factors discussed in this review to any particular situation varies enormously.

Models that accurately describe and predict growth and nutrient utilization of fish can be useful in developing strategies to improve the economic and environmental sustainability of aquaculture operations. Current bioenergetics models are not sufficiently flexible to be applied to the wide range of conditions encountered in aquaculture. There is a need to move from bioenergetics approaches to more mechanistic approaches based on nutrient utilization by fish. A non-ruminant nutrient-based growth model has been successfully used in pig production. The model explicitly describes the utilization of energy-yielding nutrients and metabolites for body protein deposition (Pd) and body lipid deposition (Ld) at the whole animal level. Partitioning of intake of energy-yielding nutrients between Pd and Ld is governed by a minimum ratio (minLP) of the body lipid mass (L) to protein mass (P), a maximum daily rate of Pd (PdMax), or maximum efficiency of using intake of the first limiting dietary essential amino acid (AA) for body Pd. The growth model was adapted to rainbow trout (Oncorhynchus mykiss (Walbaum 1792)) through parameterization and various modifications consistent with its framework. The fish nutrient-based model was evaluated by comparing model simulations with data from various experiments carried out with rainbow trout. Significant discrepancies between model predictions and experimental observations were observed. The model predicted energy retention well but did not always accurately predict growth rate, nor Pd and Ld. Overall, the model underestimated growth rate (expressed as thermal-unit growth coefficient (TGC)) by 37% and Pd by 15% and overestimated Ld by 13%. These discrepancies are probably attributable to differences in nutrient utilization and partitioning mechanisms between fish and pigs. The development of more reliable models requires better understanding of the nutritional and endogenous determinants of fish growth.

A dynamic mathematical model of a closed mammary system in lactating cows was developed to incorporate the setpoint concept of tissue activity, using equations where nutrient supply and absorption are locally regulated so as to maintain a given rate of milk protein yield. The model consists of 12 differential equations, 11 of which are concerned with intracellular biochemical compartments and one describes the volume of tissue actively perfused by blood (AP). The intracellular compartments are: amino acids (AAs), acetate, fatty acids (FAs), β-hydroxybutyrate, glucose-6-phosphate, fructose-6-phosphate, phospho-glyceraldehyde, pyruvate, mitochondrial acetyl-CoA, adenosine triphosphate (ATP) and adenosine diphosphate (ADP). The model simulates mechanisms which are aimed at reproducing and, thereby, explain variations in mammary plasma flow (MPF) observed experimentally. The AP changes according to variations in the metabolic status or in the metabolic requirements of the gland. Should the tissue energy charge (i.e. ATP/ADP ratio) exceed a baseline ratio, then AP decreases and consequently MPF declines. Conversely, when milk protein yield increases, AP increases and MPF rises. In the present model, AA uptake by the mammary gland is inhibited by intracellular AAs. It is also assumed that, when milk protein yield diminishes, the respiratory chain and ATP synthesis become uncoupled and consequently ATP yield is reduced. Model evaluation included behavioural analysis and sensitivity analysis. Behaviour analysis was conducted to test whether the model mechanisms reproduced the scenarios from which the model hypotheses were developed, and took into consideration: an increase in arterial glucose concentration (HIGLC), increases in arterial concentrations of non-esterified FAs, triacylglycerol and β-hydroxybutyrate (HIFAT), a 50% reduction of arterial histidine concentration (LOHIS), and a hyperinsulinaemic euglycaemic clamp (HIINS). Both HIGLC and HIFAT resulted in a decrease in MPF and in milk protein yield; moreover, the scenario HIGLC also produced a notable decrease in the extraction of glucose. The scenario LOHIS resulted in increased MPF and extraction of His from plasma. However these responses were not sufficiently large to prevent a severe reduction of milk protein yield which was accompanied by a reduction in the extraction of other essential AAs. The scenario HIINS resulted in an increase of MPF and of milk protein yield, in the extraction of His and of other essential AAs. Model sensitivity analysis focused on variation of both affinity and inhibition constants of some of the Michaelis–Menten equations. Improvements in model structure and directions for future research suggested by the modelling analysis are discussed.

A dynamic, mechanistic model of enteric fermentation was used to investigate the effect of type and quality of grass forage, dry matter intake (DMI) and proportion of concentrates in dietary dry matter (DM) on variation in methane (CH4) emission from enteric fermentation in dairy cows. The model represents substrate degradation and microbial fermentation processes in rumen and hindgut and, in particular, the effects of type of substrate fermented and of pH on the production of individual volatile fatty acids and CH4 as end-products of fermentation. Effects of type and quality of fresh and ensiled grass were evaluated by distinguishing two N fertilization rates of grassland and two stages of grass maturity. Simulation results indicated a strong impact of the amount and type of grass consumed on CH4 emission, with a maximum difference (across all forage types and all levels of DMI) of 49 and 77% in g CH4/kg fat and protein corrected milk (FCM) for diets with a proportion of concentrates in dietary DM of 0·1 and 0·4, respectively (values ranging from 10·2 to 19·5 g CH4/kg FCM). The lowest emission was established for early cut, high fertilized grass silage (GS) and high fertilized grass herbage (GH). The highest emission was found for late cut, low-fertilized GS. The N fertilization rate had the largest impact, followed by stage of grass maturity at harvesting and by the distinction between GH and GS. Emission expressed in g CH4/kg FCM declined on average 14% with an increase of DMI from 14 to 18 kg/day for grass forage diets with a proportion of concentrates of 0·1, and on average 29% with an increase of DMI from 14 to 23 kg/day for diets with a proportion of concentrates of 0·4. Simulation results indicated that a high proportion of concentrates in dietary DM may lead to a further reduction of CH4 emission per kg FCM mainly as a result of a higher DMI and milk yield, in comparison to low concentrate diets. Simulation results were evaluated against independent data obtained at three different laboratories in indirect calorimetry trials with cows consuming GH mainly. The model predicted the average of observed values reasonably, but systematic deviations remained between individual laboratories and root mean squared prediction error was a proportion of 0·12 of the observed mean. Both observed and predicted emission expressed in g CH4/kg DM intake decreased upon an increase in dietary N:organic matter (OM) ratio. The model reproduced reasonably well the variation in measured CH4 emission in cattle sheds on Dutch dairy farms and indicated that on average a fraction of 0·28 of the total emissions must have originated from manure under these circumstances.

Six pairs of isogenic lines of sorghum (Sorghum bicolor L. Moench) were sown in field plots in Montecillo, State of México (2240 m altitude), in 2005 and 2006. Crosses A (♀)×B (♂) were done in each pair. In A-lines, the length of pistil, stigma, style and ovary, as well as the ovary width, were measured. In B-lines, pollen diameter, viability (cytoplasm density) and production were evaluated. Pollen germination and pollen tube growth in the pistils of the A-lines, were quantified in vivo with aniline blue and epifluorescence 18 h after pollination (HAP), while fertilized pistils were counted at 96 HAP. Histological studies on both pollinated and non-pollinated pistils were performed in one male-sterile line. Seed yield, mean-seed weight, seeds per panicle and seed set (SS; seeds/flower/panicle) were determined at harvest. Pollen viability was the variable most related to pollen germination and pollen tube growth. Stigma receptivity was not associated with its morphology. Growth of the pollen tube in stigma, style and ovary was observed in the transmitting tissue 18 HAP, running parallel to the vascular tissue. Yield under chilling field temperatures (minimum average of 6 and 8°C) prevailing during flower development and pollination ranged from 7 to 12 g/panicle. The differences in seed production and SS among A×B crosses did not depend on the amount and viability of pollen.

The effect of phosphorus deficiency on yield formation in spring wheat (Triticum aestivum cv. Prointa Oasis) was investigated, focusing on crop growth and dry matter partitioning during the spike growth period (SGP), which is critical for grain number determination. Two experiments combining shading and P deficiency were performed at Balcarce, Argentina (37°45′S). The main treatments were two levels of soil P-availability: low P, a naturally low P fertility soil (7·0 and 5·5 mg Bray extractable P/kg soil, in the first and second experiments respectively) and high P, a P dose that does not limit growth. The sub-treatments were two levels of radiation (shaded and control). Phosphorus deficiency affected yield mainly through the number of grains/unit surface (m2). Differences in grain number/m2 were related to differences in dry weight of spikes/m2, measured 7 days after anthesis, excluding grain weight. The duration of the SGP did not change much as result of P deficiency: 27 days with high P and only 3 days more with low P. Therefore, changes in spike dry weight were mainly due to differences in spike growth rate. In turn, the spike growth rate of all treatments was linearly related to crop growth rate, with little effect of dry matter partitioning to spikes. Finally, differences in crop growth rate between P treatments were mainly determined by the amount of intercepted radiation. It was concluded that P deficiency resulted in a reduction in intercepted radiation during the SGP, thus causing a reduction in grain number and crop yield.

The efficiency of nitrogen fertilizer use is as low as 0·30–0·35 in most agricultural practices due to losses to the natural environment in many ways. Ammonia (NH3) volatilization is important in paddy rice fields. The present study investigated the effect of a surface film-forming material (SFFM) on NH3 volatilization from a paddy rice field, by model estimation using parameters from evaporative pan experiments. The modified Jayaweera–Mikkelsen (J-M) ammonia volatilization model was employed to simulate and elucidate the effect of SFFM in reducing ammonia volatilization from paddy fields. A parameter of kf value in the J–M modified model was introduced to represent the resistance of NH3 volatilization loss from SFFM. The simulated data fitted well with the prediction of the J–M modified model and field observations. The modified J–M model is suitable for screening and verifying the new SFFM, and merits further study.

Agricultural activity involves direct interaction with the physical environment factors in the environmental context in which the activity is developed. Galicia, northwest Spain, is an environmentally heterogeneous region that encompasses territorial spaces with different levels of suitability for each agricultural activity. In barely 30 years, the production systems of the region have evolved from self-sufficiency to commercial production; however, the requirements of production for each differ greatly. During such a transformation, many farms have disappeared while other farms have conformed to the requirements of the current production systems without changing location. Decision-making in rural planning requires knowing the spatial distribution of farms, the evolution of farm distribution and the relationship between the spatial location of farms (associated with some specific environmental characteristics) and the production systems used.

The current paper describes a methodology for analysing the spatial distribution of farms and for determining the relationships between the spatial location of farms and the values of the physical environment factors that are characteristic of each spatial location. The methodology has been developed by using Agricultural Census data and is exemplified through the analysis of two crops (wheat and potato) and one farming activity (dairy farming). Results show the location of farms and the production systems used, and reveal different degrees of fit to the physical environment factors considered.