EU milk quota deregulation has forced many farmers to reconsider the factors that will limit milk production into the future. Factors other than milk quota such as land, labour, capital, stock, etc. will become the limiting factor for many in a post-EU milk quota scenario. While it can be postulated what the limits to production will be in a post-quota scenario, how farmers react will determine the future direction of the industry. In order to determine the future attitudes and intentions and to identify the key factors influencing farmers who intend to expand, exit, remain static or contract their businesses in the future, a survey of a large group of Irish commercial dairy farmers was carried out. The telephone survey sample was chosen randomly, based on a proportional representation of suppliers to the largest milk processor in Ireland. The sample (780 suppliers) was broken down by quota size (five quota categories, Q1-Q5), supplier region and system of production. The sample was analysed to determine the effect of key survey variables on the future intentions of dairy farmers. The survey was completed by 659 suppliers (0.82 of the sample). The proportions of farmers intending to expand were 0.28, 0.47, 0.61, 0.61 and 0.56, respectively, for Q1-Q5, while the proportions intending to exit were 0.27, 0.18, 0.08, 0.09 and 0.08, respectively. Farmers who were intent on expanding had larger total farm areas, larger milk tank capacity per litre of milk quota, more modern milking facilities, more available cow housing and more housing that could be converted at a relatively low cost and were more likely to have a successor. Of those expanding, 0.60 wanted milk quotas abolished, while 0.36 of those planning to exit wanted milk quotas abolished. The level of expansion was affected by business scale, dairy stocking rate, the additional labour required with expansion and total and milking platform farm size.
Deep learning (DL) constitutes a modern technique for image processing, with large potential. Having been successfully applied in various areas, it has recently also entered the domain of agriculture. In the current paper, a survey was conducted of research efforts that employ convolutional neural networks (CNN), which constitute a specific class of DL, applied to various agricultural and food production challenges. The paper examines agricultural problems under study, models employed, sources of data used and the overall precision achieved according to the performance metrics used by the authors. Convolutional neural networks are compared with other existing techniques, and the advantages and disadvantages of using CNN in agriculture are listed. Moreover, the future potential of this technique is discussed, together with the authors' personal experiences after employing CNN to approximate a problem of identifying missing vegetation from a sugar cane plantation in Costa Rica. The overall findings indicate that CNN constitutes a promising technique with high performance in terms of precision and classification accuracy, outperforming existing commonly used image-processing techniques. However, the success of each CNN model is highly dependent on the quality of the data set used.
Noy-Meir's simple but insightful model of grazing-system dynamics was used to draw broader inferences from empirical data generated by a 17-year field trial with beef cattle grazing a Mediterranean grassland in northern Israel. After calibration of its parameters against the field results, the model predictions were tested against an independent set of data obtained from the study site; they were within acceptable deviations from the inherently noisy field data. The calibrated model was used to analyse the effects of changes to two key grazing-management factors - stocking density and early-season grazing deferment - on biomass dynamics and forage consumption. The simulated results were used to calculate forage deficits and supplementary feed requirements for optimum herd performance during the growth ('green') season and throughout the year. The results revealed a critical stocking density of 0.7 Animal Units (AU)/ha, above which early-season deferment reduced the amount of supplementary feed required to maintain the optimum production of the herd. Optimum stocking is higher when the grassland is used mainly in the highly nutritious green season. Responses of the strongly seasonal Mediterranean grassland to the interaction between stocking density and early-season grazing deferment were expressed by a calibrated model, in terms that determine the efficiency of forage supplementation of the herd during the green season and throughout the year.
Drought represents one of the major constraints on agricultural productivity and food security and in future is destined to spread widely as a consequence of climate change. Research efforts are focused on developing strategies to make crops more resilient and to mitigate the effects of stress on crop production. In this context, the use of root-associated microbial communities and chemical priming strategies able to improve plant tolerance to abiotic stresses, including drought, have attracted increasing attention in recent years. The current review offers an overview of recent research aimed at verifying the role of arbuscular mycorrhizal fungi and chemical agents to improve plant tolerance to drought and to highlight the mechanisms involved in this improvement. Attention will be devoted mainly to current knowledge on the mechanisms involved in water transport.
The use of cactus cladodes in animal feed is well-established in semi-arid areas. The cactus Nopalea cochenillifera (L.) Salm-Dyck cladodes (Nopalea) have high acceptability amongst dairy cows and are resistant to carmine cochineal insects (Dactylopius opuntiae Cockerell), a problem in semi-arid regions, but in regions of prolonged drought, it has lower productivity compared with the cactus Opuntia stricta (Haw.) Haw cladodes (Opuntia), which is also resistant to the insect. The objective of the current study was to evaluate the intake and content of digestible material of dry matter (DM) and its components, feeding behaviour, microbial protein synthesis, nitrogen balance, blood parameters, performance and milk composition of Holstein cows fed a control diet, containing either Nopalea or Opuntia associated with different concentrate levels (225, 275, 325 and 375 g/kg). Ten cows with an initial average milk production of 20 +/- 2.1 kg/day were distributed into a double 5 x 5 Latin square design. Diets containing 775 g roughage/kg and 225 g concentrate/kg promoted similar responses to the analysed variables regardless of the cactus cladode used, except for digestibility of neutral detergent fibre. Diets containing higher proportions of concentrate (325 and 375 g/kg) promoted greater DM intake and 3.5% fat-corrected milk yield. The diet containing Opuntia at 775:225 g/kg roughage:concentrate proportion is as effective as the control diet for Holstein cows producing 20 kg of milk/day. To promote greater milk production, higher proportions of concentrate should be added to diets using Opuntia.
A field experiment with the 3(5-1) fractional factorial design and five factors (k = 5) at three levels (s = 3) was performed in 2007-2010 at the Agricultural Experiment Station in Balcyny, north-eastern (NE) Poland. The results of the experiment carried out under the agro-ecological conditions of NE Poland confirmed the high yield potential of common wheat and satisfactory yield potential of spelt and durum wheat. On average, durum wheat and spelt yields were 2.14 and 2.55 t/ha lower, respectively, than common wheat yields. Sowing date was not correlated with the yields of analysed Triticum species. Seed rate (350, 450 and 550 seeds/m(2)) had no significant influence on the grain yield of winter cultivars of common wheat, durum wheat and spelt. Common wheat cv. Oliwin and durum wheat cv. Komnata were characterized by the highest yields in response to nitrogen (N) fertilizer rates calculated based on the N-min content of soil. An increase in the spring fertilizer rate by 40 kg N/ha in excess of the balanced N rate was not justified because it did not induce a further increase in the grain yield of common wheat and durum wheat. The grain yield of spelt cv. Schwabenkorn continued to increase in response to the highest rate of N fertilizer in spring (40 kg N/ha higher than the optimal rate). Intensified fungicide treatments improved grain yield in all Triticum species.
Although application of organic fertilizers has become a recommended way for developing sustainable agriculture, it is still unclear whether above-ground and below-ground crops have similar responses to chemical fertilizers (CF) and organic manure (OM) under the same farming conditions. The current study investigated soil quality and crop yield response to fertilization of a double-cropping system with rapeseed (above-ground) and sweet potato (below-ground) in an infertile red soil for 2 years (2014-16). Three fertilizer treatments were compared, including CF, OM and organic manure plus chemical fertilizer (MCF). Organic fertilizers (OM and MCF) increased the yield of both above- and below-ground crops and improved soil biochemical properties significantly. The current study also found that soil-chemical properties were the most important and direct factors in increasing crop yields. Also, crop yield was affected indirectly by soil-biological properties, because no significant effects of soil-biological activities on yield were detected after controlling the positive effects of soil-chemical properties. Since organic fertilizers could not only increase crop yield, but also improve soil nutrients and microbial activities efficiently and continuously, OM application is a reliable agricultural practice for both above- and below-ground crops in the red soils of China.
The objective of the current paper was to apply mixed models to adjust the growth curve of quail lines for meat and laying hens and present the rates of instantaneous, relative and absolute growth. A database was used with birth weight records up to the 148th day of female quail of the lines for meat and posture. The models evaluated were Brody, Von Bertalanffy, Logistic and Gompertz and the types of residues were constant, combined, proportional and exponential. The Gompertz model with the combined residue presented the best fit. Both strains present a high correlation between the parameters asymptotic weight (A) and average growth rate (k). The two strains presented a different growth profile. However, growth rates allow greater discernment of growth profiles. The meat line presented a higher growth rate (6.95 g/day) than the lineage for laying (3.65 g/day). The relative growth rate was higher for lineage for laying (0.15%) in relation to the lineage for meat (0.13%). The inflection point of both lines is on the first third of the growth curve (up to 15 days). All results suggest that changes in management or nutrition could optimize quail production.
Differences in forage nutritive value between morning and afternoon are related to patterns of dehydration and carbohydrate accumulation throughout the day. In this way, management strategies that maximize grazing time during the afternoon could increase forage nutritive value and consequently nutrient intake. The aim of the current experiment was to evaluate the effect of the time of day (06.00 h [designated AM] or 15.00 h [PM]) that cattle are moved to a new paddock on forage nutritive value, grazing behaviour and animal performance of beef cattle on rotationally stocked Marandu palisadegrass (Brachiaria brizantha cv. Marandu Syn. Urochloa brizantha cv. Marandu) pastures. A spring and summer study was conducted in Pirassununga, SP, Brazil from October 2012 to March 2013 (182 days). Treatments were distributed in a randomized complete block design with three replications. Herbage mass, morphological composition, herbage allowance and stocking rates were similar between treatments during spring and summer. Moving animals to a new paddock, regardless of the time of day - 06.00 h (AM) or 15.00 h (PM) - stimulated grazing, modifying the distribution of meals throughout the day. However, compensatory mechanisms among grazing time, bite rate and forage nutritive value throughout the day operated in order to generate similar performance between animals offered a new paddock in the morning or in the afternoon.
An experiment was carried out to examine the effects of offering beef steers grass silage (GS) as the sole forage, lupins/triticale silage (LTS) as the sole forage, a mixture of LTS and GS at a ratio of 70:30 on a dry matter (DM) basis, vetch/barley silage (VBS) as the sole forage, a mixture of VBS and GS at a ratio of 70:30 on a DM basis, giving a total of five silage diets. Each of the five silage diets was supplemented with 2 and 5 kg of concentrates/head/day in a 5 x 2 factorial design to evaluate the five silages at two levels of concentrate intake and to examine possible interactions between silage type and concentrate intake. A total of 80 beef steers were used in the 122-day experiment. The GS was well preserved while the whole crop cereal/legume silages had high ammonia-nitrogen (N) concentrations, low lactic acid concentrations and low butyric acid concentrations For GS, LTS, LTS/GS, VBS and VBS/GS, respectively, silage DM intakes were 6.5, 7.0, 7.2, 6.1 and 6.6 (s.e.d. 0.55) kg/day and live weight gains were 0.94, 0.72, 0.63, 0.65 and 0.73 (s.e.d. 0.076) kg/day. Silage type did not affect carcass fatness, the colour or tenderness of meat or the fatty acid composition of the intramuscular fat in the longissimus dorsi muscle.
Sustainable ruminant production systems depend on the ability of livestock to utilize increased quantities of grazed herbage. The current study aimed to compare the effect of white clover (WC) inclusion and perennial ryegrass (PRG) ploidy on herbage dry matter (DM) production, plant morphology, nutritive value and biological nitrogen (N) fixation (BNF) under high N fertilizer use (250 kg N/ha) and high stocking rates (2.75 livestock units/ha). Four sward treatments (diploid-only, tetraploid-only, diploid-WC, tetraploid-WC) were evaluated over a full grazing season at a farmlet scale. White clover inclusion had a significant effect on herbage DM production, herbage growth rate, tiller density, organic matter digestibility, crude protein and BNF. Tetraploid swards had a lower tiller density, lower sward WC content and post-grazing sward height and increased organic matter digestibility and crude protein than diploid swards. White clover inclusion improved herbage DM production and nutritive value across a full grazing season, with tetraploid and diploid swards producing similar herbage DM yields across the year. Perennial ryegrass ploidy had an effect on WC morphology as plants in diploid-WC swards had narrower, longer stolons, fewer branches and more petioles than tetraploid-WC swards. The current study highlights the benefit of including WC in grass-based systems under a high N fertilizer regime and high stocking rate.
Non-decorticated sunflower meal (SFM) is a potential protein source for dairy cows with high-fibre content but high ruminal degradability. The effect of replacement of soybean meal (SBM) and wheat middlings (WM) with SFM on the intake, digestibility, microbial protein synthesis, nitrogen utilization and milk production of dairy cows was evaluated. Twelve Holstein cows were blocked by days in milk and distributed in three 4 x 4 Latin squares. Diets were formulated to be isonitrogenous and contained 550 g maize silage/kg dry matter (DM). Treatment diets were no SFM (CON) or 70, 140 and 210 g/kg DM of SFM replacing fixed mixture of SBM and WM (536 and 464 g/kg of the mixture, respectively). The inclusion of SFM in diet did not affect DM intake, but intake of rumen degradable protein increased linearly. Inclusion of SFM reduced or tended to reduce total-tract digestibility of non-fibre carbohydrate, total digestible nutrients and excretion of purine derivatives. Milk production, milk protein content and efficiency of nitrogen use for lactation were reduced with increasing levels of SFM in the diet. The use of non-decorticated SFM as a replacement for SBM-WM mixture in diet reduces performance and efficiency of nutrient use in lactating dairy cows. The outcome of the current study is attributed to reduced fibre digestibility in SFM hulls. Therefore, future studies should evaluate the use of decorticated SFM.
Integrated crop-livestock systems (ICLS) are currently promoted agricultural production systems that aim to use better resources through production integration and intensification. While this system reduces some risks, it adds complexity and new risks to businesses due to interdependence between the agricultural modules. To deal with these issues, integrated risk management is required to reduce the effects of risks and to take advantage of the opportunities of an ICLS. Generically, enterprise risk management (ERM) meets this need by proposing comprehensive and coherent risk management, instead of managing agricultural module risks individually. However, there is a need to customize the ERM approach to ICLS. Therefore, the current study aims to develop a method to manage risks for ICLS based on ERM, integrating the management of risks and aligning risk management with the strategic objectives. A literature review, a pilot study, interviews with experts, four case studies and 20 practitioners supported the method development and evaluation through three versions. As a result, the method identifies and relates risks through process mapping with a qualitative and quantitative analysis of their impacts, determines risk responses based on willingness to take risks, and helps identify processes to control, communicate and monitor the risks. The method also stimulates the implementation of ICLS in market-oriented farms, providing an approach to increase the chances of ICLS success. The main difference from previous research lies in the integrative management of multiple risks, the alignment of risks with strategy and the consideration that a risk might be considered an opportunity.
It is challenging to predict the changes in weed flora that may occur because of changes in global climate. Limited data are available on the effect of climate change and drought conditions on weed flora and their competitiveness in Southern Europe. Future predictions by scientists indicate reduced and untimely rainfall, along with increased temperatures in this region. Weeds possess a variety of developmental and physiological mechanisms, including senescing, increased leaf cuticular wax deposition, well-developed palisade parenchyma in the leaves, high root/shoot ratio, stomatal closure, peroxidase accumulation and symbiosis with endophytes that enable them to adapt to drought and high temperatures. Because of high adaptability of weeds to adverse environmental conditions, it can be assumed that under future warmer and drier environmental conditions, their growth will be favoured, while the competitiveness of vegetable crops against weeds will be decreased. It is important to highlight that the predicted decrease in overall rainfall levels throughout the year may lead to increased problems of herbicide residues (carryover effects) to following crops. The current paper provides an up-to-date overview of the adaptation mechanisms of weed species commonly found in Southern Europe, in order to expand the available knowledge regarding their response to drought and elevated temperatures. Emphasis is placed on revealing the effects of drought and increased temperatures on vegetable-weed competition and, most importantly, its effect on vegetable crop yield.
Quinoa (Chenopodium quinoa Willd) is a dicotyledonous annual species belonging to the family Amaranthaceae, which is nutritionally well balanced in terms of its oil, protein and carbohydrate content. Targeting-induced local lesions in genomes (the TILLING strategy) was employed to find mutations in acetolactate synthase (AHAS) genes in a mutant quinoa population. The AHAS genes were targeted because they are common enzyme target sites for five herbicide groups. Ethyl methane sulfonate (EMS) was used to induce mutations in the AHAS genes; it was found that 2% EMS allowed a mutation frequency of one mutation every 203 kilobases to be established. In the mutant population created, a screening strategy using pre-selection phenotypic data and next-generation sequencing (NGS) allowed identification of a mutation that alters the amino acid composition of this species (nucleotide 1231 codon GTT -> ATT, Val -> Ile); however, this mutation did not result in herbicide resistance. The current work shows that TILLING combined with the high-throughput of NGS technologies and an overlapping pool design provides an efficient and economical method for detecting induced mutations in pools of individuals.
A probabilistic crop forecast based on ensembles of crop model output (CMO) estimates offers a myriad of possible realizations and probabilistic forecasts of green water components (precipitation and evapotranspiration), crop yields and green water footprints (GWFs) on monthly or seasonal scales. The present paper presents part of the results of an ongoing study related to the application of ensemble forecasting concepts for agricultural production. The methodology used to produce the ensemble CMO using the ensemble seasonal weather forecasts as the crop model input meteorological data without the perturbation of initial soil or crop conditions is presented and tested for accuracy, as are its results. The selected case study is for winter wheat growth in Austria and Serbia during the 2006-2014 period modelled with the SIRIUS crop model. The historical seasonal forecasts for a 6-month period (1 March-31 August) were collected for the period 2006-2014 and were assimilated from the European Centre for Medium-range Weather Forecast and the Meteorological Archival and Retrieval System. The seasonal ensemble forecasting results obtained for winter wheat phenology dynamics, yield and GWF showed a narrow range of estimates. These results indicate that the use of seasonal weather forecasting in agriculture and its applications for probabilistic crop forecasting can optimize field operations (e.g., soil cultivation, plant protection, fertilizing, irrigation) and takes advantage of the predictions of crop development and yield a few weeks or months in advance.
In the current regional-scale study, the model DSSAT CROPGRO was applied in order to simulate the cultivation of industrial tomato and to estimate the green water (GW), blue water (BW), blue water requirement (BWR) and water footprint (WFP) through a dual-step approach (with and without full irrigation). Simulation covered a period of 30 years for three climate scenarios including a reference period and two future scenarios based on forecast global average temperature increases of 2 and 5 degrees C. The spatial patterns of indicators relating to the whole territory of Puglia region (Southern Italy), characterized by the high evaporative demand of the atmosphere, are discussed and analysed. Considering the climatic pattern, the analysis was developed for three areas (Northern, Central and Southern). Future scenarios affected all indicators significantly, particularly the Northern area, characterized by higher temperature and rainfall anomalies. Under the A5 scenario, compared with the baseline, this area was forecast to have a large increase of BW (+30%) and reduction in yield (-20%). As a consequence, the BWR and WFP were predicted to increase dramatically, up to 40 and >65%, respectively. On the other hand, Central and Southern areas, with lower anomalies of temperature and rainfall, were forecast to be less vulnerable to climate change. The distributed analysis performed could be important for water policy, allowing most efficient allocation of scarce water resources and concentrating them where the WFP is lowest, or in other words, water use efficiency is highest.
Hailed as the single most important paper published on crop protection in the 20th century, Stern et al. in 1959 formed the conceptual basis for modern integrated pest management (IPM) worldwide. The ecological foundation for IPM envisioned by its authors is as valid today as in 1959. However, adoption by developing country farmers has been low and its advances short-lived. The present paper examines the concept of integration in IPM and criteria for determining whether its control tactics have been integrated harmoniously. The effects of local and regional landscape patterns on pests and on the design of IPM are reviewed, arguing that the agroecosystem must be understood and managed as a living system with the goal of enhancing and conserving agrobiodiversity and keeping ecosystem services intact. Key to IPM adoption is convincing farmers to integrate non-chemical alternatives (e.g. biological control, plant diversification) as primary management components and to apply pesticides judiciously and only after non-chemical components fail to manage pests effectively. Research, extension and policy changes are identified to increase the efficiency, adoption and sustainability of IPM on resource-limited farms. The over-arching challenge is devising communication and support systems that allow resource-limited farmers to try, adopt and sustain IPM that enhances yields and profits in light of the many uncertainties and challenges. Use of information technology, media development, crowdsourcing and rural sociology is advocated to connect farmers to the technical sources required to enhance yields and profits and reduce risks to them, the farming community and the environment.
Phenological models for predicting the grapevine flowering were tested using phenological data of 15 grape varieties collected between 1990 and 2014 in Vinhos Verdes and Lisbon Portuguese wine regions. Three models were tested: Spring Warming (Growing Degree Days - GDD model), Spring Warming modified using a triangular function - GDD triangular and UniFORC model, which considers an exponential response curve to temperature. Model estimation was performed using data on two grape varieties (Loureiro and Fernao Pires), present in both regions. Three dates were tested for the beginning of heat unit accumulation (t(0)( )date): budburst, 1 January and 1 September. The best overall date was budburst. Furthermore, for each model parameter, an intermediate range of values common for the studied regions was estimated and further optimized to obtain one model that could he used for a diverse range of grape varieties in both wine regions. External validation was performed using an independent data set from 13 grape varieties (seven red and six white), different from the two used in the estimation step. The results showed a high coefficient of determination (R-2 : 0.59-0.89), low Root Mean Square Error (RMSE: 3-7 days) and Mean Absolute Deviation (MAD: 2-6 days) between predicted and observed values. The UniFORC model overall performed slightly better than the two GDD models, presenting higher R-2 (0.75) and lower RMSE (4.55) and MAD (3.60). The developed phenological models presented good accuracy when applied to several varieties in different regions and can be used as a predictor tool of flowering date in Portugal.