Effect of site-specific irrigation management on grapevine yield and fruit quality attributes

Spatial variation in yield and fruit composition has been observed in many vineyards, leading to low productivity. In this study, site-specific irrigation was applied in a commercial vineyard (Vitis vinifera L. cv. Shiraz) block in the Sunraysia region of Australia to improve production in low-yielding areas of the block and decrease differences in yield and quality between irrigation management zones. Data collected under uniform irrigation management showed that spatial variation in canopy cover, yield and fruit composition across the vineyard block was substantial. Normalised difference vegetation index (NDVI) and canopy temperature data supported delineation of three irrigation management zones and decisions regarding irrigation strategy. Water use efficiency and yield improvements were achieved by implementing site-specific irrigation. Fruit composition results were varied; pH and titratable acidity showed increased similarity between zones, but other parameters maintained differences between zones. These results lend support to the use of NDVI to determine irrigation management zones.     

Sensitivity of root pruned ‘Conference’ pear to water deficit in a temperate climate

The present study examines the need for irrigation in pear trees (Pyrus Communis, cv. ‘Conference’) under low evaporative demand conditions, like in Belgium, in order to maintain a consistent fruit yield and high fruit size. To determine the sensitivity of the pear yield under low evaporative demand conditions three different orchards were monitored. The study shows that a Ψ_soil of −60 kPa during shoot growth has no effect on fruit yield but lower Ψ_soil values induced a decline in both fruit size and total yield. Just as for arid environments a Ψ_stem of −1.5 MPa is related to negative yield responses. In dry conditions lower Ψ_soil and Ψ_stem values were observed in root pruned trees compared to not root pruned trees in the same irrigation treatment, however without yield decline. In one orchard a biannual bearing tendency was observed after root pruning. Furthermore intensive Ψ_soil measurements show a high variation in Ψ_soil between orchards, and within an orchard. This underlines the need for irrigation management on a parcel level and the need for new irrigation scheduling techniques which take the spatial variation in the orchard into account.     

Integrated freshwater aquaculture,crop and livestock production in the Mekong delta,Vietnam: Determinants and the role of the pond

Promotion of integrated aquaculture with agriculture, including crops and livestock (IAA-farming), requires consideration of both bio-physical and socio-economic contexts. The major factors influencing the adoption of IAA-farming by households at three sites in the Mekong delta were identified. Special attention was given to the multiple roles ponds play in IAA-farming systems. Information was collected through semi-structured interviews and discussions with focus groups and key individuals. Data were analyzed using multivariate factor analysis, analysis of variance or participatory ranking methods. Three major IAA-systems were identified: (1) low-input fish farming integrated with intensive fruit production (system 1), (2) medium-input fish farming integrated with less intensive fruit production (system 2), and (3) high-input fish farming integrated with less intensive fruit production (system 3). System 1 was commonly practised in a rural fruit-dominated area with fertile soils, while systems 2 and 3 were more evident in peri-urban rice-dominated areas with less fertile soils. In the study area, only 6% of poor farmers adopted IAA-farming, while this was 42% for intermediate and 60% for rich households. Richer farmers tended to intensify fish farming and seek a more commercial orientation. The major factors why farmers did not start aquaculture were the inappropriateness of technology, insufficient land holding or poor access to extension services, limited farm management, and through a fear of conflicts associated with pesticide use on crops. The main motivations for practising IAA-farming included increased income and food for home consumption from the available farm resources while reducing environmental impacts. Further improvements to IAA-systems can be realized by strengthening nutrient recycling between different IAA-system components while enhancing farming output and safeguarding the environment.     

施肥胁迫对温室番茄不同生长期表型数据的影响

为了研究不同水肥策略对温室番茄长势的影响,试验选择常见的适合温室种植的小番茄（彩玉）为研究对象,以不同配比的水溶性肥,设置了4种施水肥水平。试验过程中,分别采集4种水肥条件下的番茄株高、株径、茎节数、花序数和果实参数等表型数据。采用ANOVA单因素分析方法,对试验数据进行对比分析。不同配比水肥对番茄长势存在显著差异。其中,高施肥水平（Ⅳ）能够得到最佳产量。而中等水肥（Ⅲ）长势最佳,具有最大单果质量,且与不施肥和较少量施肥相比,其长势和果实产量优势明显,经济效益显著。对果实数、株高、茎节数、花序数和产量进行多因素回归分析,决定系数R2为0.965,其差异显著性顺序依次为果实数、株高、茎节数和花序数。试验结果表明,中等水肥配比下,表型数据的自动采集和分析能够对温室番茄水肥一体化设备灌溉策略的制定提供参考。     

人工智能辅助种植策略对温室草莓生产调控效果对比研究

人工智能（Artificial Intelligence,AI）辅助种植有助于提高设施园艺作物精准化管理水平、缓解日益凸显的劳动力紧缺问题。草莓是典型的劳动密集型园艺作物,研究对比采用不同AI种植策略和关键技术对草莓温室生产的调控效果,可对园艺作物种植的AI技术改进和产业化应用提供参考。本研究对比分析了4个不同AI种植策略对草莓生长发育和产量及品质的调控效果,并以人工种植管理为参照,对AI种植的技术特点和存在问题进行了分析。结果表明,知识图谱、深度学习、视觉识别、作物模型和作物生长仿真器等技术在草莓AI种植中各有优势。其中,AI-1组采用知识图谱技术将专家经验、作物数据和环境数据进行融合,建立了标准化草莓种植知识结构和智慧种植决策方法,对作物生产发育的调控较为稳健,以较低的投入获得了最高产值。与人工种植管理相比,AI种植策略组的平均产量提高了1.66倍,平均产值提高了1.82倍,最高投入产投比提高了1.27倍。针对高产优质的目标,在配备较完善的智能化设备和控制组件的温室生产条件下,AI辅助种植能有效提高草莓种植管控的精准度,减少水肥和劳动力的投入,获得较高的收益,但也存在对人工管理扰动的模拟难、作物本体信息采集难等问题。     

Alfalfa yield as related to transpiration,growth stage and environment

Summary The utility of water production models as irrigation management tools is dependent upon their accuracy. Development of precise water production models requires a thorough understanding of how water and other factors interact to affect plant growth and yield. The objective of this experiment was to identify significant environmental variables which control water production function (transpiration vs. yield) variability between harvests and seasons for alfalfa (Medicago sativa L.) over a seven year (1981–1987) period in northwestern New Mexico. A single line-source design was used to supply a continuous gradient of irrigation (I) to the crop, and transpiration (T) was calculated as the difference between evapotranspiration, as estimated by the water balance method, and modeled soil water evaporation at each I level. Yield per cutting was found to be a function of T, growing degree-day accumulation, average daily solar radiation, year and harvest number within year. A multiple regression equation formulated with these variables explained 82% of the yield variability. Average yield per cut in 1981 at 50 mm of T was l Mg ha^-1 and in 1985 at the same level of T was 2 Mg ha^-1 based on the regression model. Yield per cut at any given level of T, as estimated by the coefficients of this equation reached a maximum at year 5.7 and a minimum in year 1. Within a season, yield per unit T was generally greatest at cut 1 and lowest at cut 2. Total seasonal yield was found to be a function of T and year which explained 90% of yield variability. Yield varied from 0.83 Mg ha^-1 to 18.1 Mg ha^-1 and T varied from 186 mm to 1298 mm.     

Effects of salinity on fruit yield and quality of tomato grown in soil-less culture in greenhouses in Mediterranean climatic conditions

There is increasing pressure to reduce water use and environmental impact associated with open system, soil-less production in simple, plastic greenhouses on the Mediterranean coast. This may force the adoption of re-circulation of nutrient solutions. In south-eastern Spain, irrigation water is mostly from aquifers and has moderate levels of salinity. The adoption of re-circulation using moderately saline water requires detailed information of crop response to salinity, in order to optimise management. The effect of salinity on fruit yield, yield components and fruit quality of tomato grown in soil-less culture in plastic greenhouses in Mediterranean climate conditions was evaluated. Two spring growing periods (experiments 1 and 2) and one long season, autumn to spring growing period (experiment 3) studies were conducted. Two cultivars, ‘Daniela’ (experiment 1) and ‘Boludo’ (experiments 2 and 3), were used. Seven levels of electrical conductivity (EC) in the nutrient solution were compared in experiment 1 (2.5–8.0 dS m⁻¹) and five levels in experiments 2 and 3 (2.5–8.5 dS m⁻¹). Total and marketable yield decreased linearly with increasing salinity above a threshold EC value (EC_t). There were only small effects of climate and cultivar on the EC_t value for yield. Average threshold EC values for total and marketable fruit yield were, respectively, 3.2 and 3.3 dS m⁻¹. The linear reductions of total and marketable yield with EC above EC_t showed significant differences between experiments, the slope varying from 7.2% (autumn to spring period, ‘Boludo’) to 9.9% (spring period, ‘Boludo’) decreases per dS m⁻¹ increase in EC for total yield, and from 8.1% (spring period, ‘Daniela’) to 11.8% (spring period, ‘Boludo’) for marketable yield. The decrease of fresh fruit yield with salinity was mostly due to a linear decrease of the fruit weight of 6.1% per dS m⁻¹ from an EC_t of 3.0 dS m⁻¹ for marketable fruits. Reduction in fruit number with salinity made a smaller relative contribution to reduced yield. Blossom-end rot (BER) increased with increasing salinity. There was a higher incidence of BER with spring grown crops, and ‘Boludo’ was more sensitive than ‘Daniela’. Increasing salinity improved various aspects of fruit quality, such as: (i) proportion of ‘Extra’ fruits (high visual quality), (ii) soluble solids content, and (iii) titratable acidity content. However, salinity decreased fruit size, which is a major determinant of price. An economic analysis indicated that the EC threshold value above which the value of fruit production decreased linearly with increasing salinity was 3.3 dS m⁻¹, which was the same as that for marketable yield. In the economic analysis, the value of increased visual fruit quality was offset by reduced yield and smaller fruit size.     

Long-term growth and yield responses of olive trees to different irrigation regimes

The aim of this work was to evaluate long-term effects of different irrigation regimes on mature olive trees growing under field conditions. A 9-year experiment was carried out. Three irrigation treatments were applied: no irrigation, water application considering soil water content (short irrigation), or irrigation without considering soil water reserves and applying a 20% of extra water as a leaching fraction (long irrigation). Leaf water content, leaf area, vegetative growth, yield and fruit characteristics (fruit size, pulp:stone ratio and oil content) were determined yearly. Results showed that growth parameters did not show significant differences as a consequence of applied water. Yield was increased in irrigated trees compared to non-irrigated ones, but little differences between short and long irrigation were observed, only when accumulated yield from 1998 to 2006 was considered. Irrigation did not cause significant differences in fruit size or pulp:stone ratio either. Irrigation regimes similar to those applied in this experiment, under environmental conditions with relatively high mean annual precipitation, does not increase growth, yield or fruit characteristics when compared to rain-fed treatment, and consequently, the installation of a irrigation system could be not financially profitable.     

Yield and quality of furrow and trickle irrigated hop (Humulus lupulus L.) in Washington State

The results of a 2 year study of the effect of trickle and furrow irrigation methods on hop production in a desert region in northwest United States are presented. Also discussed are the implications to hop production in areas with higher rainfall.Trickle, furrow, and cutback furrow irrigation systems and their associated methods of fertilization were evaluated in a commercial hop yard. Leaf diffusive resistance, leaf water potential, alpha and beta acid content, and yield were measured. Also monitored was the efficiency of irrigation water use and the intregration of these irrigation methods with commercial crop production practices. Trickle irrigation with fertilizer injection provided several crop management advantages but required changes in cultivation practices. In the 2nd year of study, the highest yield and quality of hop was obtained from trickle irrigated plots which received the least amounts of water, fertilizer and labor inputs.     

Interaction between water and nitrogen management in peaches for processing

A three-year field experiment (2006–2008) on clingstone peach cv. Andross was conducted in a commercial orchard under mechanical harvesting for the processing industry. Three irrigation strategies were evaluated: full irrigation throughout the growing season; restricted irrigation during stage-II (~70% restriction) and restricted irrigation during stage-III (~30% restriction), combined with three nitrogen fertilization treatments: 0, 60 and 120 kg N/ha. Trees were fertigated on a daily basis. Daily patterns of soil moisture were monitored with capacitance probes. Irrigation restriction strategies and nitrogen dose affected yield and fruit quality at commercial harvest. As well as the individual effects of applying irrigation strategies and N doses, interactions between the two factors were analyzed. In the second year, there was a nitrogen × irrigation interaction for fruit yield. A positive yield effect for N applied to fully irrigated trees occured, while the opposite was observed when the irrigation restrictions were applied during stage-III.     

基于机器学习的机械压实对大豆产量的影响预测研究

为评估农业机械作业对大豆产量的影响，本文开展不同机型、不同压实次数的拖拉机压实试验，获取不同压实环境中的土壤物理性质和大豆产量数据，分别从影响大豆产量的机械因素、土壤因素和复合因素出发，使用多元线性回归(Multiple linear regression, MLR)、随机森林(Random forest, RF)、自适应增强模型(Adaptive boosting, AdaBoost)、人工神经网络(Artificial neural network, ANN)4种机器学习算法建立大豆产量影响预测模型，对模型性能及模型特征重要性进行综合分析。研究结果表明，机械作业与大豆产量间关系复杂，集成学习算法(AdaBoost和RF)所建立的模型具有更好的拟合效果，模型决定系数更高；利用复合因素对大豆产量建立的模型拟合度最高，其次为机械因素和土壤因素，其中基于AdaBoost的复合因素对大豆产量影响模型其拟合程度最优，其R²为0.92,MAE为1.33%,RMSE为1.86%;机械因素、土壤因素都会影响大豆产量，其中机械压实次数以及表层和亚表层的土壤坚实度为影响大豆产量的重...     

基于模糊PID控制的NB-IoT果蔬农业物联网系统设计与试验

针对传统果蔬农业大棚环境数据感知不强、现场维护工作量大、无线覆盖区域受限、生产管理效率低、成本高的问题,提出一套基于模糊PID控制的NB-IoT果蔬农业物联网系统设计。以STM32L475VET6超低功耗芯片为主控芯片,通过NB-IoT和ZigBee双协议融合组网技术和环形缓冲队列算法组建广域无线网络,设计现场监测终端与远程云监控平台,将局域终端节点采集的环境因子信息接入云服务器进行统计与分析。系统根据采集到的数据自动调控反馈控制设备,达到低功耗模式下的广域覆盖监测并智能反馈调控果蔬大棚环境因子的目的,实现感知层、网络层到平台层和应用层一套完整的果蔬大棚物联网系统设计。将模糊PID控制算法应用于温棚环境调节的仿真测试表明,系统平均丢包率为0.088%,空气温湿度、土壤温湿度、二氧化碳浓度等环境因子参数平均相对误差保持在0.5%以内,NB-IoT休眠功耗小于9μA,能实现智能反馈控制并保证系统多节点部署、多参数检测、低功耗工作、广覆盖通信的条件,使系统具有更高的复杂环境适应性和稳定性。     

Regional crop modelling in Europe: The impact of climatic conditions and farm characteristics on maize yields

Impacts of climate variability and climate change on regional crop yields are commonly assessed using process-based crop models. These models, however, simulate potential and water limited yields, which do not always relate to observed yields. The latter are largely influenced by crop management, which varies by farm and region. Data on specific management strategies may be obtained at the field level, but at the regional level information about the diversity in management strategies is rarely available and difficult to be considered adequately in process-based crop models. Alternatively, understanding the factors influencing management may provide helpful information to improve simulations at the regional level.In this study, we aim to identify factors at the regional level that explain differences between observed and simulated yields. Observed yield data were provided by the Farm Accountancy Data Network (FADN) and Eurostat. The Crop Growth Monitoring System (CGMS), based on the WOFOST model, was used to simulate potential and water limited maize yields in the EU15 (i.e., the old member states of the European Union). Differences between observed and simulated maize yields were analysed using regression models including: (i) climatic factors (temperature and precipitation), (ii) farm size, (iii) farm intensity, (iv) land use, (v) income and (vi) subsidies. We assumed that the highest yields observed in a region were close to the yield potential as determined by climate and considered the average regional yields as also influenced by management. Model performance was analysed with respect to spatial and temporal yield variability.Results indicate that for potential yield, the model performed unsatisfactory in southern regions, where high temperatures increased observed yields which was in contrast to model simulations. When considering management effects, we find that especially irrigation and the maize area explain much of the differences between observed and simulated yields across regions. Simulations of temporal yield variability also diverted from observed data of which about 80% could be explained by the climatic factors (35%) and farm characteristics (50%) considered in the analysis. However, effects of specific factors differed depending on the regions. Accordingly, we propose different groups of regions with factors related to management which should be considered to improve regional yield simulations with CGMS.     

不同灌水量对红枣果实生长及产量的影响

为探究不同灌水量对红枣坐果率、果实生长及产量的影响,以甘肃省民勤县当地7a生骏枣为试验材料,在砂管灌条件下设置3个不同灌水量(2 700、3 375和4 050 m3/hm2)和一个地表滴灌(4 050 m3 /hm2)对照进行大田试验.结果 表明:4 050 m3/hm2灌水量的坐果率和产量均达到最大值,分别为6.7...     

Evaluation of simplified water-crop yield models

Firstly theoretical considerations on three simplified water-crop yield models are given, which are subsequently used for the analysis of a large number of reported irrigation trials on alfalfa, sorghum and maize.Alfalfa (Medicago sativa L.), being a crop on which many irrigation trials have been carried out, was first selected for calibrating and testing the three models. Being the first crop for which these simplified relationships are tested, a number of alternative calculation procedures are tried out, using published data from experiments with varying water application.Sorghum (Sorghum bicolor L. Moench) and maize (Zea mays L.) were next chosen for calibrating and testing. The most important difference between alfalfa on one hand and sorghum and maize on the other is that the latter crops are not used as forage crops, but for grain production, so that one is interested only in a part of the above-ground dry matter production. This leads to a new parameter in the model, the harvest index, which is the ratio between grain and above-ground dry matter production and depends on the distribution of dry matter in the plant during the growing period.Based on earlier work of De Wit (1965), the concept of standard production is presented as a reference type of potential crop production. Two available simplified water-crop yield models based on the concept of standard production are summarized.The Rijtema model treats the water-yield relationship as a diffusion process, by combining diffusion equations for transpiration and photosynthesis. The method therefore is based on functional relationships for the resistances involved. Respiratory losses are accounted for by a factor expressing photosynthetic efficiency. The original Rijtema model is amended by introducing correction factors for the effect of temperature on plant growth and a conversion factor from total dry matter production to harvestable product.The FKZ model is a Blackman-type production model in which a maximum production level is considered. The effect of the production factor water is accounted for by a simplified transpiration/photosynthesis relationship. Water use efficiency (P/E) is considered to vary only with crop-type and vapour pressure deficit. A modification is proposed in which water-use efficiency also depends on potential production conditions.A third, Linear model is derived from the Rijtema model. The Linear model is calibrated for alfalfa using 84 data from different regions all over the world. The validation is carried out using 85 data sets. Ninety-two per cent of the observed variation in yields is explained. For the model calibration for sorghum and maize, 58 and 83 data sets, respectively, from different regions were used. The validation of the model was carried out using 42 and 38 data sets, respectively.The calculation of grain production is based on different relationships with the calculated total dry matter production, depending on water stress in sensitive periods. The grain model is calibrated and tested for sorghum using 108 and 76 data sets, respectively, and for maize using 121 and 93 data sets, respectively. The model explains 81% of the observed variations in sorghum and maize grain yields in experiments under different environmental conditions.The simplified transpiration/photosynthesis used in the original FKZ model does not adequately describe the alfalfa data used. An improved version of this relationship, containing the same functional relationships as found for the Linear model, yielded significant results. The modified model explains 95, 80 and 74% of the observed variation in alfalfa, sorghum and maize yields, respectively, using the same data sets as for the Linear model.The functional relationships derived in the calibration of the Linear model are also introduced in the Rijtema model. A number of alternative relationships for photosynthetic efficiency, stomatal and mesophyll resistance are tried for alfalfa. A significant functional relationship is derived between mesophyll and stomatal resistance at a constant value (0.6) of photosynthetic efficiency. Testing the modified model reveals that 87, 72 and 69% of the observed variation in alfalfa, sorghum and maize yields, respectively, can be explained.All three modified models yield satisfactory results for estimating the effects of alternative water management strategies.     

火龙果设施高产栽培技术

通过多年生产实践,总结了一套火龙果设施高产栽培技术,主要包括定植技术、水肥管理技术、整形修剪技术、温湿度与光照管理技术、花果管理技术和病虫害防治技术等方面,以供北方火龙果种植户参考。      

基于神经网络算法的果树需水预测研究

【目的】准确预测果树需水量。【方法】对采集地果园环境数据进行主成分分析,筛选出影响果树蒸腾量的关键因子。建立以长短时记忆(LSTM)神经网络为基础的预测模型来预测果树蒸腾量。为提高预测的精度,在LSTM神经网络的基础上加入了注意力(Attention)机制,形成Attention-LSTM预测模型。【结果】将改进的模型与其他模型的预测精度进行对比,仿真试验表明,该模型的预测精度最高,RMSE和MSE分别为0.487和0.062。【结论】该预测模型可以准确预测果树蒸腾量,从而实现果园精准灌溉并提高水果产量,具有一定的实际意义。     

GAMEDE: A global activity model for evaluating the sustainability of dairy enterprises Part I – Whole-farm dynamic model

 Crop-livestock farms are complex systems. The interactions operating in such systems involve decisional, biophysical, structural, and environmental factors. Moreover, as farmers face a large range of management options, tools are needed to support their decision-making to enable them to reach production levels meeting their objectives and compatible with their human and physical resources, while controlling their effects on the environment. Gamede, a whole-dairy-farm model, has been developed to explore this complexity and to represent dynamically the effect of management decisions on biomass and nitrogen flows and on numerous sustainability indicators, such as milk and forage crop productivity, labour requirements, nitrogen balance, and nitrogen efficiency.This article describes the integration of six modules accounting for biophysical processes in a dairy farm (forage production; forage conditioning; herd demography; milk, excreta and animal biomass productions; grazing, quality of fertilisers; and nitrogen gaseous emissions) together with a decision system accounting for the farmer’s strategy and technical operations. Most of the six biophysical modules incorporate mathematical models from the literature, but the decision system stems from our own original work.Six commercial farms with different structures, agro-climatic conditions and management strategies were used for validation. The model can explain the differences found in their sustainability indicators at the year scale. The intra-year variability of the main biomass stocks and flows is also well explained. This quantitative validation was completed by a qualitative validation from researcher, adviser and farmer points of view, including simulations of prospective scenarios.     

南方蓝莓智能温室促早熟生产多因子协调控制技术

为达到蓝莓提前上市、获得更大经济效益的目的,本团队将南方蓝莓移至环境可控型智能温室中试验生产,探索研究出南方蓝莓智能温室促早熟生产控制技术.首先从蓝莓物候期、品种特点、土壤pH、水肥灌溉方式、小气候环境区间等方面进行了较为详细全面的调研与总结,明确了无土栽培蓝莓全周期管理要点和环境调控范围;接着基于Venlo型温室对蓝...     

温室生产系统环境控制算法综述

温室是实现作物优质高效生产的重要设施，可以在一定程度上克服传统农业难以解决的限制因素，消除对作物生长不利的环境条件，使其部分或者全部脱离外界气候条件及土壤因素的制约，达到作物高产出、高质量、高效益和工厂化生产的目标。先进温室生产系统的标志之一是可基于温室环境控制系统进行温室生产过程调控，为作物构造合适的生长环境，以提高产量，改善质量。温室生产过程性能的好与坏取决于控制算法。在检索中外文献基础上，介绍了目前控制算法的类型、存在的问题、改进措施和未来发展趋向。