农业机械信息管理平台中会计智能化监测技术研究

为了提高农业机械信息管理平台的智能化服务水平,将云技术和会计智能化监测技术引入到了平台的设计上,并以农机调度系统的平台功能设计为例,在智能监测的基础上,采用粒子群神经网络算法对调度系统进行优化设计.为了验证方法的可行性,以不同作业区块的路径规划模拟为测试对象,将优化前后的调度系统的性能进行了对比.由路径规划距离和调度完...     

基于水氮耦合的枸杞灌溉制度优化

为明确一定养分条件下枸杞耗水量与产量的关系,于2014年和2015年采用2因素3水平对比试验设计,研究了枸杞耗水量与碱解氮消耗量耦合效应对产量的影响,通过回归的耦合模型对基于树种、树龄、碱解氮消耗量的枸杞灌溉制度进行了优化。结果表明：（1）相同施肥条件时,4年树龄时HW产量最高,为1 335.7 kg/hm²,MW产量次之,为1 174.2 kg/hm²,LW产量最低,为1 066.5 kg/hm²,5年树龄时HW产量为2 463.7 kg/hm²,MW产量最高,为2 556.1 kg/hm²,LW产量最低,为2 394.5 kg/hm²;（2）同一灌水水平条件下2年试验均表现出中施肥水平产量最高,高施肥水平产量次之,低施肥水平产量最低,4年树龄MF产量为2 758.0 kg/hm²,HF产量为2 595.5 kg/hm²,LF产量为2 407.0 kg/hm²,5年树龄MF产量为4 113.9 kg/hm²,HF产量为3 652.3 kg/hm²,LF产量为3 532.1 kg/hm²;（3）耗水量、碱解氮消耗量耦合效应显示,2014年产量随着耗水量的增加而增加,而产量随碱解氮消耗量增加呈凸形抛物线趋势变化,2015年产量随耗水量、碱解氮消耗量增加均呈凸形抛物线趋势变化。（4）灌溉制度优化发现1年树龄总ET_a为166.0~198.8 mm,2年树龄总ET_a为194.7~252.5 mm,3年树龄总ET_a为196.6~227.2 mm,4年树龄总ET_a为173.5~221.6 mm,5年树龄总ET_a为179.3~196.6 mm。研究结果可为1~5年树龄宁杞1号枸杞获得理想的产量提供灌溉制度优化参考。     

Performance Assessment of Chlorophyll Meter to Determine When to Irrigate Wheat under Different Soil Moisture Deficit Conditions: An Initial Study

ABSTRACT

Proper irrigation timing can minimize the negative impacts that reduce crop yields. Therefore, in an initial pot experimental study, we assessed the SPAD (Soil–Plant Analysis Development)-chlorophyll meter as a tool to determine proper irrigation timing of wheat under different soil water deficit conditions in a controlled-environment greenhouse. The treatments were controlled irrigation at 100% (T₁), 70% (T₂), 50% (T₃) and 30% (T₄) of soil water content at field capacity; and the growth stages were development, mid-season and late-season. SPAD readings were measured pre-irrigation events. The results indicated that the T₃ and T₂ achieved maximum grain yield per accumulated crop evapotranspiration, i.e. water productivity (0.82 and 0.76 kg m^?3), and were at par with T₁. Moreover, the SPAD readings had a high Pearson’s correlation coefficient with crop evapotranspiration (r = 0.95; P ≤ 0.001) and wheat grain yield (r = 0.90; P ≤ 0.001), indicating that SPAD reading could be used to reliably estimate when to irrigate wheat. Therefore, T₃ and T₂ SPAD readings were averaged to estimate a target limit at which irrigation should be applied. Accordingly, the target limit was defined as >44.76 for the development stage, >50.72 for the mid-season stage, and >37.64 for the late-season stage; readings below this target limit indicate that it is time to irrigate.     

Locating and protecting critical reserve sites to minimize expected and worst-case losses

There has been much recent interest in the development of systematic reserve selection methods that are capable of incorporating uncertainty associated with site destruction. This paper makes a contribution to this line of research by presenting two different optimization models for minimizing species losses within a planning region. Given limited acquisition budgets, the first minimizes expected species losses over all possible site loss patterns outside the reserve network while the second minimizes maximum species losses following the worst-case loss of a restricted subset of nonreserve sites. By incorporating the uncertainty of site destruction directly into the decision planning process, these models allow a conservation planner to take a less defensive and more strategic view of reserve selection that seeks to minimize species losses through the targeted acquisition of high-value/high-risk sites. We compare both of these methods to a more standard approach, which simply maximizes within reserve representation without regard for the varied level of threat faced by different sites and species. Results on a realistic dataset show that significant reductions in species losses can be achieved using either of these more intelligent modeling frameworks.     

Dynamical niche sets-based cooperativeevolutionary algorithm for job shop scheduling

Job shop scheduling is an important part of manufacturing process. Pre-mature, local optimal solution or low convergence rate of Genetic Algorithm may come across in solving scheduling problem in multi-Job shop. To avoid those unhealthy tendencies, this paper introduced the Dynamical Niche Sets-based Cooperative Evolutionary Algorithm model.In the Algorithm, Process-based chromosome encoding method was used; the crossover operator and mutation operator were designed to adjust operation sequences and choose process routes. The cooperative scheduling problem in multi-Job shop was solved using dynamical niche sets technology and multi-population cooperative evolution method. The Experiment result shows the proposed method has good advantages.     

Regulated deficit irrigation effects on growth, yield, grape quality and individual anthocyanin composition in Vitis vinifera L. cv. ‘Tempranillo’

Regulated Deficit Irrigation (RDI) is an irrigation scheduling technique, originally developed for fruit orchards, that has been successfully adapted for winegrape production. The aim of this work is to evaluate the effect of RDI in vegetative growth, yield and harvest quality in ‘Tempranillo’ vineyards grown under semiarid conditions typical in Mediterranean areas. Two RDI strategies were compared with conventional irrigation practices (CI). CI that consisted in a progressive increase in water deficit as summer progressed, whereas RDI strategies (RDI1 and RDI2) had in common a deficit period just after fruit set and, in RDI2, vines were subjected to an additional stress period shortly after veraison. The experiment was carried out in four consecutive seasons in a commercial vineyard.Water stress at the beginning of berry development resulted in an important reduction of both vegetative growth and berry weight in RDI strategies. No differences in sugar concentration were found between treatments, and RDI berries tended to have lower acidity. The most relevant effect of RDI strategies on grape quality was an increase in anthocyanin and phenolics concentration. In RDI1 berries, this increase was mainly an indirect consequence of smaller berry size. However, in the RDI2 treatment the higher berry anthocyanin concentration reported was not exclusively due to a reduction in berry size. Since harvest quality has been clearly improved by any of the RDI strategies in both years, it can be concluded that RDI constitutes an interesting technique to be applied in ‘Tempranillo’ vineyards grown in semiarid areas aiming to obtain high quality grape.     

幼龄期压砂地枸杞产量和品质多指标耦合灌溉制度优化

为提高宁夏中部干旱带幼龄期压砂地枸杞灌水效率,保障枸杞产量和品质,进行了3水平灌水定额(300、225 m³·hm^-2和150 m³·hm^-2)的田间对比试验,采用综合指标增量最优方法对灌溉制度进行了优化。研究发现:枸杞5月上旬萌芽期耗水以土壤蒸发为主,日耗水量0.6～1.2 mm,6月中旬进入夏果花期耗水量增大,日耗水量2.5～3.7 mm,7月中旬枸杞夏果期耗水量继续增大,达2.4～4.3 mm,7月下旬日耗水量最大,为3.2～4.7 mm,8月中旬耗水量下降,日耗水量3.0～4.2 mm。灌水定额对枸杞产量影响显著(P<0.05),灌水定额300 m³·hm^-2时产量最高,为1 402.65 kg·hm^-2;灌水定额225 m³·hm^-2时枸杞多糖、β-胡萝卜素和黄酮较高,含量分别为4.56%、0.15%和0.41%;灌水定额150 m³·hm^-2...     

Optimal on-farm irrigation scheduling with a seasonal water limit using simulated annealing

As water resources are limited and the demand for agricultural products increases, it becomes increasingly important to use irrigation water optimally. At a farm scale, farmer's have a particularly strong incentive to optimize their irrigation water use when the volume of water available over a season is production limiting. In this situation, a farmer's goal is to maximize farm profit, by adjusting when and where irrigation water is used. However, making the very best decisions about when and where to irrigate is not easy, since these daily decisions require consideration of the entire remaining irrigation season. Future rainfall uncertainty further complicates decisions on when and which crops should be subjected to water stress. This paper presents an innovative on-farm irrigation scheduling decision support method called the Canterbury irrigation scheduler (CIS) that is suitable when seasonal water availability is limited. Previous optimal scheduling methods generally use stochastic dynamic programming, which requires over-simplistic plant models, limiting their practical usefulness. The CIS method improves on previous methods because it accommodates realistic plant models. Future farm profit (the objective function) is calculated using a time-series simulation model of the farm. Different irrigation management strategies are tested using the farm simulation model. The irrigation strategies are defined by a set of decision variables, and the decision variables are optimized using simulated annealing. The result of this optimization is an irrigation strategy that maximizes the expected future farm profit. This process is repeated several times during the irrigation season using the CIS method, and the optimal irrigation strategy is modified and improved using updated climate and soil moisture information. The ability of the CIS method to produce near optimal decisions was demonstrated by a comparison to previous stochastic dynamic programming schedulers. A second case study shows the CIS method can incorporate more realistic farm models than is possible when using stochastic dynamic programming. This case study used the FarmWi$e/APSIM model developed by CSIRO, Australia. Results show that when seasonal water limit is the primary constraint on water availability, the CIS could increase pasture yield revenue in Canterbury (New Zealand) in the order of 10%, compared with scheduling irrigation using current state of the art scheduling practice.     

基于供应链的农机制造企业生产计划调度研究

生产计划调度是企业生产管理研究的重要领域。目前的研究多是集中于单个企业内部进行优化,而忽视了企业所在供应链的整体利益。本文从宏观角度研究农机制造企业的生产调度问题,并在此基础上将企业仿生学的研究推广到企业供应链中,从生物学的角度对企业生产计划调度进行研究,为今后的研究提出了新的方向。