振动深松鼠道犁的试验分析

石河子及周围垦区的土壤粘重且呈盐碱性,由于犁底层的存在,土质很难得到改善。而深松作业则是打破犁底层的主要农业技术措施之一。为此,论述了IZSS-600-3型振动深松鼠道犁的构造和工作原理,分析了试验因素对试验指标的影响,为机具今后在农业生产中的应用和推广提供了依据和参考。     

Re-defining tillage erosion: quantifying intensity–direction relationships for complex terrain

Abstract. Current tillage erosion models account for the influence of tillage direction in the magnitude of the soil (tillage) transport coefficient. It is argued here that this is counter-intuitive and causes significant problems in modelling tillage erosion in areas of complex terrain. This article examines whether a re-modelling of tillage erosion is possible that separates tillage direction (an interaction with the landform) from the soil transport coefficient (a measure of tillage intensity representing the combination of implement erosivity and soil erodibility). Experimental data for mouldboard ploughing upslope, downslope and cross-slope at Coombe Barton Farm, Devon are examined. Integration of data for all directions into a single relationship, which relates translocation in the direction of tillage to slope in the direction of tillage and translocation perpendicular to tillage to slope perpendicular to tillage, is not possible using previously published methods of analysis. However, when total translocation distance is regressed against the tangent of the slope at 45° to the tillage direction (bisecting the tillage direction and the direction of overturning) it is found that a single relationship can be used to describe tillage in all three directions. Therefore, this relationship is used to determine a single value of the soil transport coefficient ( k _fTa) for constant soil and implement conditions but different tillage directions. This redefinition of tillage is important both for true estimation of tillage erosion severity, the adirectional coefficient being 40% larger than the directional coefficient, and for modelling of tillage erosion in complex terrain. These improvements are vital when tillage erosion simulation is used to direct soil conservation strategies.     

The effects of stubble burning and tillage on soil carbon sequestration and crop productivity in southeastern Australia

Abstract. In Australia, stubble burning and tillage are two of the major processes responsible for the decline of soil organic carbon concentration in cropped soils, and the resulting soil degradation. However, the relative importance of these two practices in influencing the soil organic carbon concentration and the long-term impact on soil quality and productivity are not clear. The effects of stubble burning as practised by farmers in southeastern Australia were evaluated in two field trials, one of 19 years duration, the other of 5 years. Conventional tillage (three tillage passes) led to greater loss of soil organic carbon than stubble burning. Loss of total soil organic carbon attributed to stubble burning in the 0–10 cm layer was estimated to be 1.75 t C ha⁻¹ over the period of the 19-year trial, equivalent to 29% of that lost due to tillage. In the 5-year trial, no change in soil organic carbon due to stubble burning was detectable. Changes in soil quality associated with stubble burning detected in the longer trial included a reduction in macro-aggregate stability, and increases in pH and exchangeable K⁺. Only the latter two were detected in the shorter trial. A higher mean wheat yield (average 0.15 t ha⁻¹) following stubble burning was observed in the 19-year trial but not in the 5-year trial. Research to monitor the longer term effects of stubble burning is needed, and to identify conditions where loss of soil organic carbon is minimized.     

深基坑锻锤基础冬期施工

在冬期施工，对于土方开挖、钢筋绑扎、人员的通行、砼的浇铸、砼的温度控制，基坑的保温等都带来一定困难，为此提出了深基坑锻锤基础才是最佳实践应用。     

Simulating evolution of glyphosate resistance in Lolium rigidum II: past, present and future glyphosate use in Australian cropping

Glyphosate is a key component of weed control strategies in Australia and worldwide. Despite widespread and frequent use, evolved resistance to glyphosate is rare. A herbicide resistance model, parameterized for Lolium rigidum has been used to perform a number of simulations to compare predicted rates of evolution of glyphosate resistance under past, present and projected future use strategies. In a 30‐year wheat, lupin, wheat, oilseed rape crop rotation with minimum tillage (100% shallow depth soil disturbance at sowing) and annual use of glyphosate pre‐sowing, L. rigidum control was sustainable with no predicted glyphosate resistance. When the crop establishment system was changed to annual no‐tillage (15% soil disturbance at sowing), glyphosate resistance was predicted in 90% of populations, with resistance becoming apparent after between 10 and 18 years when sowing was delayed. Resistance was predicted in 20% of populations after 25–30 years with early sowing. Risks of glyphosate resistance could be reduced by rotating between no‐tillage and minimum‐tillage establishment systems, or by rotating between glyphosate and paraquat for pre‐sowing weed control. The double knockdown strategy (sequential full rate applications of glyphosate and paraquat) reduced risks of glyphosate and paraquat resistance to <2%. Introduction of glyphosate‐resistant oilseed rape significantly increased predicted risks of glyphosate resistance in no‐tillage systems even when the double knockdown was practised. These increased risks could be offset by high crop sowing rates and weed seed collection at harvest. When no selective herbicides were available in wheat crops, the introduction of glyphosate‐resistant oilseed rape necessitated a return to a minimum‐tillage crop establishment system.     

基于注意力机制的小样本啤酒花病虫害识别

为提高啤酒花产业的品质和产量,针对于传统人工识别鉴定难度大,效率低和客观性不够,以及啤酒花病虫害识别无大型公开数据集等问题.本文提出一种基于软注意力机制的小样本啤酒花病虫害识别方法,对传统深度残差网络ResNet模型进行改进,并使用图像增强技术-直方图均衡化处理图片得到新的数据集.实验结果表明,在小样本情况下,相比于传...     

基于卷积神经网络的家蚕病害识别研究

病害是我国养蚕业健康发展面临的主要威胁之一,为研究机械化养蚕模式下的家蚕病害防治方法,采用卷积神经网络进行家蚕病害图像的识别研究。首先在实际环境下,采用饲养和添食病原的方法,集中获取家蚕品种芳·秀×白·春在大蚕期的部分生长阶段下患脓病、微粒子病、白僵病、细菌病、农药中毒以及健康状态的样本,并开展图像采集工作,构建出家蚕病害图像数据集。其次采用特征融合和缩减结构的方法,对残差神经网络进行部分改进,以避免直接使用该算法会导致不必要的计算耗损。最后进行家蚕病害识别试验。结果表明:卷积神经网络能够高效准确识别家蚕病害图像,使用改进的算法在测试集上的准确率达到94.31%,与标准的残差神经网络准确率相当,但训练的参数量仅为原来的1/3,且识别效率大幅提升,更有利于网络的训练与部署。     

旋耕减阻降耗技术研究进展

我国是农业大国,农业发展关系到国计民生,而耕作是农业生产中的重要环节.随着我国农业机械化发展转型升级,耕作能耗过高,成为农业生产中必须面对的主要问题之一.旋耕作为一种应用广泛的耕作方式,开展旋耕减阻降耗技术研究,对我国农业可持续发展具有重要的现实意义.本文介绍了旋耕减阻降耗技术的研究要点,重点分析了国内外在旋耕刀辊结构...     

The Impact of Natural Deep Eutectic Solvents and Extraction Method on the Co-Extraction of Trace Metals from Fucus vesiculosus

In recent years, natural deep eutectic solvents (NADES) have been widely investigated for the extraction of food and medicinal plants as well as seaweeds. However, the ability of NADES for trace elements co-extraction from natural sources is not well investigated. The aim of this study was to investigate the ability of common NADES for trace elements co-extraction from Fucus vesiculosus. All of the tested NADES did not recover As and Co (concentration <LOQ). Moreover, all of the tested NADES provided a low recovery (<9%) of Ba, Ca, Fe, Mg, Mn, Sr, and Zn. The method of extraction had not shown a statistically significant effect on the co-extraction of all elements (excluding Ba and Ca). In contrast, the water content in NADES was significantly affected on the recovery of Ba, Ca, Mg, Mn, Sr, and Zn. The recovery of Al and Cr was relatively high and considerably varied (from 1.5 to 59.9%). NADES comprising lactic acid:glucose:H₂O (5:3:1) provided the lowest contents of all elements, and the highest extracted amounts were obtained employing water contents of 60–80%. The calculated daily intake of all the elements contained in NADES extracts were less than the daily dose risk estimators. The hazard quotients, hazard indexes, and carcinogenic risk calculated for all trace elements and their combination were considerably less than 1. This evidences no health risk, and carcinogenic risk after topical application of all studied NADES. For the first time, the results of the current study demonstrated that NADES extracts of F. vesiculosus contain a lower amount of trace metals and are safer than the extracts obtained with water and 70% acetone. This indicates a significant advantage for NADES compared with the other solvents.     

FC-CNN:基于卷积神经网络的水果图像分类算法

针对现有基于卷积神经网络的水果图像分类算法均使用池化层进行降维处理会丢失部分特征,导致分类精度有待提高的问题,提出FC-CNN(Fruit Classification Convolutional Neural Network)水果图像分类算法.该算法基于深度卷积神经网络思想,设计了一种由二维卷积层、批量规范化层和激活...