Growth Dynamics and Optimal Harvesting Stage of Two Forage Maize Varieties

SAUMZ 1 and SAUMZ 2 are two forage maize varieties reproduced by distant hybridization.In a randomized block experiment,their fresh forage yield and dry matter yield were investigated on the basis of growth period,leaf stage,and effective accumulated temperature.The nutritional components were measured in a near infrared diffuse reflectance spectroscopy.Referring to the concept of forage grading index,a formula was constructed to calculate the total digestible energy.The investigated characters and indexes were adapted to suitable models of growth dynamics.The results showed that these two varieties have strong heterosis in fresh forage yield,dry matter yield,and total digestible energy.Their growth dynamics were adapted to Logistic models described by general equation y=k/（1＋ae-bx）.The forage grading indexes of these two varieties were decreased linearly along with the increasing of their leaf stage.The stopping point of fast growing period of total digestible energy estimated on the basis of leaf stage was suggested to be used as optimal harvesting stage of forage maize.The optimal harvesting stage was estimated to be tasseling stage for SAUMZ 1 and 19.50-leaf stage for SAUMZ 2.

Effects of Planting Date on Development and Field of Forage Maize

[ Objective] To investigate the effects of planting date on development and yield of forage maize and to determine the appropriate plant- ing date for forage maize. [ Method] Using forage maize 50 as experimental material, the development of forage maize was observed, and the yield of forage in the later grain filling period and mature stage was measured, after the maize were planted at different dates, r Remltl With the delaying planting date, phenological period was delayed, and the duration of the same growing stage was shortened among different treatments. The shor- test duration days of anthesis maturity period appeared in the treatment of planting in June 15, and the duration days of anthesis maturity period was increased in the treatment of planting in June 30. With the delaying planting date, the height of maize plant in the five leaf stage was increased. The highest plant in the jointing stage appeared in the treatment of planting in June 15. However, the highest plant appeared in the treatment of planting in May 30 after the jointing stage. The number of green leaves per plant was reduced with the delaying planting date in the tasseling stage, and it was increased with the delaying planting date from later grain filling period to mature stage. With the delaying planting date, the fresh matter yield, forage yield and grain yield were reduced. [ Conclusion] The study provides theoretical and practical reference for high-yield cultivation of forage maize.

Bending properties of green forage maize in field

Stalk lodging is prone to occur during the harvesting of green forage maize due to the header and root anchorage,resulting in loss of harvest.In particular,the fallen stalk wraps around the header,causing a blockage and increasing the energy cost.To address this problem,the deflection model was analyzed and established and a novel method to explore the field bend characteristics of green forage maize was proposed.The effects of stalk diameter,bending angle,and cutting height on bending stress and Young’s modulus were explored by using the method of in-situ measurement.Additionally,the bending deflection,axial displacement and measuring point displacement were obtained.Experimental results indicate that the stalk diameter and bending angle have a significant influence on bending stress.The bending stress has a positive correlation with bending angle and cutting height,while there is a negative correlation with stalk diameter.On the other hand,the bending angle,stalk diameter,and cutting height are closely related to the Young’s modulus.The mean values of the Young’s modulus decrease as a quadratic function with the increasing diameter and bending angle,while the cutting height has the opposite effect on it.Besides,the average values of bending deflection,axial displacement,and measuring point displacement exhibit an increasing trend when the bending angle and cutting height increase.This study results can provide a reference for studying the failure mechanism of green forage maize stalk harvesting,and the design of green forage maize harvesting machinery.

Behavior modelling and sensing for machinery operations using smartphone’s sensor data:A case study of forage maize sowing

Large-scale agricultural machinery cooperatives require technical statistic report of agricultural machinery operations to improve the efficiency of fleet management.This research proposed a smartphone-based solution to build the behavior model for agricultural machinery operations by using the embedded sensors including the GNSS,the accelerometer,and the microphone.The whole working process of agricultural machinery operation was divided into four stages:preparation,operation,U-turn,and transfer,each of which may contain the behaviors of stalling and idling.Field experiments were carried out by skilled operators,whose operations were typical agricultural machinery operations that could be used to extract behavior features.Butterworth low-pass filter was used to smooth the output from the accelerometer.Then,the operating data were collected through an APP when sowing the forage maize as a case study.Four stages of machinery operation can be preliminarily classified by using GNSS speed,while the identification of behaviors such as sudden acceleration and longtime idling that may increase fuel consumption,reduce machinery life,or decrease the working efficiency,requires extra information such as acceleration and sound intensity.The results showed that the jerk of accelerating can describe the severity of the sudden acceleration,the standard deviation of forward acceleration can reflect the smoothness of operation,the upward acceleration can be used to identify behaviors of stalling and idling,and the sound intensity during idling can capture the behavior of goosing the throttle.Further,the operating behavior figure can be drawn based on the above parameters.In conclusion,this research constructed several behavior models of agricultural machinery and operators by using smartphone’s sensor data and established the base of the online assessing and scoring system for agricultural machinery operations.

INTENSIFICATION OF GRASSLAND-BASED DAIRY PRODUCTION AND ITS IMPACTS ON LAND,NITROGEN AND PHOSPHORUS USE EFFICIENCIES

Many grassland-based dairy farms are intensifying production,i.e.,produce more milk per ha of land in response to the increasing demand for milk(by about 2%per year)in a globalized market.However,intensive dairy farming has been implicated for its resources use,ammonia and greenhouse gas emissions,and eutrophication impacts.This paper addresses the question of how the intensity of dairy production relates to N and P surpluses and use efficiencies on farms subjected to agri-environmental regulations.Detailed monitoring data were analyzed from 2858 grassland-based dairy farms in The Netherlands for the year 2015.The farms produced on average 925 Mg·yr^(-1)milk.Milk production per ha ranged from<10 to>30 Mg·ha^(-1)·yr^(-1).Purchased feed and manure export strongly increased with the level of intensification.Surpluses of N and P at farm level remained constant and ammonia emissions per kg milk decreased with the level of intensification.In conclusion,N and P surpluses did not differ much among dairy farms greatly differing in intensity due to legal N and P application limits and obligatory export of manure surpluses to other farms.Further,N and P use efficiencies also did not differ among dairy farms differing in intensity provided the externalization of feed production was accounted for.This paper provides lessons for proper monitoring and control of N and P cycling in dairy farming.