Leaching of nitrate from cropped rainfed terraces in the mid-hills of Nepal

Intensification of crop production in the mid-hills of Nepal has led to concerns that nitrogen loss by leaching may increase. This study estimated the amount of N leached during two years from rainfed terraces (bari-land) at three locations in Nepal. Maize or upland rice grown in the monsoon season was given either no nutrient inputs or inputs via either nitrogen fertilizer or farmyard manure. Nitrate concentration in soil solution was measured regularly with porous ceramic cup samplers and drainage estimated from a simple soil water balance. Estimated losses of nitrogen by leaching ranged from 0 to 63.5 kg N ha(-1) depending on location and the form of nitrogen applied. Losses from plots receiving no nutrient inputs were generally small (range: 0-35 kg N ha(-1)) and losses from plots where nitrogen was applied as manure (range: 2-41 kg N ha(-1)) were typically half those from plots with nitrogen applied as fertilizer. Losses during the post-monsoon crops of finger millet were small (typically <5% of total loss) although losses from the one site with blackgram were larger (about 13%). The highest concentrations of nitrate in solution were measured early in the season as the monsoon rains began and immediately following fertilizer applications. Leaching losses are likely to be minimised if manure is applied as a basal nutrient dressing followed by fertilizer nitrogen later in the season.

Quantitative response of the longevity of seed of twelve crops to temperature and moisture in hermetic storage

Seeds of 39 seed lots of a total of twelve different crops were stored hermetically in a wide range of air-dry environments (2-25% moisture content at 0-50 degrees C), viability assessed periodically, and the seed viability equation constants estimated. Within a species, estimates of the constants which quantify absolute longevity (K-E) and the relative effects on longevity of moisture content (C-W) and temperature (C-H and C-Q) did not differ (P >0.05 to P >0.25) among lots. Comparison among the 12 crops provided variant estimates of K-E and C-W (P< 0.01), but common values of C-H and C-Q (0.0322 and 0.000454, respectively, P >0.25). Maize (Zea mays) provided the greatest estimate of K-E (9.993, s.e.= 0.456), followed by sorghum (Sorghum bicolor) (9.381, s.e. 0.428), pearl millet (Pennisetum typhoides) (9.336, s.e.= 0.408), sugar beet (Beta vulgaris) (8.988, s.e.= 0.387), African rice (Oryza glaberrima) (8.786, s.e.= 0.484), wheat (Triticum aestivum) (8.498, s.e.= 0.431), foxtail millet (Setaria italica) (8.478, s.e.= 0.396), sugarcane (Saccharum sp.) (8.454, s.e.= 0.545), finger millet (Eleusine coracana) (8.288, s.e.= 0.392), kodo millet (Paspalum scrobiculatum) (8.138, s.e.= 0.418), rice (Oryza sativa) (8.096, s.e.= 0.416) and potato (Solanum tuberosum) (8.037, s.e.= 0.397). Similarly, estimates of C-W were ranked maize (5.993, s.e.= 0.392), pearl millet (5.540, s.e.= 0.348), sorghum (5.379, s.e.=0.365), potato (5.152, s.e.= 0.347), sugar beet (4.969, s.e.= 0.328), sugar cane (4.964, s.e.= 0.518), foxtail millet (4.829, s.e.= 0.339), wheat (4.836, s.e.= 0.366), African rice (4.727, s.e.= 0.416), kodo millet (4.435, s.e.= 0.360), finger millet (4.345, s.e.= 0.336) and rice (4.246, s.e.= 0.355). The application of these constants to long-term seed storage is discussed.

Perceptual cues for orientation in a two finger haptic grasp task

Single point interaction haptic devices do not provide the natural grasp and manipulations found in the real world, as afforded by multi-fingered haptics. The present study investigates a two-fingered grasp manipulation involving rotation with and without force feedback. There were three visual cue conditions: monocular, binocular and projective lighting. Performance metrics of time and positional accuracy were assessed. The results indicate that adding haptics to an object manipulation task increases the positional accuracy but slightly increases the overall time taken.

Dextrous hands: issues relating to a four-finger articulated hand

Manipulation of an object by a multi-fingered robot hand requires task planning which involves computation of joint space vectors and fingertip forces. To implement a task as fast as possible, computations have to be carried out in minimum time. The state of the art in manipulation by multi-fingered robot hand designs has shown the possible use of remotely driven finger joints. Such remotely driven hands require computation of tendon displacement for evaluating joint space vectors before signals are sent to actuators. Alternatively, a direct drive hand is a mechanical hand in which the shafts of articulated joints are directly coupled to the rotors of motors with high output torques. This article has been divided into two main sections. The first section presents a brief view of manipulation using a direct drive approach. Meanwhile, the other section presents ongoing research which is being carried out to design a four-finger articulated hand in the Department of Cybernetics at the University of Reading.

Multi-finger grasps in a dynamic environment

Most current state-of-the-art haptic devices render only a single force, however almost all human grasps are characterised by multiple forces and torques applied by the fingers and palms of the hand to the object. In this chapter we will begin by considering the different types of grasp and then consider the physics of rigid objects that will be needed for correct haptic rendering. We then describe an algorithm to represent the forces associated with grasp in a natural manner. The power of the algorithm is that it considers only the capabilities of the haptic device and requires no model of the hand, thus applies to most practical grasp types. The technique is sufficiently general that it would also apply to multi-hand interactions, and hence to collaborative interactions where several people interact with the same rigid object. Key concepts in friction and rigid body dynamics are discussed and applied to the problem of rendering multiple forces to allow the person to choose their grasp on a virtual object and perceive the resulting movement via the forces in a natural way. The algorithm also generalises well to support computation of multi-body physics

Corticomuscular coherence modulation with the pattern of finger force coordination

We assess the corticomuscular coherence (CMC) of the contralateral primary motor cortex and the hand muscles during a finger force-tracking task and explore whether the pattern of finger coordination has an impact on the CMC level. Six healthy subjects (three men and three women) were recruited to conduct the force-tracking tasks comprising two finger patterns, i.e., natural combination of index and middle fingers and unnatural combination of index and middle fingers (i.e., simultaneously producing equal force strength in index and middle finger). During the conducting of the tasks with right index and middle finger, MEG and sEMG signals were recorded from left primary motor cortex (M1) and right flexor digitorum superficialis (FDS), respectively; the contralateral CMC was calculated to assess the neuromuscular interaction. Finger force-tracking tasks of Common-IM only induce beta-band CMC, whereas Uncommon-IM tasks produce CMC in both beta and low-gamma band. Compared to the force-tracking tasks of Common-IM, the Uncommon-IM task is associated with the most intensive contralateral CMC. Our study demonstrated that the pattern of finger coordination had significant impact on the CMC between the contralateral M1 and hand muscles, and more corticomuscular interaction was necessary for unnaturally coordinated finger activities to regulate the fixed neural drive of hand muscles.